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Sample records for based facial feature

  1. Frame-Based Facial Expression Recognition Using Geometrical Features

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    Anwar Saeed

    2014-01-01

    Full Text Available To improve the human-computer interaction (HCI to be as good as human-human interaction, building an efficient approach for human emotion recognition is required. These emotions could be fused from several modalities such as facial expression, hand gesture, acoustic data, and biophysiological data. In this paper, we address the frame-based perception of the universal human facial expressions (happiness, surprise, anger, disgust, fear, and sadness, with the help of several geometrical features. Unlike many other geometry-based approaches, the frame-based method does not rely on prior knowledge of a person-specific neutral expression; this knowledge is gained through human intervention and not available in real scenarios. Additionally, we provide a method to investigate the performance of the geometry-based approaches under various facial point localization errors. From an evaluation on two public benchmark datasets, we have found that using eight facial points, we can achieve the state-of-the-art recognition rate. However, this state-of-the-art geometry-based approach exploits features derived from 68 facial points and requires prior knowledge of the person-specific neutral expression. The expression recognition rate using geometrical features is adversely affected by the errors in the facial point localization, especially for the expressions with subtle facial deformations.

  2. Dynamic facial expression recognition based on geometric and texture features

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    Li, Ming; Wang, Zengfu

    2018-04-01

    Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

  3. Face detection and facial feature localization using notch based templates

    International Nuclear Information System (INIS)

    Qayyum, U.

    2007-01-01

    We present a real time detection off aces from the video with facial feature localization as well as the algorithm capable of differentiating between the face/non-face patterns. The need of face detection and facial feature localization arises in various application of computer vision, so a lot of research is dedicated to come up with a real time solution. The algorithm should remain simple to perform real time whereas it should not compromise on the challenges encountered during the detection and localization phase, keeping simplicity and all challenges i.e. algorithm invariant to scale, translation, and (+-45) rotation transformations. The proposed system contains two parts. Visual guidance and face/non-face classification. The visual guidance phase uses the fusion of motion and color cues to classify skin color. Morphological operation with union-structure component labeling algorithm extracts contiguous regions. Scale normalization is applied by nearest neighbor interpolation method to avoid the effect of different scales. Using the aspect ratio of width and height size. Region of Interest (ROI) is obtained and then passed to face/non-face classifier. Notch (Gaussian) based templates/ filters are used to find circular darker regions in ROI. The classified face region is handed over to facial feature localization phase, which uses YCbCr eyes/lips mask for face feature localization. The empirical results show an accuracy of 90% for five different videos with 1000 face/non-face patterns and processing rate of proposed algorithm is 15 frames/sec. (author)

  4. Facial expression recognition in the wild based on multimodal texture features

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    Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

    2016-11-01

    Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

  5. Assessing the accuracy of perceptions of intelligence based on heritable facial features

    OpenAIRE

    Lee, Anthony J.; Hibbs, Courtney; Wright, Margaret J.; Martin, Nicholas G.; Keller, Matthew C.; Zietsch, Brendan P.

    2017-01-01

    Perceptions of intelligence based on facial features can have a profound impact on many social situations, but findings have been mixed as to whether these judgements are accurate. Even if such perceptions were accurate, the underlying mechanism is unclear. Several possibilities have been proposed, including evolutionary explanations where certain morphological facial features are associated with fitness-related traits (including cognitive development), or that intelligence judgements are ove...

  6. Learning representative features for facial images based on a modified principal component analysis

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    Averkin, Anton; Potapov, Alexey

    2013-05-01

    The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.

  7. An Algorithm Based on the Self-Organized Maps for the Classification of Facial Features

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    Gheorghe Gîlcă

    2015-12-01

    Full Text Available This paper deals with an algorithm based on Self Organized Maps networks which classifies facial features. The proposed algorithm can categorize the facial features defined by the input variables: eyebrow, mouth, eyelids into a map of their grouping. The groups map is based on calculating the distance between each input vector and each output neuron layer , the neuron with the minimum distance being declared winner neuron. The network structure consists of two levels: the first level contains three input vectors, each having forty-one values, while the second level contains the SOM competitive network which consists of 100 neurons. The proposed system can classify facial features quickly and easily using the proposed algorithm based on SOMs.

  8. A Classification Method of Normal and Overweight Females Based on Facial Features for Automated Medical Applications

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    Bum Ju Lee

    2012-01-01

    Full Text Available Obesity and overweight have become serious public health problems worldwide. Obesity and abdominal obesity are associated with type 2 diabetes, cardiovascular diseases, and metabolic syndrome. In this paper, we first suggest a method of predicting normal and overweight females according to body mass index (BMI based on facial features. A total of 688 subjects participated in this study. We obtained the area under the ROC curve (AUC value of 0.861 and kappa value of 0.521 in Female: 21–40 (females aged 21–40 years group, and AUC value of 0.76 and kappa value of 0.401 in Female: 41–60 (females aged 41–60 years group. In two groups, we found many features showing statistical differences between normal and overweight subjects by using an independent two-sample t-test. We demonstrated that it is possible to predict BMI status using facial characteristics. Our results provide useful information for studies of obesity and facial characteristics, and may provide useful clues in the development of applications for alternative diagnosis of obesity in remote healthcare.

  9. Facial expression recognition under partial occlusion based on fusion of global and local features

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    Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

    2018-04-01

    Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

  10. Enhancing facial features by using clear facial features

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    Rofoo, Fanar Fareed Hanna

    2017-09-01

    The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

  11. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin

    2015-07-29

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  12. An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

    KAUST Repository

    Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming

    2015-01-01

    We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

  13. Fusing Facial Features for Face Recognition

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    Jamal Ahmad Dargham

    2012-06-01

    Full Text Available Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three selection methods. It was found out that fusing the facial features gives better recognition rate than either facial feature used individually regardless of the landmark selection method.

  14. Tracking subtle stereotypes of children with trisomy 21: from facial-feature-based to implicit stereotyping.

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    Claire Enea-Drapeau

    Full Text Available BACKGROUND: Stigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome, the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping. METHODOLOGY/PRINCIPAL FINDINGS: The participants were 165 adults including 55 young adult students, 55 non-student adults, and 55 professional caregivers working with intellectually disabled persons. They were faced with implicit association tests (IAT, a well-known technique whereby response latency is used to capture the relative strength with which some groups of people--here photographed faces of typically developing children and children with T21--are automatically (without conscious awareness associated with positive versus negative attributes in memory. Each participant also rated the same photographed faces (consciously accessible evaluations. We provide the first evidence that the positive bias typically found in explicit judgments of children with T21 is smaller for those whose facial features are highly characteristic of this disorder, compared to their counterparts with less distinctive features and to typically developing children. We also show that this bias can coexist with negative evaluations at the implicit level (with large effect sizes, even among professional caregivers. CONCLUSION: These findings support recent models of feature-based stereotyping, and more importantly show how crucial it is to go beyond explicit evaluations to estimate the true extent of stigmatization of intellectually disabled people.

  15. Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

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    Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

    2017-09-01

    Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

  16. Artificial Neural Networks and Gene Expression Programing based age estimation using facial features

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    Baddrud Z. Laskar

    2015-10-01

    Full Text Available This work is about estimating human age automatically through analysis of facial images. It has got a lot of real-world applications. Due to prompt advances in the fields of machine vision, facial image processing, and computer graphics, automatic age estimation via faces in computer is one of the dominant topics these days. This is due to widespread real-world applications, in areas of biometrics, security, surveillance, control, forensic art, entertainment, online customer management and support, along with cosmetology. As it is difficult to estimate the exact age, this system is to estimate a certain range of ages. Four sets of classifications have been used to differentiate a person’s data into one of the different age groups. The uniqueness about this study is the usage of two technologies i.e., Artificial Neural Networks (ANN and Gene Expression Programing (GEP to estimate the age and then compare the results. New methodologies like Gene Expression Programing (GEP have been explored here and significant results were found. The dataset has been developed to provide more efficient results by superior preprocessing methods. This proposed approach has been developed, tested and trained using both the methods. A public data set was used to test the system, FG-NET. The quality of the proposed system for age estimation using facial features is shown by broad experiments on the available database of FG-NET.

  17. Human Amygdala Tracks a Feature-Based Valence Signal Embedded within the Facial Expression of Surprise.

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    Kim, M Justin; Mattek, Alison M; Bennett, Randi H; Solomon, Kimberly M; Shin, Jin; Whalen, Paul J

    2017-09-27

    Human amygdala function has been traditionally associated with processing the affective valence (negative vs positive) of an emotionally charged event, especially those that signal fear or threat. However, this account of human amygdala function can be explained by alternative views, which posit that the amygdala might be tuned to either (1) general emotional arousal (activation vs deactivation) or (2) specific emotion categories (fear vs happy). Delineating the pure effects of valence independent of arousal or emotion category is a challenging task, given that these variables naturally covary under many circumstances. To circumvent this issue and test the sensitivity of the human amygdala to valence values specifically, we measured the dimension of valence within the single facial expression category of surprise. Given the inherent valence ambiguity of this category, we show that surprised expression exemplars are attributed valence and arousal values that are uniquely and naturally uncorrelated. We then present fMRI data from both sexes, showing that the amygdala tracks these consensus valence values. Finally, we provide evidence that these valence values are linked to specific visual features of the mouth region, isolating the signal by which the amygdala detects this valence information. SIGNIFICANCE STATEMENT There is an open question as to whether human amygdala function tracks the valence value of cues in the environment, as opposed to either a more general emotional arousal value or a more specific emotion category distinction. Here, we demonstrate the utility of surprised facial expressions because exemplars within this emotion category take on valence values spanning the dimension of bipolar valence (positive to negative) at a consistent level of emotional arousal. Functional neuroimaging data showed that amygdala responses tracked the valence of surprised facial expressions, unconfounded by arousal. Furthermore, a machine learning classifier identified

  18. Tracking Subtle Stereotypes of Children with Trisomy 21: From Facial-Feature-Based to Implicit Stereotyping

    OpenAIRE

    Enea-Drapeau , Claire; Carlier , Michèle; Huguet , Pascal

    2012-01-01

    International audience; BackgroundStigmatization is one of the greatest obstacles to the successful integration of people with Trisomy 21 (T21 or Down syndrome), the most frequent genetic disorder associated with intellectual disability. Research on attitudes and stereotypes toward these people still focuses on explicit measures subjected to social-desirability biases, and neglects how variability in facial stigmata influences attitudes and stereotyping.Methodology/Principal FindingsThe parti...

  19. Odor valence linearly modulates attractiveness, but not age assessment, of invariant facial features in a memory-based rating task.

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    Seubert, Janina; Gregory, Kristen M; Chamberland, Jessica; Dessirier, Jean-Marc; Lundström, Johan N

    2014-01-01

    Scented cosmetic products are used across cultures as a way to favorably influence one's appearance. While crossmodal effects of odor valence on perceived attractiveness of facial features have been demonstrated experimentally, it is unknown whether they represent a phenomenon specific to affective processing. In this experiment, we presented odors in the context of a face battery with systematic feature manipulations during a speeded response task. Modulatory effects of linear increases of odor valence were investigated by juxtaposing subsequent memory-based ratings tasks--one predominantly affective (attractiveness) and a second, cognitive (age). The linear modulation pattern observed for attractiveness was consistent with additive effects of face and odor appraisal. Effects of odor valence on age perception were not linearly modulated and may be the result of cognitive interference. Affective and cognitive processing of faces thus appear to differ in their susceptibility to modulation by odors, likely as a result of privileged access of olfactory stimuli to affective brain networks. These results are critically discussed with respect to potential biases introduced by the preceding speeded response task.

  20. Towards the automation of forensic facial individualisation: Comparing forensic to non forensic eyebrow features

    NARCIS (Netherlands)

    Zeinstra, Christopher Gerard; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2014-01-01

    The Facial Identification Scientific Working Group (FISWG) publishes recommendations regarding one-to-one facial comparisons. At this moment a draft version of a facial image comparison feature list for morphological analysis has been published. This feature list is based on casework experience by

  1. Effects of Bariatric Surgery on Facial Features

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    Vardan Papoian

    2015-09-01

    Full Text Available BackgroundBariatric surgeries performed in the USA has increased twelve-fold in the past two decades. The effects of rapid weight loss on facial features has not been previously studied. We hypothesized that bariatric surgery will mimic the effects of aging thus giving the patient an older and less attractive appearance.MethodsConsecutive patients were enrolled from the bariatric surgical clinic at our institution. Pre and post weight loss photographs were taken and used to generate two surveys. The surveys were distributed through social media to assess the difference between the preoperative and postoperative facial photos, in terms of patients' perceived age and overall attractiveness. 102 respondents completed the first survey and 95 respondents completed the second survey.ResultsOf the 14 patients, five showed statistically significant change in perceived age (three more likely to be perceived older and two less likely to be perceived older. The patients were assessed to be more attractive postoperatively, which showed statistical significance.ConclusionsWeight loss does affect facial aesthetics. Mild weight loss is perceived by survey respondents to give the appearance of a younger but less attractive patient, while substantial weight loss is perceived to give the appearance of an older but more attractive patient.

  2. Accurate landmarking of three-dimensional facial data in the presence of facial expressions and occlusions using a three-dimensional statistical facial feature model.

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    Zhao, Xi; Dellandréa, Emmanuel; Chen, Liming; Kakadiaris, Ioannis A

    2011-10-01

    Three-dimensional face landmarking aims at automatically localizing facial landmarks and has a wide range of applications (e.g., face recognition, face tracking, and facial expression analysis). Existing methods assume neutral facial expressions and unoccluded faces. In this paper, we propose a general learning-based framework for reliable landmark localization on 3-D facial data under challenging conditions (i.e., facial expressions and occlusions). Our approach relies on a statistical model, called 3-D statistical facial feature model, which learns both the global variations in configurational relationships between landmarks and the local variations of texture and geometry around each landmark. Based on this model, we further propose an occlusion classifier and a fitting algorithm. Results from experiments on three publicly available 3-D face databases (FRGC, BU-3-DFE, and Bosphorus) demonstrate the effectiveness of our approach, in terms of landmarking accuracy and robustness, in the presence of expressions and occlusions.

  3. Facial and Ocular Features of Marfan Syndrome

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    Juan C. Leoni

    2014-10-01

    Full Text Available Marfan syndrome is the most common inherited disorder of connective tissue affecting multiple organ systems. Identification of the facial, ocular and skeletal features should prompt referral for aortic imaging since sudden death by aortic dissection and rupture remains a major cause of death in patients with unrecognized Marfan syndrome. Echocardiography is recommended as the initial imaging test, and once a dilated aortic root is identified magnetic resonance or computed tomography should be done to assess the entire aorta. Prophylactic aortic root replacement is safe and has been demonstrated to improve life expectancy in patients with Marfan syndrome. Medical therapy for Marfan syndrome includes the use of beta blockers in older children and adults with an enlarged aorta. Addition of angiotensin receptor antagonists has been shown to slow the progression of aortic root dilation compared to beta blockers alone. Lifelong and regular follow up in a center for specialized care is important for patients with Marfan syndrome. We present a case of a patient with clinical features of Marfan syndrome and discuss possible therapeutic interventions for her dilated aorta.

  4. Facial feature tracking: a psychophysiological measure to assess exercise intensity?

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    Miles, Kathleen H; Clark, Bradley; Périard, Julien D; Goecke, Roland; Thompson, Kevin G

    2018-04-01

    The primary aim of this study was to determine whether facial feature tracking reliably measures changes in facial movement across varying exercise intensities. Fifteen cyclists completed three, incremental intensity, cycling trials to exhaustion while their faces were recorded with video cameras. Facial feature tracking was found to be a moderately reliable measure of facial movement during incremental intensity cycling (intra-class correlation coefficient = 0.65-0.68). Facial movement (whole face (WF), upper face (UF), lower face (LF) and head movement (HM)) increased with exercise intensity, from lactate threshold one (LT1) until attainment of maximal aerobic power (MAP) (WF 3464 ± 3364mm, P exercise intensities (UF minus LF at: LT1, 1048 ± 383mm; LT2, 1208 ± 611mm; MAP, 1401 ± 712mm; P exercise intensity.

  5. iFER: facial expression recognition using automatically selected geometric eye and eyebrow features

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    Oztel, Ismail; Yolcu, Gozde; Oz, Cemil; Kazan, Serap; Bunyak, Filiz

    2018-03-01

    Facial expressions have an important role in interpersonal communications and estimation of emotional states or intentions. Automatic recognition of facial expressions has led to many practical applications and became one of the important topics in computer vision. We present a facial expression recognition system that relies on geometry-based features extracted from eye and eyebrow regions of the face. The proposed system detects keypoints on frontal face images and forms a feature set using geometric relationships among groups of detected keypoints. Obtained feature set is refined and reduced using the sequential forward selection (SFS) algorithm and fed to a support vector machine classifier to recognize five facial expression classes. The proposed system, iFER (eye-eyebrow only facial expression recognition), is robust to lower face occlusions that may be caused by beards, mustaches, scarves, etc. and lower face motion during speech production. Preliminary experiments on benchmark datasets produced promising results outperforming previous facial expression recognition studies using partial face features, and comparable results to studies using whole face information, only slightly lower by ˜ 2.5 % compared to the best whole face facial recognition system while using only ˜ 1 / 3 of the facial region.

  6. Regression-based Multi-View Facial Expression Recognition

    NARCIS (Netherlands)

    Rudovic, Ognjen; Patras, Ioannis; Pantic, Maja

    2010-01-01

    We present a regression-based scheme for multi-view facial expression recognition based on 2蚠D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a

  7. [Infantile facial paralysis: diagnostic and therapeutic features].

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    Montalt, J; Barona, R; Comeche, C; Basterra, J

    2000-01-01

    This paper deals with a series of 11 cases of peripheral unilateral facial paralyses affecting children under 15 years. Following parameters are reviewed: age, sex, side immobilized, origin, morbid antecedents, clinical and neurophysiological explorations (electroneurography through magnetic stimulation) and the evolutive course of the cases. These items are assembled in 3 sketches in the article. Clinical assessment of face movility is more difficult as the patient is younger, nevertheless electroneurography was possible in the whole group. Clinical restoration was complete, excepting one complicated cholesteatomatous patient. Some aspects concerning the etiology, diagnostic explorations and management of each pediatric case are discussed.

  8. Extracted facial feature of racial closely related faces

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    Liewchavalit, Chalothorn; Akiba, Masakazu; Kanno, Tsuneo; Nagao, Tomoharu

    2010-02-01

    Human faces contain a lot of demographic information such as identity, gender, age, race and emotion. Human being can perceive these pieces of information and use it as an important clue in social interaction with other people. Race perception is considered the most delicacy and sensitive parts of face perception. There are many research concerning image-base race recognition, but most of them are focus on major race group such as Caucasoid, Negroid and Mongoloid. This paper focuses on how people classify race of the racial closely related group. As a sample of racial closely related group, we choose Japanese and Thai face to represents difference between Northern and Southern Mongoloid. Three psychological experiment was performed to study the strategies of face perception on race classification. As a result of psychological experiment, it can be suggested that race perception is an ability that can be learn. Eyes and eyebrows are the most attention point and eyes is a significant factor in race perception. The Principal Component Analysis (PCA) was performed to extract facial features of sample race group. Extracted race features of texture and shape were used to synthesize faces. As the result, it can be suggested that racial feature is rely on detailed texture rather than shape feature. This research is a indispensable important fundamental research on the race perception which are essential in the establishment of human-like race recognition system.

  9. Facial expression recognition based on improved deep belief networks

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    Wu, Yao; Qiu, Weigen

    2017-08-01

    In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

  10. Facial Feature Extraction Using Frequency Map Series in PCNN

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    Rencan Nie

    2016-01-01

    Full Text Available Pulse coupled neural network (PCNN has been widely used in image processing. The 3D binary map series (BMS generated by PCNN effectively describes image feature information such as edges and regional distribution, so BMS can be treated as the basis of extracting 1D oscillation time series (OTS for an image. However, the traditional methods using BMS did not consider the correlation of the binary sequence in BMS and the space structure for every map. By further processing for BMS, a novel facial feature extraction method is proposed. Firstly, consider the correlation among maps in BMS; a method is put forward to transform BMS into frequency map series (FMS, and the method lessens the influence of noncontinuous feature regions in binary images on OTS-BMS. Then, by computing the 2D entropy for every map in FMS, the 3D FMS is transformed into 1D OTS (OTS-FMS, which has good geometry invariance for the facial image, and contains the space structure information of the image. Finally, by analyzing the OTS-FMS, the standard Euclidean distance is used to measure the distances for OTS-FMS. Experimental results verify the effectiveness of OTS-FMS in facial recognition, and it shows better recognition performance than other feature extraction methods.

  11. Orientations for the successful categorization of facial expressions and their link with facial features.

    Science.gov (United States)

    Duncan, Justin; Gosselin, Frédéric; Cobarro, Charlène; Dugas, Gabrielle; Blais, Caroline; Fiset, Daniel

    2017-12-01

    Horizontal information was recently suggested to be crucial for face identification. In the present paper, we expand on this finding and investigate the role of orientations for all the basic facial expressions and neutrality. To this end, we developed orientation bubbles to quantify utilization of the orientation spectrum by the visual system in a facial expression categorization task. We first validated the procedure in Experiment 1 with a simple plaid-detection task. In Experiment 2, we used orientation bubbles to reveal the diagnostic-i.e., task relevant-orientations for the basic facial expressions and neutrality. Overall, we found that horizontal information was highly diagnostic for expressions-surprise excepted. We also found that utilization of horizontal information strongly predicted performance level in this task. Despite the recent surge of research on horizontals, the link with local features remains unexplored. We were thus also interested in investigating this link. In Experiment 3, location bubbles were used to reveal the diagnostic features for the basic facial expressions. Crucially, Experiments 2 and 3 were run in parallel on the same participants, in an interleaved fashion. This way, we were able to correlate individual orientation and local diagnostic profiles. Our results indicate that individual differences in horizontal tuning are best predicted by utilization of the eyes.

  12. Facial expression identification using 3D geometric features from Microsoft Kinect device

    Science.gov (United States)

    Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

    2016-05-01

    Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

  13. Seven Non-melanoma Features to Rule Out Facial Melanoma

    Directory of Open Access Journals (Sweden)

    Philipp Tschandl

    2017-08-01

    Full Text Available Facial melanoma is difficult to diagnose and dermatoscopic features are often subtle. Dermatoscopic non-melanoma patterns may have a comparable diagnostic value. In this pilot study, facial lesions were collected retrospectively, resulting in a case set of 339 melanomas and 308 non-melanomas. Lesions were evaluated for the prevalence (> 50% of lesional surface of 7 dermatoscopic non-melanoma features: scales, white follicles, erythema/reticular vessels, reticular and/or curved lines/fingerprints, structureless brown colour, sharp demarcation, and classic criteria of seborrhoeic keratosis. Melanomas had a lower number of non-melanoma patterns (p < 0.001. Scoring a lesion suspicious when no prevalent non-melanoma pattern is found resulted in a sensitivity of 88.5% and a specificity of 66.9% for the diagnosis of melanoma. Specificity was higher for solar lentigo (78.8% and seborrhoeic keratosis (74.3% and lower for actinic keratosis (61.4% and lichenoid keratosis (25.6%. Evaluation of prevalent non-melanoma patterns can provide slightly lower sensitivity and higher specificity in detecting facial melanoma compared with already known malignant features.

  14. Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

    Science.gov (United States)

    Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

    2016-10-05

    Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

  15. Extraction and representation of common feature from uncertain facial expressions with cloud model.

    Science.gov (United States)

    Wang, Shuliang; Chi, Hehua; Yuan, Hanning; Geng, Jing

    2017-12-01

    Human facial expressions are key ingredient to convert an individual's innate emotion in communication. However, the variation of facial expressions affects the reliable identification of human emotions. In this paper, we present a cloud model to extract facial features for representing human emotion. First, the uncertainties in facial expression are analyzed in the context of cloud model. The feature extraction and representation algorithm is established under cloud generators. With forward cloud generator, facial expression images can be re-generated as many as we like for visually representing the extracted three features, and each feature shows different roles. The effectiveness of the computing model is tested on Japanese Female Facial Expression database. Three common features are extracted from seven facial expression images. Finally, the paper is concluded and remarked.

  16. Millennial Filipino Student Engagement Analyzer Using Facial Feature Classification

    Science.gov (United States)

    Manseras, R.; Eugenio, F.; Palaoag, T.

    2018-03-01

    Millennials has been a word of mouth of everybody and a target market of various companies nowadays. In the Philippines, they comprise one third of the total population and most of them are still in school. Having a good education system is important for this generation to prepare them for better careers. And a good education system means having quality instruction as one of the input component indicators. In a classroom environment, teachers use facial features to measure the affect state of the class. Emerging technologies like Affective Computing is one of today’s trends to improve quality instruction delivery. This, together with computer vision, can be used in analyzing affect states of the students and improve quality instruction delivery. This paper proposed a system of classifying student engagement using facial features. Identifying affect state, specifically Millennial Filipino student engagement, is one of the main priorities of every educator and this directed the authors to develop a tool to assess engagement percentage. Multiple face detection framework using Face API was employed to detect as many student faces as possible to gauge current engagement percentage of the whole class. The binary classifier model using Support Vector Machine (SVM) was primarily set in the conceptual framework of this study. To achieve the most accuracy performance of this model, a comparison of SVM to two of the most widely used binary classifiers were tested. Results show that SVM bested RandomForest and Naive Bayesian algorithms in most of the experiments from the different test datasets.

  17. Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

    Directory of Open Access Journals (Sweden)

    Cheng-Yuan Shih

    2010-01-01

    Full Text Available This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA and quadratic discriminant analysis (QDA. It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

  18. Research on facial expression simulation based on depth image

    Science.gov (United States)

    Ding, Sha-sha; Duan, Jin; Zhao, Yi-wu; Xiao, Bo; Wang, Hao

    2017-11-01

    Nowadays, face expression simulation is widely used in film and television special effects, human-computer interaction and many other fields. Facial expression is captured by the device of Kinect camera .The method of AAM algorithm based on statistical information is employed to detect and track faces. The 2D regression algorithm is applied to align the feature points. Among them, facial feature points are detected automatically and 3D cartoon model feature points are signed artificially. The aligned feature points are mapped by keyframe techniques. In order to improve the animation effect, Non-feature points are interpolated based on empirical models. Under the constraint of Bézier curves we finish the mapping and interpolation. Thus the feature points on the cartoon face model can be driven if the facial expression varies. In this way the purpose of cartoon face expression simulation in real-time is came ture. The experiment result shows that the method proposed in this text can accurately simulate the facial expression. Finally, our method is compared with the previous method. Actual data prove that the implementation efficiency is greatly improved by our method.

  19. The extraction and use of facial features in low bit-rate visual communication.

    Science.gov (United States)

    Pearson, D

    1992-01-29

    A review is given of experimental investigations by the author and his collaborators into methods of extracting binary features from images of the face and hands. The aim of the research has been to enable deaf people to communicate by sign language over the telephone network. Other applications include model-based image coding and facial-recognition systems. The paper deals with the theoretical postulates underlying the successful experimental extraction of facial features. The basic philosophy has been to treat the face as an illuminated three-dimensional object and to identify features from characteristics of their Gaussian maps. It can be shown that in general a composite image operator linked to a directional-illumination estimator is required to accomplish this, although the latter can often be omitted in practice.

  20. Prediction of mortality based on facial characteristics

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    2016-05-01

    Full Text Available Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail. Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.

  1. Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

    Science.gov (United States)

    Wu, Yao; Qiu, Weigen

    2017-08-01

    In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

  2. An Improved AAM Method for Extracting Human Facial Features

    Directory of Open Access Journals (Sweden)

    Tao Zhou

    2012-01-01

    Full Text Available Active appearance model is a statistically parametrical model, which is widely used to extract human facial features and recognition. However, intensity values used in original AAM cannot provide enough information for image texture, which will lead to a larger error or a failure fitting of AAM. In order to overcome these defects and improve the fitting performance of AAM model, an improved texture representation is proposed in this paper. Firstly, translation invariant wavelet transform is performed on face images and then image structure is represented using the measure which is obtained by fusing the low-frequency coefficients with edge intensity. Experimental results show that the improved algorithm can increase the accuracy of the AAM fitting and express more information for structures of edge and texture.

  3. Sensorineural Deafness, Distinctive Facial Features and Abnormal Cranial Bones

    Science.gov (United States)

    Gad, Alona; Laurino, Mercy; Maravilla, Kenneth R.; Matsushita, Mark; Raskind, Wendy H.

    2008-01-01

    The Waardenburg syndromes (WS) account for approximately 2% of congenital sensorineural deafness. This heterogeneous group of diseases currently can be categorized into four major subtypes (WS types 1-4) on the basis of characteristic clinical features. Multiple genes have been implicated in WS, and mutations in some genes can cause more than one WS subtype. In addition to eye, hair and skin pigmentary abnormalities, dystopia canthorum and broad nasal bridge are seen in WS type 1. Mutations in the PAX3 gene are responsible for the condition in the majority of these patients. In addition, mutations in PAX3 have been found in WS type 3 that is distinguished by musculoskeletal abnormalities, and in a family with a rare subtype of WS, craniofacial-deafness-hand syndrome (CDHS), characterized by dysmorphic facial features, hand abnormalities, and absent or hypoplastic nasal and wrist bones. Here we describe a woman who shares some, but not all features of WS type 3 and CDHS, and who also has abnormal cranial bones. All sinuses were hypoplastic, and the cochlea were small. No sequence alteration in PAX3 was found. These observations broaden the clinical range of WS and suggest there may be genetic heterogeneity even within the CDHS subtype. PMID:18553554

  4. A Robust Shape Reconstruction Method for Facial Feature Point Detection

    Directory of Open Access Journals (Sweden)

    Shuqiu Tan

    2017-01-01

    Full Text Available Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed and applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression and gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment dictionary and the local appearance dictionary are learned in a regressive manner to select robust features and fit shape increments. Additionally, to make the learned model more generalized, we select the best matched parameter set through extensive validation tests. Experimental results on three public datasets demonstrate that the proposed method achieves a better robustness over the state-of-the-art methods.

  5. Facial Asymmetry-Based Age Group Estimation: Role in Recognizing Age-Separated Face Images.

    Science.gov (United States)

    Sajid, Muhammad; Taj, Imtiaz Ahmad; Bajwa, Usama Ijaz; Ratyal, Naeem Iqbal

    2018-04-23

    Face recognition aims to establish the identity of a person based on facial characteristics. On the other hand, age group estimation is the automatic calculation of an individual's age range based on facial features. Recognizing age-separated face images is still a challenging research problem due to complex aging processes involving different types of facial tissues, skin, fat, muscles, and bones. Certain holistic and local facial features are used to recognize age-separated face images. However, most of the existing methods recognize face images without incorporating the knowledge learned from age group estimation. In this paper, we propose an age-assisted face recognition approach to handle aging variations. Inspired by the observation that facial asymmetry is an age-dependent intrinsic facial feature, we first use asymmetric facial dimensions to estimate the age group of a given face image. Deeply learned asymmetric facial features are then extracted for face recognition using a deep convolutional neural network (dCNN). Finally, we integrate the knowledge learned from the age group estimation into the face recognition algorithm using the same dCNN. This integration results in a significant improvement in the overall performance compared to using the face recognition algorithm alone. The experimental results on two large facial aging datasets, the MORPH and FERET sets, show that the proposed age group estimation based on the face recognition approach yields superior performance compared to some existing state-of-the-art methods. © 2018 American Academy of Forensic Sciences.

  6. Interpretation of appearance: the effect of facial features on first impressions and personality

    DEFF Research Database (Denmark)

    Wolffhechel, Karin Marie Brandt; Fagertun, Jens; Jacobsen, Ulrik Plesner

    2014-01-01

    Appearance is known to influence social interactions, which in turn could potentially influence personality development. In this study we focus on discovering the relationship between self-reported personality traits, first impressions and facial characteristics. The results reveal that several...... personality traits can be read above chance from a face, and that facial features influence first impressions. Despite the former, our prediction model fails to reliably infer personality traits from either facial features or first impressions. First impressions, however, could be inferred more reliably from...... facial features. We have generated artificial, extreme faces visualising the characteristics having an effect on first impressions for several traits. Conclusively, we find a relationship between first impressions, some personality traits and facial features and consolidate that people on average assess...

  7. Contactless measurement of muscles fatigue by tracking facial feature points in a video

    DEFF Research Database (Denmark)

    Irani, Ramin; Nasrollahi, Kamal; Moeslund, Thomas B.

    2014-01-01

    their exercises when the level of the fatigue might be dangerous for the patients. The current technology for measuring tiredness, like Electromyography (EMG), requires installing some sensors on the body. In some applications, like remote patient monitoring, this however might not be possible. To deal...... with such cases, in this paper we present a contactless method based on computer vision techniques to measure tiredness by detecting, tracking, and analyzing some facial feature points during the exercise. Experimental results on several test subjects and comparing them against ground truth data show...... that the proposed system can properly find the temporal point of tiredness of the muscles when the test subjects are doing physical exercises....

  8. Contributions of feature shapes and surface cues to the recognition of facial expressions.

    Science.gov (United States)

    Sormaz, Mladen; Young, Andrew W; Andrews, Timothy J

    2016-10-01

    Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Feature selection from a facial image for distinction of sasang constitution.

    Science.gov (United States)

    Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun; Kim, Keun Ho

    2009-09-01

    Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

  10. Feature Selection from a Facial Image for Distinction of Sasang Constitution

    Directory of Open Access Journals (Sweden)

    Imhoi Koo

    2009-01-01

    Full Text Available Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

  11. Feature Selection from a Facial Image for Distinction of Sasang Constitution

    Science.gov (United States)

    Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun

    2009-01-01

    Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here. PMID:19745013

  12. Biometric identification based on novel frequency domain facial asymmetry measures

    Science.gov (United States)

    Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

    2005-03-01

    In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.

  13. Resorcinarene-Based Facial Glycosides

    DEFF Research Database (Denmark)

    Hussain, Hazrat; Du, Yang; Tikhonova, Elena

    2017-01-01

    degradation during extraction and purification, thus necessitating the development of new agents with enhanced properties. In the current study, two classes of new amphiphiles are introduced, resorcinarene-based glucoside and maltoside amphiphiles (designated RGAs and RMAs, respectively), for which the alkyl...

  14. Binary pattern flavored feature extractors for Facial Expression Recognition: An overview

    DEFF Research Database (Denmark)

    Kristensen, Rasmus Lyngby; Tan, Zheng-Hua; Ma, Zhanyu

    2015-01-01

    This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression Recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER...

  15. Perceptually Valid Facial Expressions for Character-Based Applications

    Directory of Open Access Journals (Sweden)

    Ali Arya

    2009-01-01

    Full Text Available This paper addresses the problem of creating facial expression of mixed emotions in a perceptually valid way. The research has been done in the context of a “game-like” health and education applications aimed at studying social competency and facial expression awareness in autistic children as well as native language learning, but the results can be applied to many other applications such as games with need for dynamic facial expressions or tools for automating the creation of facial animations. Most existing methods for creating facial expressions of mixed emotions use operations like averaging to create the combined effect of two universal emotions. Such methods may be mathematically justifiable but are not necessarily valid from a perceptual point of view. The research reported here starts by user experiments aiming at understanding how people combine facial actions to express mixed emotions, and how the viewers perceive a set of facial actions in terms of underlying emotions. Using the results of these experiments and a three-dimensional emotion model, we associate facial actions to dimensions and regions in the emotion space, and create a facial expression based on the location of the mixed emotion in the three-dimensional space. We call these regionalized facial actions “facial expression units.”

  16. The importance of internal facial features in learning new faces.

    Science.gov (United States)

    Longmore, Christopher A; Liu, Chang Hong; Young, Andrew W

    2015-01-01

    For familiar faces, the internal features (eyes, nose, and mouth) are known to be differentially salient for recognition compared to external features such as hairstyle. Two experiments are reported that investigate how this internal feature advantage accrues as a face becomes familiar. In Experiment 1, we tested the contribution of internal and external features to the ability to generalize from a single studied photograph to different views of the same face. A recognition advantage for the internal features over the external features was found after a change of viewpoint, whereas there was no internal feature advantage when the same image was used at study and test. In Experiment 2, we removed the most salient external feature (hairstyle) from studied photographs and looked at how this affected generalization to a novel viewpoint. Removing the hair from images of the face assisted generalization to novel viewpoints, and this was especially the case when photographs showing more than one viewpoint were studied. The results suggest that the internal features play an important role in the generalization between different images of an individual's face by enabling the viewer to detect the common identity-diagnostic elements across non-identical instances of the face.

  17. Active AU Based Patch Weighting for Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Weicheng Xie

    2017-01-01

    Full Text Available Facial expression has many applications in human-computer interaction. Although feature extraction and selection have been well studied, the specificity of each expression variation is not fully explored in state-of-the-art works. In this work, the problem of multiclass expression recognition is converted into triplet-wise expression recognition. For each expression triplet, a new feature optimization model based on action unit (AU weighting and patch weight optimization is proposed to represent the specificity of the expression triplet. The sparse representation-based approach is then proposed to detect the active AUs of the testing sample for better generalization. The algorithm achieved competitive accuracies of 89.67% and 94.09% for the Jaffe and Cohn–Kanade (CK+ databases, respectively. Better cross-database performance has also been observed.

  18. Recovering Faces from Memory: The Distracting Influence of External Facial Features

    Science.gov (United States)

    Frowd, Charlie D.; Skelton, Faye; Atherton, Chris; Pitchford, Melanie; Hepton, Gemma; Holden, Laura; McIntyre, Alex H.; Hancock, Peter J. B.

    2012-01-01

    Recognition memory for unfamiliar faces is facilitated when contextual cues (e.g., head pose, background environment, hair and clothing) are consistent between study and test. By contrast, inconsistencies in external features, especially hair, promote errors in unfamiliar face-matching tasks. For the construction of facial composites, as carried…

  19. Newborns' Face Recognition: Role of Inner and Outer Facial Features

    Science.gov (United States)

    Turati, Chiara; Macchi Cassia, Viola; Simion, Francesca; Leo, Irene

    2006-01-01

    Existing data indicate that newborns are able to recognize individual faces, but little is known about what perceptual cues drive this ability. The current study showed that either the inner or outer features of the face can act as sufficient cues for newborns' face recognition (Experiment 1), but the outer part of the face enjoys an advantage…

  20. Spectrum of mucocutaneous, ocular and facial features and delineation of novel presentations in 62 classical Ehlers-Danlos syndrome patients.

    Science.gov (United States)

    Colombi, M; Dordoni, C; Venturini, M; Ciaccio, C; Morlino, S; Chiarelli, N; Zanca, A; Calzavara-Pinton, P; Zoppi, N; Castori, M; Ritelli, M

    2017-12-01

    Classical Ehlers-Danlos syndrome (cEDS) is characterized by marked cutaneous involvement, according to the Villefranche nosology and its 2017 revision. However, the diagnostic flow-chart that prompts molecular testing is still based on experts' opinion rather than systematic published data. Here we report on 62 molecularly characterized cEDS patients with focus on skin, mucosal, facial, and articular manifestations. The major and minor Villefranche criteria, additional 11 mucocutaneous signs and 15 facial dysmorphic traits were ascertained and feature rates compared by sex and age. In our cohort, we did not observe any mandatory clinical sign. Skin hyperextensibility plus atrophic scars was the most frequent combination, whereas generalized joint hypermobility according to the Beighton score decreased with age. Skin was more commonly hyperextensible on elbows, neck, and knees. The sites more frequently affected by abnormal atrophic scarring were knees, face (especially forehead), pretibial area, and elbows. Facial dysmorphism commonly affected midface/orbital areas with epicanthal folds and infraorbital creases more commonly observed in young patients. Our findings suggest that the combination of ≥1 eye dysmorphism and facial/forehead scars may support the diagnosis in children. Minor acquired traits, such as molluscoid pseudotumors, subcutaneous spheroids, and signs of premature skin aging are equally useful in adults. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  1. Support vector machine-based facial-expression recognition method combining shape and appearance

    Science.gov (United States)

    Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

    2010-11-01

    Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

  2. The Association of Quantitative Facial Color Features with Cold Pattern in Traditional East Asian Medicine

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    Sujeong Mun

    2017-01-01

    Full Text Available Introduction. Facial diagnosis is a major component of the diagnostic method in traditional East Asian medicine. We investigated the association of quantitative facial color features with cold pattern using a fully automated facial color parameterization system. Methods. The facial color parameters of 64 participants were obtained from digital photographs using an automatic color correction and color parameter calculation system. Cold pattern severity was evaluated using a questionnaire. Results. The a⁎ values of the whole face, lower cheek, and chin were negatively associated with cold pattern score (CPS (whole face: B=-1.048, P=0.021; lower cheek: B=-0.494, P=0.007; chin: B=-0.640, P=0.031, while b⁎ value of the lower cheek was positively associated with CPS (B=0.234, P=0.019. The a⁎ values of the whole face were significantly correlated with specific cold pattern symptoms including cold abdomen (partial ρ=-0.354, P<0.01 and cold sensation in the body (partial ρ=-0.255, P<0.05. Conclusions. a⁎ values of the whole face were negatively associated with CPS, indicating that individuals with increased levels of cold pattern had paler faces. These findings suggest that objective facial diagnosis has utility for pattern identification.

  3. Feature Fusion Algorithm for Multimodal Emotion Recognition from Speech and Facial Expression Signal

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    Han Zhiyan

    2016-01-01

    Full Text Available In order to overcome the limitation of single mode emotion recognition. This paper describes a novel multimodal emotion recognition algorithm, and takes speech signal and facial expression signal as the research subjects. First, fuse the speech signal feature and facial expression signal feature, get sample sets by putting back sampling, and then get classifiers by BP neural network (BPNN. Second, measure the difference between two classifiers by double error difference selection strategy. Finally, get the final recognition result by the majority voting rule. Experiments show the method improves the accuracy of emotion recognition by giving full play to the advantages of decision level fusion and feature level fusion, and makes the whole fusion process close to human emotion recognition more, with a recognition rate 90.4%.

  4. Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram

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    Lei Zhao

    2017-01-01

    Full Text Available This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better.

  5. Facial Image Compression Based on Structured Codebooks in Overcomplete Domain

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    Vila-Forcén JE

    2006-01-01

    Full Text Available We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.

  6. Robust facial landmark detection based on initializing multiple poses

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    Xin Chai

    2016-10-01

    Full Text Available For robot systems, robust facial landmark detection is the first and critical step for face-based human identification and facial expression recognition. In recent years, the cascaded-regression-based method has achieved excellent performance in facial landmark detection. Nevertheless, it still has certain weakness, such as high sensitivity to the initialization. To address this problem, regression based on multiple initializations is established in a unified model; face shapes are then estimated independently according to these initializations. With a ranking strategy, the best estimate is selected as the final output. Moreover, a face shape model based on restricted Boltzmann machines is built as a constraint to improve the robustness of ranking. Experiments on three challenging datasets demonstrate the effectiveness of the proposed facial landmark detection method against state-of-the-art methods.

  7. Facial Expression Recognition Based on TensorFlow Platform

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    Xia Xiao-Ling

    2017-01-01

    Full Text Available Facial expression recognition have a wide range of applications in human-machine interaction, pattern recognition, image understanding, machine vision and other fields. Recent years, it has gradually become a hot research. However, different people have different ways of expressing their emotions, and under the influence of brightness, background and other factors, there are some difficulties in facial expression recognition. In this paper, based on the Inception-v3 model of TensorFlow platform, we use the transfer learning techniques to retrain facial expression dataset (The Extended Cohn-Kanade dataset, which can keep the accuracy of recognition and greatly reduce the training time.

  8. Alagille syndrome in a Vietnamese cohort: mutation analysis and assessment of facial features.

    Science.gov (United States)

    Lin, Henry C; Le Hoang, Phuc; Hutchinson, Anne; Chao, Grace; Gerfen, Jennifer; Loomes, Kathleen M; Krantz, Ian; Kamath, Binita M; Spinner, Nancy B

    2012-05-01

    Alagille syndrome (ALGS, OMIM #118450) is an autosomal dominant disorder that affects multiple organ systems including the liver, heart, eyes, vertebrae, and face. ALGS is caused by mutations in one of two genes in the Notch Signaling Pathway, Jagged1 (JAG1) or NOTCH2. In this study, analysis of 21 Vietnamese ALGS individuals led to the identification of 19 different mutations (18 JAG1 and 1 NOTCH2), 17 of which are novel, including the third reported NOTCH2 mutation in Alagille Syndrome. The spectrum of JAG1 mutations in the Vietnamese patients is similar to that previously reported, including nine frameshift, three missense, two splice site, one nonsense, two whole gene, and one partial gene deletion. The missense mutations are all likely to be disease causing, as two are loss of cysteines (C22R and C78G) and the third creates a cryptic splice site in exon 9 (G386R). No correlation between genotype and phenotype was observed. Assessment of clinical phenotype revealed that skeletal manifestations occur with a higher frequency than in previously reported Alagille cohorts. Facial features were difficult to assess and a Vietnamese pediatric gastroenterologist was only able to identify the facial phenotype in 61% of the cohort. To assess the agreement among North American dysmorphologists at detecting the presence of ALGS facial features in the Vietnamese patients, 37 clinical dysmorphologists evaluated a photographic panel of 20 Vietnamese children with and without ALGS. The dysmorphologists were unable to identify the individuals with ALGS in the majority of cases, suggesting that evaluation of facial features should not be used in the diagnosis of ALGS in this population. This is the first report of mutations and phenotypic spectrum of ALGS in a Vietnamese population. Copyright © 2012 Wiley Periodicals, Inc.

  9. Ring 2 chromosome associated with failure to thrive, microcephaly and dysmorphic facial features.

    Science.gov (United States)

    López-Uriarte, Arelí; Quintero-Rivera, Fabiola; de la Fuente Cortez, Beatriz; Puente, Viviana Gómez; Campos, María Del Roble Velazco; de Villarreal, Laura E Martínez

    2013-10-15

    We report here a child with a ring chromosome 2 [r(2)] associated with failure to thrive, microcephaly and dysmorphic features. The chromosomal aberration was defined by chromosome microarray analysis, revealing two small deletions of 2p25.3 (139 kb) and 2q37.3 (147 kb). We show the clinical phenotype of the patient, using a conventional approach and the molecular cytogenetics of a male with a history of prenatal intrauterine growth restriction (IUGR), failure to thrive, microcephaly and dysmorphic facial features. The phenotype is very similar to that reported in other clinical cases with ring chromosome 2. © 2013 Elsevier B.V. All rights reserved.

  10. Facial anatomy.

    Science.gov (United States)

    Marur, Tania; Tuna, Yakup; Demirci, Selman

    2014-01-01

    Dermatologic problems of the face affect both function and aesthetics, which are based on complex anatomical features. Treating dermatologic problems while preserving the aesthetics and functions of the face requires knowledge of normal anatomy. When performing successfully invasive procedures of the face, it is essential to understand its underlying topographic anatomy. This chapter presents the anatomy of the facial musculature and neurovascular structures in a systematic way with some clinically important aspects. We describe the attachments of the mimetic and masticatory muscles and emphasize their functions and nerve supply. We highlight clinically relevant facial topographic anatomy by explaining the course and location of the sensory and motor nerves of the face and facial vasculature with their relations. Additionally, this chapter reviews the recent nomenclature of the branching pattern of the facial artery. © 2013 Elsevier Inc. All rights reserved.

  11. Mirror on the wall: a study of women's perception of facial features as they age.

    Science.gov (United States)

    Sezgin, Billur; Findikcioglu, Kemal; Kaya, Basar; Sibar, Serhat; Yavuzer, Reha

    2012-05-01

    Facial aesthetic treatments are among the most popular cosmetic procedures worldwide, but the factors that motivate women to change their facial appearance are not fully understood. The authors examine the relationships among the facial areas on which women focus most as they age, women's general self-perception, and the effect of their personal focus on "beauty points" on their perception of other women's faces. In this prospective study, 200 women who presented to a cosmetic surgery outpatient clinic for consultation between December 2009 and February 2010 completed a questionnaire. The 200 participants were grouped by age: 20-29 years, 30-39, 40-49, and 50 or older (50 women in each group). They were asked which part of their face they focus on most when looking in the mirror, which part they notice most in other women (of different age groups), what they like/dislike most about their own face, and whether they wished to change any facial feature. A positive correlation was found between women's focal points and the areas they dislike or desire to change. Younger women focused mainly on their nose and skin, while older women focused on their periorbital area and jawline. Women focus on their personal focal points when looking at other women in their 20s and 30s, but not when looking at older women. Women presenting for cosmetic surgery consultation focus on the areas that they dislike most, which leads to a desire to change those features. The plastic surgeon must fully understand patients' expectations to select appropriate candidates and maximize satisfaction with the outcomes.

  12. СREATING OF BARCODES FOR FACIAL IMAGES BASED ON INTENSITY GRADIENTS

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    G. A. Kukharev

    2014-05-01

    Full Text Available The paper provides analysis of existing approaches to the generating of barcodes and description of the system structure for generating of barcodes from facial images. The method for generating of standard type linear barcodes from facial images is proposed. This method is based on the difference of intensity gradients, which represent images in the form of initial features. Further averaging of these features into a limited number of intervals is performed; the quantization of results into decimal digits from 0 to 9 and table conversion into the standard barcode is done. Testing was conducted on the Face94 database and database of composite faces of different ages. It showed that the proposed method ensures the stability of generated barcodes according to changes of scale, pose and mirroring of facial images, as well as changes of facial expressions and shadows on faces from local lighting. The proposed solutions are computationally low-cost and do not require the use of any specialized image processing software for generating of facial barcodes in real-time systems.

  13. Facial contour deformity correction with microvascular flaps based on the 3-dimentional template and facial moulage

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    Dinesh Kadam

    2013-01-01

    Full Text Available Introduction: Facial contour deformities presents with varied aetiology and degrees severity. Accurate assessment, selecting a suitable tissue and sculpturing it to fill the defect is challenging and largely subjective. Objective assessment with imaging and software is not always feasible and preparing a template is complicated. A three-dimensional (3D wax template pre-fabricated over the facial moulage aids surgeons to fulfil these tasks. Severe deformities demand a stable vascular tissue for an acceptable outcome. Materials and Methods: We present review of eight consecutive patients who underwent augmentation of facial contour defects with free flaps between June 2005 and January 2011. De-epithelialised free anterolateral thigh (ALT flap in three, radial artery forearm flap and fibula osteocutaneous flap in two each and groin flap was used in one patient. A 3D wax template was fabricated by augmenting the deformity on facial moulage. It was utilised to select the flap, to determine the exact dimensions and to sculpture intraoperatively. Ancillary procedures such as genioplasty, rhinoplasty and coloboma correction were performed. Results: The average age at the presentation was 25 years and average disease free interval was 5.5 years and all flaps survived. Mean follow-up period was 21.75 months. The correction was aesthetically acceptable and was maintained without any recurrence or atrophy. Conclusion: The 3D wax template on facial moulage is simple, inexpensive and precise objective tool. It provides accurate guide for the planning and execution of the flap reconstruction. The selection of the flap is based on the type and extent of the defect. Superiority of vascularised free tissue is well-known and the ALT flap offers a versatile option for correcting varying degrees of the deformities. Ancillary procedures improve the overall aesthetic outcomes and minor flap touch-up procedures are generally required.

  14. An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

    Science.gov (United States)

    Shen, Xiaolei; Zhang, Jiachi; Yan, Chenjun; Zhou, Hong

    2018-04-11

    In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vulgaris. The core of our method is to extract features of images based on CNNs and achieve classification by classifier. A binary-classifier of skin-and-non-skin is used to detect skin area and a seven-classifier is used to achieve the classification task of facial acne vulgaris and healthy skin. In the experiments, we compare the effectiveness of our CNN and the VGG16 neural network which is pre-trained on the ImageNet data set. We use a ROC curve to evaluate the performance of binary-classifier and use a normalized confusion matrix to evaluate the performance of seven-classifier. The results of our experiments show that the pre-trained VGG16 neural network is effective in extracting features from facial acne vulgaris images. And the features are very useful for the follow-up classifiers. Finally, we try applying the classifiers both based on the pre-trained VGG16 neural network to assist doctors in facial acne vulgaris diagnosis.

  15. Dysmorphic Facial Features and Other Clinical Characteristics in Two Patients with PEX1 Gene Mutations

    Science.gov (United States)

    Gunduz, Mehmet

    2016-01-01

    Peroxisomal disorders are a group of genetically heterogeneous metabolic diseases related to dysfunction of peroxisomes. Dysmorphic features, neurological abnormalities, and hepatic dysfunction can be presenting signs of peroxisomal disorders. Here we presented dysmorphic facial features and other clinical characteristics in two patients with PEX1 gene mutation. Follow-up periods were 3.5 years and 1 year in the patients. Case I was one-year-old girl that presented with neurodevelopmental delay, hepatomegaly, bilateral hearing loss, and visual problems. Ophthalmologic examination suggested septooptic dysplasia. Cranial magnetic resonance imaging (MRI) showed nonspecific gliosis at subcortical and periventricular deep white matter. Case II was 2.5-year-old girl referred for investigation of global developmental delay and elevated liver enzymes. Ophthalmologic examination findings were consistent with bilateral nystagmus and retinitis pigmentosa. Cranial MRI was normal. Dysmorphic facial features including broad nasal root, low set ears, downward slanting eyes, downward slanting eyebrows, and epichantal folds were common findings in two patients. Molecular genetic analysis indicated homozygous novel IVS1-2A>G mutation in Case I and homozygous p.G843D (c.2528G>A) mutation in Case II in the PEX1 gene. Clinical findings and developmental prognosis vary in PEX1 gene mutation. Kabuki-like phenotype associated with liver pathology may indicate Zellweger spectrum disorders (ZSD). PMID:27882258

  16. A Diagnosis to Consider in an Adult Patient with Facial Features and Intellectual Disability: Williams Syndrome.

    Science.gov (United States)

    Doğan, Özlem Akgün; Şimşek Kiper, Pelin Özlem; Utine, Gülen Eda; Alikaşifoğlu, Mehmet; Boduroğlu, Koray

    2017-03-01

    Williams syndrome (OMIM #194050) is a rare, well-recognized, multisystemic genetic condition affecting approximately 1/7,500 individuals. There are no marked regional differences in the incidence of Williams syndrome. The syndrome is caused by a hemizygous deletion of approximately 28 genes, including ELN on chromosome 7q11.2. Prenatal-onset growth retardation, distinct facial appearance, cardiovascular abnormalities, and unique hypersocial behavior are among the most common clinical features. Here, we report the case of a patient referred to us with distinct facial features and intellectual disability, who was diagnosed with Williams syndrome at the age of 37 years. Our aim is to increase awareness regarding the diagnostic features and complications of this recognizable syndrome among adult health care providers. Williams syndrome is usually diagnosed during infancy or childhood, but in the absence of classical findings, such as cardiovascular anomalies, hypercalcemia, and cognitive impairment, the diagnosis could be delayed. Due to the multisystemic and progressive nature of the syndrome, accurate diagnosis is critical for appropriate care and screening for the associated morbidities that may affect the patient's health and well-being.

  17. A novel human-machine interface based on recognition of multi-channel facial bioelectric signals

    International Nuclear Information System (INIS)

    Razazadeh, Iman Mohammad; Firoozabadi, S. Mohammad; Golpayegani, S.M.R.H.; Hu, H.

    2011-01-01

    Full text: This paper presents a novel human-machine interface for disabled people to interact with assistive systems for a better quality of life. It is based on multichannel forehead bioelectric signals acquired by placing three pairs of electrodes (physical channels) on the Fron-tails and Temporalis facial muscles. The acquired signals are passes through a parallel filter bank to explore three different sub-bands related to facial electromyogram, electrooculogram and electroencephalogram. The root mean features of the bioelectric signals analyzed within non-overlapping 256 ms windows were extracted. The subtractive fuzzy c-means clustering method (SFCM) was applied to segment the feature space and generate initial fuzzy based Takagi-Sugeno rules. Then, an adaptive neuro-fuzzy inference system is exploited to tune up the premises and consequence parameters of the extracted SFCMs. rules. The average classifier discriminating ratio for eight different facial gestures (smiling, frowning, pulling up left/right lips corner, eye movement to left/right/up/down is between 93.04% and 96.99% according to different combinations and fusions of logical features. Experimental results show that the proposed interface has a high degree of accuracy and robustness for discrimination of 8 fundamental facial gestures. Some potential and further capabilities of our approach in human-machine interfaces are also discussed. (author)

  18. An adaptation study of internal and external features in facial representations.

    Science.gov (United States)

    Hills, Charlotte; Romano, Kali; Davies-Thompson, Jodie; Barton, Jason J S

    2014-07-01

    Prior work suggests that internal features contribute more than external features to face processing. Whether this asymmetry is also true of the mental representations of faces is not known. We used face adaptation to determine whether the internal and external features of faces contribute differently to the representation of facial identity, whether this was affected by familiarity, and whether the results differed if the features were presented in isolation or as part of a whole face. In a first experiment, subjects performed a study of identity adaptation for famous and novel faces, in which the adapting stimuli were whole faces, the internal features alone, or the external features alone. In a second experiment, the same faces were used, but the adapting internal and external features were superimposed on whole faces that were ambiguous to identity. The first experiment showed larger aftereffects for unfamiliar faces, and greater aftereffects from internal than from external features, and the latter was true for both familiar and unfamiliar faces. When internal and external features were presented in a whole-face context in the second experiment, aftereffects from either internal or external features was less than that from the whole face, and did not differ from each other. While we reproduce the greater importance of internal features when presented in isolation, we find this is equally true for familiar and unfamiliar faces. The dominant influence of internal features is reduced when integrated into a whole-face context, suggesting another facet of expert face processing. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Contributions of feature shapes and surface cues to the recognition and neural representation of facial identity.

    Science.gov (United States)

    Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W

    2016-10-01

    A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Scattered Data Processing Approach Based on Optical Facial Motion Capture

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    Qiang Zhang

    2013-01-01

    Full Text Available In recent years, animation reconstruction of facial expressions has become a popular research field in computer science and motion capture-based facial expression reconstruction is now emerging in this field. Based on the facial motion data obtained using a passive optical motion capture system, we propose a scattered data processing approach, which aims to solve the common problems of missing data and noise. To recover missing data, given the nonlinear relationships among neighbors with the current missing marker, we propose an improved version of a previous method, where we use the motion of three muscles rather than one to recover the missing data. To reduce the noise, we initially apply preprocessing to eliminate impulsive noise, before our proposed three-order quasi-uniform B-spline-based fitting method is used to reduce the remaining noise. Our experiments showed that the principles that underlie this method are simple and straightforward, and it delivered acceptable precision during reconstruction.

  1. Is the emotion recognition deficit associated with frontotemporal dementia caused by selective inattention to diagnostic facial features?

    Science.gov (United States)

    Oliver, Lindsay D; Virani, Karim; Finger, Elizabeth C; Mitchell, Derek G V

    2014-07-01

    Frontotemporal dementia (FTD) is a debilitating neurodegenerative disorder characterized by severely impaired social and emotional behaviour, including emotion recognition deficits. Though fear recognition impairments seen in particular neurological and developmental disorders can be ameliorated by reallocating attention to critical facial features, the possibility that similar benefits can be conferred to patients with FTD has yet to be explored. In the current study, we examined the impact of presenting distinct regions of the face (whole face, eyes-only, and eyes-removed) on the ability to recognize expressions of anger, fear, disgust, and happiness in 24 patients with FTD and 24 healthy controls. A recognition deficit was demonstrated across emotions by patients with FTD relative to controls. Crucially, removal of diagnostic facial features resulted in an appropriate decline in performance for both groups; furthermore, patients with FTD demonstrated a lack of disproportionate improvement in emotion recognition accuracy as a result of isolating critical facial features relative to controls. Thus, unlike some neurological and developmental disorders featuring amygdala dysfunction, the emotion recognition deficit observed in FTD is not likely driven by selective inattention to critical facial features. Patients with FTD also mislabelled negative facial expressions as happy more often than controls, providing further evidence for abnormalities in the representation of positive affect in FTD. This work suggests that the emotional expression recognition deficit associated with FTD is unlikely to be rectified by adjusting selective attention to diagnostic features, as has proven useful in other select disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Fixation to features and neural processing of facial expressions in a gender discrimination task.

    Science.gov (United States)

    Neath, Karly N; Itier, Roxane J

    2015-10-01

    Early face encoding, as reflected by the N170 ERP component, is sensitive to fixation to the eyes. Whether this sensitivity varies with facial expressions of emotion and can also be seen on other ERP components such as P1 and EPN, was investigated. Using eye-tracking to manipulate fixation on facial features, we found the N170 to be the only eye-sensitive component and this was true for fearful, happy and neutral faces. A different effect of fixation to features was seen for the earlier P1 that likely reflected general sensitivity to face position. An early effect of emotion (∼120 ms) for happy faces was seen at occipital sites and was sustained until ∼350 ms post-stimulus. For fearful faces, an early effect was seen around 80 ms followed by a later effect appearing at ∼150 ms until ∼300 ms at lateral posterior sites. Results suggests that in this emotion-irrelevant gender discrimination task, processing of fearful and happy expressions occurred early and largely independently of the eye-sensitivity indexed by the N170. Processing of the two emotions involved different underlying brain networks active at different times. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. 3D Facial Similarity Measure Based on Geodesic Network and Curvatures

    Directory of Open Access Journals (Sweden)

    Junli Zhao

    2014-01-01

    Full Text Available Automated 3D facial similarity measure is a challenging and valuable research topic in anthropology and computer graphics. It is widely used in various fields, such as criminal investigation, kinship confirmation, and face recognition. This paper proposes a 3D facial similarity measure method based on a combination of geodesic and curvature features. Firstly, a geodesic network is generated for each face with geodesics and iso-geodesics determined and these network points are adopted as the correspondence across face models. Then, four metrics associated with curvatures, that is, the mean curvature, Gaussian curvature, shape index, and curvedness, are computed for each network point by using a weighted average of its neighborhood points. Finally, correlation coefficients according to these metrics are computed, respectively, as the similarity measures between two 3D face models. Experiments of different persons’ 3D facial models and different 3D facial models of the same person are implemented and compared with a subjective face similarity study. The results show that the geodesic network plays an important role in 3D facial similarity measure. The similarity measure defined by shape index is consistent with human’s subjective evaluation basically, and it can measure the 3D face similarity more objectively than the other indices.

  4. Analysis of differences between Western and East-Asian faces based on facial region segmentation and PCA for facial expression recognition

    Science.gov (United States)

    Benitez-Garcia, Gibran; Nakamura, Tomoaki; Kaneko, Masahide

    2017-01-01

    Darwin was the first one to assert that facial expressions are innate and universal, which are recognized across all cultures. However, recent some cross-cultural studies have questioned this assumed universality. Therefore, this paper presents an analysis of the differences between Western and East-Asian faces of the six basic expressions (anger, disgust, fear, happiness, sadness and surprise) focused on three individual facial regions of eyes-eyebrows, nose and mouth. The analysis is conducted by applying PCA for two feature extraction methods: appearance-based by using the pixel intensities of facial parts, and geometric-based by handling 125 feature points from the face. Both methods are evaluated using 4 standard databases for both racial groups and the results are compared with a cross-cultural human study applied to 20 participants. Our analysis reveals that differences between Westerns and East-Asians exist mainly on the regions of eyes-eyebrows and mouth for expressions of fear and disgust respectively. This work presents important findings for a better design of automatic facial expression recognition systems based on the difference between two racial groups.

  5. Replicating distinctive facial features in lineups: identification performance in young versus older adults.

    Science.gov (United States)

    Badham, Stephen P; Wade, Kimberley A; Watts, Hannah J E; Woods, Natalie G; Maylor, Elizabeth A

    2013-04-01

    Criminal suspects with distinctive facial features, such as tattoos or bruising, may stand out in a police lineup. To prevent suspects from being unfairly identified on the basis of their distinctive feature, the police often manipulate lineup images to ensure that all of the members appear similar. Recent research shows that replicating a distinctive feature across lineup members enhances eyewitness identification performance, relative to removing that feature on the target. In line with this finding, the present study demonstrated that with young adults (n = 60; mean age = 20), replication resulted in more target identifications than did removal in target-present lineups and that replication did not impair performance, relative to removal, in target-absent lineups. Older adults (n = 90; mean age = 74) performed significantly worse than young adults, identifying fewer targets and more foils; moreover, older adults showed a minimal benefit from replication over removal. This pattern is consistent with the associative deficit hypothesis of aging, such that older adults form weaker links between faces and their distinctive features. Although replication did not produce much benefit over removal for older adults, it was not detrimental to their performance. Therefore, the results suggest that replication may not be as beneficial to older adults as it is to young adults and demonstrate a new practical implication of age-related associative deficits in memory.

  6. Automated detection of pain from facial expressions: a rule-based approach using AAM

    Science.gov (United States)

    Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

    2012-02-01

    In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

  7. Radiofrequency facial rejuvenation: evidence-based effect.

    Science.gov (United States)

    el-Domyati, Moetaz; el-Ammawi, Tarek S; Medhat, Walid; Moawad, Osama; Brennan, Donna; Mahoney, My G; Uitto, Jouni

    2011-03-01

    Multiple therapies involving ablative and nonablative techniques have been developed for rejuvenation of photodamaged skin. Monopolar radiofrequency (RF) is emerging as a gentler, nonablative skin-tightening device that delivers uniform heat to the dermis at a controlled depth. We evaluated the clinical effects and objectively quantified the histologic changes of the nonablative RF device in the treatment of photoaging. Six individuals of Fitzpatrick skin type III to IV and Glogau class I to II wrinkles were subjected to 3 months of treatment (6 sessions at 2-week intervals). Standard photographs and skin biopsy specimens were obtained at baseline, and at 3 and 6 months after the start of treatment. We performed quantitative evaluation of total elastin, collagen types I and III, and newly synthesized collagen using computerized histometric and immunohistochemical techniques. Blinded photographs were independently scored for wrinkle improvement. RF produced noticeable clinical results, with high satisfaction and corresponding facial skin improvement. Compared with the baseline, there was a statistically significant increase in the mean of collagen types I and III, and newly synthesized collagen, while the mean of total elastin was significantly decreased, at the end of treatment and 3 months posttreatment. A limitation of this study is the small number of patients, yet the results show a significant improvement. Although the results may not be as impressive as those obtained by ablative treatments, RF is a promising treatment option for photoaging with fewer side effects and downtime. Copyright © 2010 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

  8. Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach

    NARCIS (Netherlands)

    Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

    2016-01-01

    Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in

  9. A newly recognized syndrome of severe growth deficiency, microcephaly, intellectual disability, and characteristic facial features.

    Science.gov (United States)

    Vinkler, Chana; Leshinsky-Silver, Esther; Michelson, Marina; Haas, Dorothea; Lerman-Sagie, Tally; Lev, Dorit

    2014-01-01

    Genetic syndromes with proportionate severe short stature are rare. We describe two sisters born to nonconsanguineous parents with severe linear growth retardation, poor weight gain, microcephaly, characteristic facial features, cutaneous syndactyly of the toes, high myopia, and severe intellectual disability. During infancy and early childhood, the girls had transient hepatosplenomegaly and low blood cholesterol levels that normalized later. A thorough evaluation including metabolic studies, radiological, and genetic investigations were all normal. Cholesterol metabolism and transport were studied and no definitive abnormality was found. No clinical deterioration was observed and no metabolic crises were reported. After due consideration of other known hereditary causes of post-natal severe linear growth retardation, microcephaly, and intellectual disability, we propose that this condition represents a newly recognized autosomal recessive multiple congenital anomaly-intellectual disability syndrome. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  10. Facial expression recognition based on weber local descriptor and sparse representation

    Science.gov (United States)

    Ouyang, Yan

    2018-03-01

    Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

  11. Facial Nerve Schwannoma: A Case Report, Radiological Features and Literature Review.

    Science.gov (United States)

    Pilloni, Giulia; Mico, Barbara Massa; Altieri, Roberto; Zenga, Francesco; Ducati, Alessandro; Garbossa, Diego; Tartara, Fulvio

    2017-12-22

    Facial nerve schwannoma localized in the middle fossa is a rare lesion. We report a case of a facial nerve schwannoma in a 30-year-old male presenting with facial nerve palsy. Magnetic resonance imaging (MRI) showed a 3 cm diameter tumor of the right middle fossa. The tumor was removed using a sub-temporal approach. Intraoperative monitoring allowed for identification of the facial nerve, so it was not damaged during the surgical excision. Neurological clinical examination at discharge demonstrated moderate facial nerve improvement (Grade III House-Brackmann).

  12. Sensorineural deafness, distinctive facial features, and abnormal cranial bones: a new variant of Waardenburg syndrome?

    Science.gov (United States)

    Gad, Alona; Laurino, Mercy; Maravilla, Kenneth R; Matsushita, Mark; Raskind, Wendy H

    2008-07-15

    The Waardenburg syndromes (WS) account for approximately 2% of congenital sensorineural deafness. This heterogeneous group of diseases currently can be categorized into four major subtypes (WS types 1-4) on the basis of characteristic clinical features. Multiple genes have been implicated in WS, and mutations in some genes can cause more than one WS subtype. In addition to eye, hair, and skin pigmentary abnormalities, dystopia canthorum and broad nasal bridge are seen in WS type 1. Mutations in the PAX3 gene are responsible for the condition in the majority of these patients. In addition, mutations in PAX3 have been found in WS type 3 that is distinguished by musculoskeletal abnormalities, and in a family with a rare subtype of WS, craniofacial-deafness-hand syndrome (CDHS), characterized by dysmorphic facial features, hand abnormalities, and absent or hypoplastic nasal and wrist bones. Here we describe a woman who shares some, but not all features of WS type 3 and CDHS, and who also has abnormal cranial bones. All sinuses were hypoplastic, and the cochlea were small. No sequence alteration in PAX3 was found. These observations broaden the clinical range of WS and suggest there may be genetic heterogeneity even within the CDHS subtype. 2008 Wiley-Liss, Inc.

  13. Extreme Facial Expressions Classification Based on Reality Parameters

    Science.gov (United States)

    Rahim, Mohd Shafry Mohd; Rad, Abdolvahab Ehsani; Rehman, Amjad; Altameem, Ayman

    2014-09-01

    Extreme expressions are really type of emotional expressions that are basically stimulated through the strong emotion. An example of those extreme expression is satisfied through tears. So to be able to provide these types of features; additional elements like fluid mechanism (particle system) plus some of physics techniques like (SPH) are introduced. The fusion of facile animation with SPH exhibits promising results. Accordingly, proposed fluid technique using facial animation is the real tenor for this research to get the complex expression, like laugh, smile, cry (tears emergence) or the sadness until cry strongly, as an extreme expression classification that's happens on the human face in some cases.

  14. Image Based Hair Segmentation Algorithm for the Application of Automatic Facial Caricature Synthesis

    Directory of Open Access Journals (Sweden)

    Yehu Shen

    2014-01-01

    Full Text Available Hair is a salient feature in human face region and are one of the important cues for face analysis. Accurate detection and presentation of hair region is one of the key components for automatic synthesis of human facial caricature. In this paper, an automatic hair detection algorithm for the application of automatic synthesis of facial caricature based on a single image is proposed. Firstly, hair regions in training images are labeled manually and then the hair position prior distributions and hair color likelihood distribution function are estimated from these labels efficiently. Secondly, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood. This energy function is further optimized according to graph cuts technique and initial hair region is obtained. Finally, K-means algorithm and image postprocessing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. Experimental results show that the average processing time for each image is about 280 ms and the average hair region detection accuracy is above 90%. The proposed algorithm is applied to a facial caricature synthesis system. Experiments proved that with our proposed hair segmentation algorithm the facial caricatures are vivid and satisfying.

  15. Tolerance-Based Feature Transforms

    NARCIS (Netherlands)

    Reniers, Dennie; Telea, Alexandru

    2007-01-01

    Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary

  16. MRI-based diagnostic imaging of the intratemporal facial nerve

    International Nuclear Information System (INIS)

    Kress, B.; Baehren, W.

    2001-01-01

    Detailed imaging of the five sections of the full intratemporal course of the facial nerve can be achieved by MRI and using thin tomographic section techniques and surface coils. Contrast media are required for tomographic imaging of pathological processes. Established methods are available for diagnostic evaluation of cerebellopontine angle tumors and chronic Bell's palsy, as well as hemifacial spasms. A method still under discussion is MRI for diagnostic evaluation of Bell's palsy in the presence of fractures of the petrous bone, when blood volumes in the petrous bone make evaluation even more difficult. MRI-based diagnostic evaluation of the idiopatic facial paralysis currently is subject to change. Its usual application cannot be recommended for routine evaluation at present. However, a quantitative analysis of contrast medium uptake of the nerve may be an approach to improve the prognostic value of MRI in acute phases of Bell's palsy. (orig./CB) [de

  17. Neural bases of different cognitive strategies for facial affect processing in schizophrenia.

    Science.gov (United States)

    Fakra, Eric; Salgado-Pineda, Pilar; Delaveau, Pauline; Hariri, Ahmad R; Blin, Olivier

    2008-03-01

    To examine the neural basis and dynamics of facial affect processing in schizophrenic patients as compared to healthy controls. Fourteen schizophrenic patients and fourteen matched controls performed a facial affect identification task during fMRI acquisition. The emotional task included an intuitive emotional condition (matching emotional faces) and a more cognitively demanding condition (labeling emotional faces). Individual analysis for each emotional condition, and second-level t-tests examining both within-, and between-group differences, were carried out using a random effects approach. Psychophysiological interactions (PPI) were tested for variations in functional connectivity between amygdala and other brain regions as a function of changes in experimental conditions (labeling versus matching). During the labeling condition, both groups engaged similar networks. During the matching condition, schizophrenics failed to activate regions of the limbic system implicated in the automatic processing of emotions. PPI revealed an inverse functional connectivity between prefrontal regions and the left amygdala in healthy volunteers but there was no such change in patients. Furthermore, during the matching condition, and compared to controls, patients showed decreased activation of regions involved in holistic face processing (fusiform gyrus) and increased activation of regions associated with feature analysis (inferior parietal cortex, left middle temporal lobe, right precuneus). Our findings suggest that schizophrenic patients invariably adopt a cognitive approach when identifying facial affect. The distributed neocortical network observed during the intuitive condition indicates that patients may resort to feature-based, rather than configuration-based, processing and may constitute a compensatory strategy for limbic dysfunction.

  18. Likelihood Ratio Based Mixed Resolution Facial Comparison

    NARCIS (Netherlands)

    Peng, Y.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2015-01-01

    In this paper, we propose a novel method for low-resolution face recognition. It is especially useful for a common situation in forensic search where faces of low resolution, e.g. on surveillance footage or in a crowd, must be compared to a high-resolution reference. This method is based on the

  19. Facial motion parameter estimation and error criteria in model-based image coding

    Science.gov (United States)

    Liu, Yunhai; Yu, Lu; Yao, Qingdong

    2000-04-01

    Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.

  20. Energy-Based Facial Rejuvenation: Advances in Diagnosis and Treatment.

    Science.gov (United States)

    Britt, Christopher J; Marcus, Benjamin

    2017-01-01

    The market for nonsurgical, energy-based facial rejuvenation techniques has increased exponentially since lasers were first used for skin rejuvenation in 1983. Advances in this area have led to a wide range of products that require the modern facial plastic surgeon to have a large repertoire of knowledge. To serve as a guide for current trends in the development of technology, applications, and outcomes of laser and laser-related technology over the past 5 years. We performed a review of PubMed from January 1, 2011, to March 1, 2016, and focused on randomized clinical trials, meta-analyses, systematic reviews, and clinical practice guidelines including case control, case studies and case reports when necessary, and included 14 articles we deemed landmark articles before 2011. Three broad categories of technology are leading non-energy-based rejuvenation technology: lasers, light therapy, and non-laser-based thermal tightening devices. Laser light therapy has continued to diversify with the use of ablative and nonablative resurfacing technologies, fractionated lasers, and their combined use. Light therapy has developed for use in combination with other technologies or stand alone. Finally, thermally based nonlaser skin-tightening devices, such as radiofrequency (RF) and intense focused ultrasonography (IFUS), are evolving technologies that have changed rapidly over the past 5 years. Improvements in safety and efficacy for energy-based treatment have expanded the patient base considering these therapies viable options. With a wide variety of options, the modern facial plastic surgeon can have a frank discussion with the patient regarding nonsurgical techniques that were never before available. Many of these patients can now derive benefit from treatments requiring significantly less downtime than before while the clinician can augment the treatment to maximize benefit to fit the patient's time schedule.

  1. Steel syndrome: dislocated hips and radial heads, carpal coalition, scoliosis, short stature, and characteristic facial features.

    Science.gov (United States)

    Flynn, John M; Ramirez, Norman; Betz, Randal; Mulcahey, Mary Jane; Pino, Franz; Herrera-Soto, Jose A; Carlo, Simon; Cornier, Alberto S

    2010-01-01

    A syndrome of children with short stature, bilateral hip dislocations, radial head dislocations, carpal coalitions, scoliosis, and cavus feet in Puerto Rican children, was reported by Steel et al in 1993. The syndrome was described as a unique entity with dismal results after conventional treatment of dislocated hips. The purpose of this study is to reevaluate this patient population with a longer follow-up and delineate the clinical and radiologic features, treatment outcomes, and the genetic characteristics. This is a retrospective cohort study of 32 patients in whom we evaluated the clinical, imaging data, and genetic characteristics. We compare the findings and quality of life in patients with this syndrome who have had attempts at reduction of the hips versus those who did not have the treatment. Congenital hip dislocations were present in 100% of the patients. There was no attempt at reduction in 39% (25/64) of the hips. In the remaining 61% (39/64), the hips were treated with a variety of modalities fraught with complications. Of those treated, 85% (33/39) remain dislocated, the rest of the hips continue subluxated with acetabular dysplasia and pain. The group of hips that were not treated reported fewer complaints and limitation in daily activities compared with the hips that had attempts at reduction. Steel syndrome is a distinct clinical entity characterized by short stature, bilateral hip and radial head dislocation, carpal coalition, scoliosis, cavus feet, and characteristic facial features with dismal results for attempts at reduction of the hips. Prognostic Study Level II.

  2. Analysis of facial expressions in parkinson's disease through video-based automatic methods.

    Science.gov (United States)

    Bandini, Andrea; Orlandi, Silvia; Escalante, Hugo Jair; Giovannelli, Fabio; Cincotta, Massimo; Reyes-Garcia, Carlos A; Vanni, Paola; Zaccara, Gaetano; Manfredi, Claudia

    2017-04-01

    The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia. In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based METHODS: 17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions. Results show that control subjects reported on average higher distances than PD patients along the tasks. This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients. Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. [Facial palsy].

    Science.gov (United States)

    Cavoy, R

    2013-09-01

    Facial palsy is a daily challenge for the clinicians. Determining whether facial nerve palsy is peripheral or central is a key step in the diagnosis. Central nervous lesions can give facial palsy which may be easily differentiated from peripheral palsy. The next question is the peripheral facial paralysis idiopathic or symptomatic. A good knowledge of anatomy of facial nerve is helpful. A structure approach is given to identify additional features that distinguish symptomatic facial palsy from idiopathic one. The main cause of peripheral facial palsies is idiopathic one, or Bell's palsy, which remains a diagnosis of exclusion. The most common cause of symptomatic peripheral facial palsy is Ramsay-Hunt syndrome. Early identification of symptomatic facial palsy is important because of often worst outcome and different management. The prognosis of Bell's palsy is on the whole favorable and is improved with a prompt tapering course of prednisone. In Ramsay-Hunt syndrome, an antiviral therapy is added along with prednisone. We also discussed of current treatment recommendations. We will review short and long term complications of peripheral facial palsy.

  4. Appearance-based human gesture recognition using multimodal features for human computer interaction

    Science.gov (United States)

    Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

    2011-03-01

    The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

  5. Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

    Science.gov (United States)

    Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

    2016-06-01

    Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

  6. A novel method for human age group classification based on Correlation Fractal Dimension of facial edges

    OpenAIRE

    Yarlagadda, Anuradha; Murthy, J.V.R.; Krishna Prasad, M.H.M.

    2015-01-01

    In the computer vision community, easy categorization of a person’s facial image into various age groups is often quite precise and is not pursued effectively. To address this problem, which is an important area of research, the present paper proposes an innovative method of age group classification system based on the Correlation Fractal Dimension of complex facial image. Wrinkles appear on the face with aging thereby changing the facial edges of the image. The proposed method is rotation an...

  7. Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

    DEFF Research Database (Denmark)

    Duan, Xiaodong; Tan, Zheng-Hua

    2015-01-01

    In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

  8. Cosmetics as a Feature of the Extended Human Phenotype: Modulation of the Perception of Biologically Important Facial Signals

    Science.gov (United States)

    Etcoff, Nancy L.; Stock, Shannon; Haley, Lauren E.; Vickery, Sarah A.; House, David M.

    2011-01-01

    Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

  9. Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

    Directory of Open Access Journals (Sweden)

    Nancy L Etcoff

    Full Text Available Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural, to moderate (professional, to dramatic (glamorous. Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important

  10. Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

    Science.gov (United States)

    Etcoff, Nancy L; Stock, Shannon; Haley, Lauren E; Vickery, Sarah A; House, David M

    2011-01-01

    Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

  11. A Brief Review of Facial Emotion Recognition Based on Visual Information

    Science.gov (United States)

    2018-01-01

    Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling “end-to-end” learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work. PMID:29385749

  12. A Brief Review of Facial Emotion Recognition Based on Visual Information.

    Science.gov (United States)

    Ko, Byoung Chul

    2018-01-30

    Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling "end-to-end" learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN) for the spatial features of an individual frame and long short-term memory (LSTM) for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work.

  13. A Brief Review of Facial Emotion Recognition Based on Visual Information

    Directory of Open Access Journals (Sweden)

    Byoung Chul Ko

    2018-01-01

    Full Text Available Facial emotion recognition (FER is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Although FER can be conducted using multiple sensors, this review focuses on studies that exclusively use facial images, because visual expressions are one of the main information channels in interpersonal communication. This paper provides a brief review of researches in the field of FER conducted over the past decades. First, conventional FER approaches are described along with a summary of the representative categories of FER systems and their main algorithms. Deep-learning-based FER approaches using deep networks enabling “end-to-end” learning are then presented. This review also focuses on an up-to-date hybrid deep-learning approach combining a convolutional neural network (CNN for the spatial features of an individual frame and long short-term memory (LSTM for temporal features of consecutive frames. In the later part of this paper, a brief review of publicly available evaluation metrics is given, and a comparison with benchmark results, which are a standard for a quantitative comparison of FER researches, is described. This review can serve as a brief guidebook to newcomers in the field of FER, providing basic knowledge and a general understanding of the latest state-of-the-art studies, as well as to experienced researchers looking for productive directions for future work.

  14. A dynamic texture based approach to recognition of facial actions and their temporal models

    NARCIS (Netherlands)

    Koelstra, Sander; Pantic, Maja; Patras, Ioannis (Yannis)

    2010-01-01

    In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the

  15. GENDER RECOGNITION BASED ON SIFT FEATURES

    OpenAIRE

    Sahar Yousefi; Morteza Zahedi

    2011-01-01

    This paper proposes a robust approach for face detection and gender classification in color images. Previous researches about gender recognition suppose an expensive computational and time-consuming pre-processing step in order to alignment in which face images are aligned so that facial landmarks like eyes, nose, lips, chin are placed in uniform locations in image. In this paper, a novel technique based on mathematical analysis is represented in three stages that eliminates align...

  16. Chondromyxoid fibroma of the mastoid facial nerve canal mimicking a facial nerve schwannoma.

    Science.gov (United States)

    Thompson, Andrew L; Bharatha, Aditya; Aviv, Richard I; Nedzelski, Julian; Chen, Joseph; Bilbao, Juan M; Wong, John; Saad, Reda; Symons, Sean P

    2009-07-01

    Chondromyxoid fibroma of the skull base is a rare entity. Involvement of the temporal bone is particularly rare. We present an unusual case of progressive facial nerve paralysis with imaging and clinical findings most suggestive of a facial nerve schwannoma. The lesion was tubular in appearance, expanded the mastoid facial nerve canal, protruded out of the stylomastoid foramen, and enhanced homogeneously. The only unusual imaging feature was minor calcification within the tumor. Surgery revealed an irregular, cystic lesion. Pathology diagnosed a chondromyxoid fibroma involving the mastoid portion of the facial nerve canal, destroying the facial nerve.

  17. An Improved Surface Simplification Method for Facial Expression Animation Based on Homogeneous Coordinate Transformation Matrix and Maximum Shape Operator

    Directory of Open Access Journals (Sweden)

    Juin-Ling Tseng

    2016-01-01

    Full Text Available Facial animation is one of the most popular 3D animation topics researched in recent years. However, when using facial animation, a 3D facial animation model has to be stored. This 3D facial animation model requires many triangles to accurately describe and demonstrate facial expression animation because the face often presents a number of different expressions. Consequently, the costs associated with facial animation have increased rapidly. In an effort to reduce storage costs, researchers have sought to simplify 3D animation models using techniques such as Deformation Sensitive Decimation and Feature Edge Quadric. The studies conducted have examined the problems in the homogeneity of the local coordinate system between different expression models and in the retainment of simplified model characteristics. This paper proposes a method that applies Homogeneous Coordinate Transformation Matrix to solve the problem of homogeneity of the local coordinate system and Maximum Shape Operator to detect shape changes in facial animation so as to properly preserve the features of facial expressions. Further, root mean square error and perceived quality error are used to compare the errors generated by different simplification methods in experiments. Experimental results show that, compared with Deformation Sensitive Decimation and Feature Edge Quadric, our method can not only reduce the errors caused by simplification of facial animation, but also retain more facial features.

  18. Facial Nerve Palsy: An Unusual Presenting Feature of Small Cell Lung Cancer

    Directory of Open Access Journals (Sweden)

    Ozcan Yildiz

    2011-01-01

    Full Text Available Lung cancer is the second most common type of cancer in the world and is the most common cause of cancer-related death in men and women; it is responsible for 1.3 million deaths annually worldwide. It can metastasize to any organ. The most common site of metastasis in the head and neck region is the brain; however, it can also metastasize to the oral cavity, gingiva, tongue, parotid gland and lymph nodes. This article reports a case of small cell lung cancer presenting with metastasis to the facial nerve.

  19. Integration of internal and external facial features in 8- to 10-year-old children and adults.

    Science.gov (United States)

    Meinhardt-Injac, Bozana; Persike, Malte; Meinhardt, Günter

    2014-06-01

    Investigation of whole-part and composite effects in 4- to 6-year-old children gave rise to claims that face perception is fully mature within the first decade of life (Crookes & McKone, 2009). However, only internal features were tested, and the role of external features was not addressed, although external features are highly relevant for holistic face perception (Sinha & Poggio, 1996; Axelrod & Yovel, 2010, 2011). In this study, 8- to 10-year-old children and adults performed a same-different matching task with faces and watches. In this task participants attended to either internal or external features. Holistic face perception was tested using a congruency paradigm, in which face and non-face stimuli either agreed or disagreed in both features (congruent contexts) or just in the attended ones (incongruent contexts). In both age groups, pronounced context congruency and inversion effects were found for faces, but not for watches. These findings indicate holistic feature integration for faces. While inversion effects were highly similar in both age groups, context congruency effects were stronger for children. Moreover, children's face matching performance was generally better when attending to external compared to internal features. Adults tended to perform better when attending to internal features. Our results indicate that both adults and 8- to 10-year-old children integrate external and internal facial features into holistic face representations. However, in children's face representations external features are much more relevant. These findings suggest that face perception is holistic but still not adult-like at the end of the first decade of life. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Facial Video-Based Photoplethysmography to Detect HRV at Rest.

    Science.gov (United States)

    Moreno, J; Ramos-Castro, J; Movellan, J; Parrado, E; Rodas, G; Capdevila, L

    2015-06-01

    Our aim is to demonstrate the usefulness of photoplethysmography (PPG) for analyzing heart rate variability (HRV) using a standard 5-min test at rest with paced breathing, comparing the results with real RR intervals and testing supine and sitting positions. Simultaneous recordings of R-R intervals were conducted with a Polar system and a non-contact PPG, based on facial video recording on 20 individuals. Data analysis and editing were performed with individually designated software for each instrument. Agreement on HRV parameters was assessed with concordance correlations, effect size from ANOVA and Bland and Altman plots. For supine position, differences between video and Polar systems showed a small effect size in most HRV parameters. For sitting position, these differences showed a moderate effect size in most HRV parameters. A new procedure, based on the pixels that contained more heart beat information, is proposed for improving the signal-to-noise ratio in the PPG video signal. Results were acceptable in both positions but better in the supine position. Our approach could be relevant for applications that require monitoring of stress or cardio-respiratory health, such as effort/recuperation states in sports. © Georg Thieme Verlag KG Stuttgart · New York.

  1. Assessment of the facial features and chin development of fetuses with use of serial three-dimensional sonography and the mandibular size monogram in a Chinese population.

    Science.gov (United States)

    Tsai, Meng-Yin; Lan, Kuo-Chung; Ou, Chia-Yo; Chen, Jen-Huang; Chang, Shiuh-Young; Hsu, Te-Yao

    2004-02-01

    Our purpose was to evaluate whether the application of serial three-dimensional (3D) sonography and the mandibular size monogram can allow observation of dynamic changes in facial features, as well as chin development in utero. The mandibular size monogram has been established through a cross-sectional study involving 183 fetal images. The serial changes of facial features and chin development are assessed in a cohort study involving 40 patients. The monogram reveals that the Biparietal distance (BPD)/Mandibular body length (MBL) ratio is gradually decreased with the advance of gestational age. The cohort study conducted with serial 3D sonography shows the same tendency. Both the images and the results of paired-samples t test (Pmonogram display disproportionate growth of the fetal head and chin that leads to changes in facial features in late gestation. This fact must be considered when we evaluate fetuses at risk for development of micrognathia.

  2. MPEG-4-based 2D facial animation for mobile devices

    Science.gov (United States)

    Riegel, Thomas B.

    2005-03-01

    The enormous spread of mobile computing devices (e.g. PDA, cellular phone, palmtop, etc.) emphasizes scalable applications, since users like to run their favorite programs on the terminal they operate at that moment. Therefore appliances are of interest, which can be adapted to the hardware realities without loosing a lot of their functionalities. A good example for this is "Facial Animation," which offers an interesting way to achieve such "scalability." By employing MPEG-4, which provides an own profile for facial animation, a solution for low power terminals including mobile phones is demonstrated. From the generic 3D MPEG-4 face a specific 2D head model is derived, which consists primarily of a portrait image superposed by a suited warping mesh and adapted 2D animation rules. Thus the animation process of MPEG-4 need not be changed and standard compliant facial animation parameters can be used to displace the vertices of the mesh and warp the underlying image accordingly.

  3. Facial Emotion Recognition Using Context Based Multimodal Approach

    Directory of Open Access Journals (Sweden)

    Priya Metri

    2011-12-01

    Full Text Available Emotions play a crucial role in person to person interaction. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers. The ability to understand human emotions is desirable for the computer in several applications especially by observing facial expressions. This paper explores a ways of human-computer interaction that enable the computer to be more aware of the user’s emotional expressions we present a approach for the emotion recognition from a facial expression, hand and body posture. Our model uses multimodal emotion recognition system in which we use two different models for facial expression recognition and for hand and body posture recognition and then combining the result of both classifiers using a third classifier which give the resulting emotion . Multimodal system gives more accurate result than a signal or bimodal system

  4. Familiarity and Within-Person Facial Variability: The Importance of the Internal and External Features.

    Science.gov (United States)

    Kramer, Robin S S; Manesi, Zoi; Towler, Alice; Reynolds, Michael G; Burton, A Mike

    2018-01-01

    As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces-sorting was more accurate and showed very few errors in comparison with unfamiliar faces. However, for both familiar and unfamiliar faces, sorting was less accurate for external features and equivalent for internal and full faces. In Experiment 3, we asked whether external features can ever be used to make an accurate sort. Using familiar faces and instructions on the number of identities present, we nevertheless found worse performance for the external in comparison with the internal features, suggesting that less identity information was available in the former. Taken together, we show that full faces and internal features are similarly informative with regard to identity. In comparison, external features contain less identity information and produce worse card sorting performance. This research extends current thinking on the shift in focus, both in attention and importance, toward the internal features and away from the external features as familiarity with a face increases.

  5. Review of research in feature based design

    NARCIS (Netherlands)

    Salomons, O.W.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

    1993-01-01

    Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems

  6. 3D facial expression recognition based on histograms of surface differential quantities

    KAUST Repository

    Li, Huibin

    2011-01-01

    3D face models accurately capture facial surfaces, making it possible for precise description of facial activities. In this paper, we present a novel mesh-based method for 3D facial expression recognition using two local shape descriptors. To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle theory based curvature estimation method is employed on 3D face models along with the common cubic fitting curvature estimation method for the purpose of comparison. Based on the basic fact that different expressions involve different local shape deformations, the SVM classifier with both linear and RBF kernels outperforms the state of the art results on the subset of the BU-3DFE database with the same experimental setting. © 2011 Springer-Verlag.

  7. Familiarity and within-person facial variability: the importance of the internal and external features

    OpenAIRE

    Kramer, R. S. S.; Manesi, Z.; Towler, A.; Reynolds, M. G.; Burton, A. M.

    2018-01-01

    As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces—sorting was more accurate and showed very few errors in comparison w...

  8. Image-based Analysis of Emotional Facial Expressions in Full Face Transplants.

    Science.gov (United States)

    Bedeloglu, Merve; Topcu, Çagdas; Akgul, Arzu; Döger, Ela Naz; Sever, Refik; Ozkan, Ozlenen; Ozkan, Omer; Uysal, Hilmi; Polat, Ovunc; Çolak, Omer Halil

    2018-01-20

    In this study, it is aimed to determine the degree of the development in emotional expression of full face transplant patients from photographs. Hence, a rehabilitation process can be planned according to the determination of degrees as a later work. As envisaged, in full face transplant cases, the determination of expressions can be confused or cannot be achieved as the healthy control group. In order to perform image-based analysis, a control group consist of 9 healthy males and 2 full-face transplant patients participated in the study. Appearance-based Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) methods are adopted for recognizing neutral and 6 emotional expressions which consist of angry, scared, happy, hate, confused and sad. Feature extraction was carried out by using both methods and combination of these methods serially. In the performed expressions, the extracted features of the most distinct zones in the facial area where the eye and mouth region, have been used to classify the emotions. Also, the combination of these region features has been used to improve classifier performance. Control subjects and transplant patients' ability to perform emotional expressions have been determined with K-nearest neighbor (KNN) classifier with region-specific and method-specific decision stages. The results have been compared with healthy group. It has been observed that transplant patients don't reflect some emotional expressions. Also, there were confusions among expressions.

  9. A model based method for automatic facial expression recognition

    NARCIS (Netherlands)

    Kuilenburg, H. van; Wiering, M.A.; Uyl, M. den

    2006-01-01

    Automatic facial expression recognition is a research topic with interesting applications in the field of human-computer interaction, psychology and product marketing. The classification accuracy for an automatic system which uses static images as input is however largely limited by the image

  10. Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Qi Jia

    2015-03-01

    Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

  11. Emotion Index of Cover Song Music Video Clips based on Facial Expression Recognition

    DEFF Research Database (Denmark)

    Kavallakis, George; Vidakis, Nikolaos; Triantafyllidis, Georgios

    2017-01-01

    This paper presents a scheme of creating an emotion index of cover song music video clips by recognizing and classifying facial expressions of the artist in the video. More specifically, it fuses effective and robust algorithms which are employed for expression recognition, along with the use...... of a neural network system using the features extracted by the SIFT algorithm. Also we support the need of this fusion of different expression recognition algorithms, because of the way that emotions are linked to facial expressions in music video clips....

  12. Facial Expression Recognition

    NARCIS (Netherlands)

    Pantic, Maja; Li, S.; Jain, A.

    2009-01-01

    Facial expression recognition is a process performed by humans or computers, which consists of: 1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial

  13. External and internal facial features modulate processing of vertical but not horizontal spatial relations.

    Science.gov (United States)

    Meinhardt, Günter; Kurbel, David; Meinhardt-Injac, Bozana; Persike, Malte

    2018-03-22

    Some years ago an asymmetry was reported for the inversion effect for horizontal (H) and vertical (V) relational face manipulations (Goffaux & Rossion, 2007). Subsequent research examined whether a specific disruption of long-range relations underlies the H/V inversion asymmetry (Sekunova & Barton, 2008). Here, we tested how detection of changes in interocular distance (H) and eye height (V) depends on cardinal internal features and external feature surround. Results replicated the H/V inversion asymmetry. Moreover, we found very different face cue dependencies for both change types. Performance and inversion effects did not depend on the presence of other face cues for detecting H changes. In contrast, accuracy for detecting V changes strongly depended on internal and external features, showing cumulative improvement when more cues were added. Inversion effects were generally large, and larger with external feature surround. The cue independence in detecting H relational changes indicates specialized local processing tightly tuned to the eyes region, while the strong cue dependency in detecting V relational changes indicates a global mechanism of cue integration across different face regions. These findings suggest that the H/V asymmetry of the inversion effect rests on an H/V anisotropy of face cue dependency, since only the global V mechanism suffers from disruption of cue integration as the major effect of face inversion. Copyright © 2018. Published by Elsevier Ltd.

  14. Heartbeat Rate Measurement from Facial Video

    DEFF Research Database (Denmark)

    Haque, Mohammad Ahsanul; Irani, Ramin; Nasrollahi, Kamal

    2016-01-01

    Heartbeat Rate (HR) reveals a person’s health condition. This paper presents an effective system for measuring HR from facial videos acquired in a more realistic environment than the testing environment of current systems. The proposed method utilizes a facial feature point tracking method...... by combining a ‘Good feature to track’ and a ‘Supervised descent method’ in order to overcome the limitations of currently available facial video based HR measuring systems. Such limitations include, e.g., unrealistic restriction of the subject’s movement and artificial lighting during data capture. A face...

  15. A small-world network model of facial emotion recognition.

    Science.gov (United States)

    Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto

    2016-01-01

    Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.

  16. SIFT based algorithm for point feature tracking

    Directory of Open Access Journals (Sweden)

    Adrian BURLACU

    2007-12-01

    Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.

  17. Personality Trait and Facial Expression Filter-Based Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Seongah Chin

    2013-02-01

    Full Text Available In this paper, we present technical approaches that bridge the gap in the research related to the use of brain-computer interfaces for entertainment and facial expressions. Such facial expressions that reflect an individual's personal traits can be used to better realize artificial facial expressions in a gaming environment based on a brain-computer interface. First, an emotion extraction filter is introduced in order to classify emotions on the basis of the users' brain signals in real time. Next, a personality trait filter is defined to classify extrovert and introvert types, which manifest as five traits: very extrovert, extrovert, medium, introvert and very introvert. In addition, facial expressions derived from expression rates are obtained by an extrovert-introvert fuzzy model through its defuzzification process. Finally, we confirm this validation via an analysis of the variance of the personality trait filter, a k-fold cross validation of the emotion extraction filter, an accuracy analysis, a user study of facial synthesis and a test case game.

  18. Facial orientation and facial shape in extant great apes: a geometric morphometric analysis of covariation.

    Science.gov (United States)

    Neaux, Dimitri; Guy, Franck; Gilissen, Emmanuel; Coudyzer, Walter; Vignaud, Patrick; Ducrocq, Stéphane

    2013-01-01

    The organization of the bony face is complex, its morphology being influenced in part by the rest of the cranium. Characterizing the facial morphological variation and craniofacial covariation patterns in extant hominids is fundamental to the understanding of their evolutionary history. Numerous studies on hominid facial shape have proposed hypotheses concerning the relationship between the anterior facial shape, facial block orientation and basicranial flexion. In this study we test these hypotheses in a sample of adult specimens belonging to three extant hominid genera (Homo, Pan and Gorilla). Intraspecific variation and covariation patterns are analyzed using geometric morphometric methods and multivariate statistics, such as partial least squared on three-dimensional landmarks coordinates. Our results indicate significant intraspecific covariation between facial shape, facial block orientation and basicranial flexion. Hominids share similar characteristics in the relationship between anterior facial shape and facial block orientation. Modern humans exhibit a specific pattern in the covariation between anterior facial shape and basicranial flexion. This peculiar feature underscores the role of modern humans' highly-flexed basicranium in the overall integration of the cranium. Furthermore, our results are consistent with the hypothesis of a relationship between the reduction of the value of the cranial base angle and a downward rotation of the facial block in modern humans, and to a lesser extent in chimpanzees.

  19. Neural processing of fearful and happy facial expressions during emotion-relevant and emotion-irrelevant tasks: a fixation-to-feature approach

    Science.gov (United States)

    Neath-Tavares, Karly N.; Itier, Roxane J.

    2017-01-01

    Research suggests an important role of the eyes and mouth for discriminating facial expressions of emotion. A gaze-contingent procedure was used to test the impact of fixation to facial features on the neural response to fearful, happy and neutral facial expressions in an emotion discrimination (Exp.1) and an oddball detection (Exp.2) task. The N170 was the only eye-sensitive ERP component, and this sensitivity did not vary across facial expressions. In both tasks, compared to neutral faces, responses to happy expressions were seen as early as 100–120ms occipitally, while responses to fearful expressions started around 150ms, on or after the N170, at both occipital and lateral-posterior sites. Analyses of scalp topographies revealed different distributions of these two emotion effects across most of the epoch. Emotion processing interacted with fixation location at different times between tasks. Results suggest a role of both the eyes and mouth in the neural processing of fearful expressions and of the mouth in the processing of happy expressions, before 350ms. PMID:27430934

  20. Generation of facial expressions from emotion using a fuzzy rule based system

    NARCIS (Netherlands)

    Bui, T.D.; Heylen, Dirk K.J.; Poel, Mannes; Nijholt, Antinus; Stumptner, Markus; Corbett, Dan; Brooks, Mike

    2001-01-01

    We propose a fuzzy rule-based system to map representations of the emotional state of an animated agent onto muscle contraction values for the appropriate facial expressions. Our implementation pays special attention to the way in which continuous changes in the intensity of emotions can be

  1. Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images

    DEFF Research Database (Denmark)

    Bellantonio, Marco; Haque, Mohammad Ahsanul; Rodriguez, Pau

    2017-01-01

    Automatic pain detection is a long expected solution to a prevalent medical problem of pain management. This is more relevant when the subject of pain is young children or patients with limited ability to communicate about their pain experience. Computer vision-based analysis of facial pain...

  2. Nine-year-old children use norm-based coding to visually represent facial expression.

    Science.gov (United States)

    Burton, Nichola; Jeffery, Linda; Skinner, Andrew L; Benton, Christopher P; Rhodes, Gillian

    2013-10-01

    Children are less skilled than adults at making judgments about facial expression. This could be because they have not yet developed adult-like mechanisms for visually representing faces. Adults are thought to represent faces in a multidimensional face-space, and have been shown to code the expression of a face relative to the norm or average face in face-space. Norm-based coding is economical and adaptive, and may be what makes adults more sensitive to facial expression than children. This study investigated the coding system that children use to represent facial expression. An adaptation aftereffect paradigm was used to test 24 adults and 18 children (9 years 2 months to 9 years 11 months old). Participants adapted to weak and strong antiexpressions. They then judged the expression of an average expression. Adaptation created aftereffects that made the test face look like the expression opposite that of the adaptor. Consistent with the predictions of norm-based but not exemplar-based coding, aftereffects were larger for strong than weak adaptors for both age groups. Results indicate that, like adults, children's coding of facial expressions is norm-based. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  3. Adaptive metric learning with deep neural networks for video-based facial expression recognition

    Science.gov (United States)

    Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

    2018-01-01

    Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

  4. A comprehensive approach to long-standing facial paralysis based on lengthening temporalis myoplasty.

    Science.gov (United States)

    Labbè, D; Bussu, F; Iodice, A

    2012-06-01

    Long-standing peripheral monolateral facial paralysis in the adult has challenged otolaryngologists, neurologists and plastic surgeons for centuries. Notwithstanding, the ultimate goal of normality of the paralyzed hemi-face with symmetry at rest, and the achievement of a spontaneous symmetrical smile with corneal protection, has not been fully reached. At the beginning of the 20(th) century, the main options were neural reconstructions including accessory to facial nerve transfer and hypoglossal to facial nerve crossover. In the first half of the 20(th) century, various techniques for static correction with autologous temporalis muscle and fascia grafts were proposed as the techniques of Gillies (1934) and McLaughlin (1949). Cross-facial nerve grafts have been performed since the beginning of the 1970s often with the attempt to transplant free-muscle to restore active movements. However, these transplants were non-vascularized, and further evaluations revealed central fibrosis and minimal return of function. A major step was taken in the second half of the 1970s, with the introduction of microneurovascular muscle transfer in facial reanimation, which, often combined in two steps with a cross-facial nerve graft, has become the most popular option for the comprehensive treatment of long-standing facial paralysis. In the second half of the 1990s in France, a regional muscle transfer technique with the definite advantages of being one-step, technically easier and relatively fast, namely lengthening temporalis myoplasty, acquired popularity and consensus among surgeons treating facial paralysis. A total of 111 patients with facial paralysis were treated in Caen between 1997 and 2005 by a single surgeon who developed 2 variants of the technique (V1, V2), each with its advantages and disadvantages, but both based on the same anatomo-functional background and aim, which is transfer of the temporalis muscle tendon on the coronoid process to the lips. For a comprehensive

  5. Cloud field classification based on textural features

    Science.gov (United States)

    Sengupta, Sailes Kumar

    1989-01-01

    An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

  6. Audiovisual laughter detection based on temporal features

    NARCIS (Netherlands)

    Petridis, Stavros; Nijholt, Antinus; Nijholt, A.; Pantic, M.; Pantic, Maja; Poel, Mannes; Poel, M.; Hondorp, G.H.W.

    2008-01-01

    Previous research on automatic laughter detection has mainly been focused on audio-based detection. In this study we present an audiovisual approach to distinguishing laughter from speech based on temporal features and we show that the integration of audio and visual information leads to improved

  7. Facial expression recognition and model-based regeneration for distance teaching

    Science.gov (United States)

    De Silva, Liyanage C.; Vinod, V. V.; Sengupta, Kuntal

    1998-12-01

    This paper presents a novel idea of a visual communication system, which can support distance teaching using a network of computers. Here the author's main focus is to enhance the quality of distance teaching by reducing the barrier between the teacher and the student, which is formed due to the remote connection of the networked participants. The paper presents an effective way of improving teacher-student communication link of an IT (Information Technology) based distance teaching scenario, using facial expression recognition results and face global and local motion detection results of both the teacher and the student. It presents a way of regenerating the facial images for the teacher-student down-link, which can enhance the teachers facial expressions and which also can reduce the network traffic compared to usual video broadcasting scenarios. At the same time, it presents a way of representing a large volume of facial expression data of the whole student population (in the student-teacher up-link). This up-link representation helps the teacher to receive an instant feed back of his talk, as if he was delivering a face to face lecture. In conventional video tele-conferencing type of applications, this task is nearly impossible, due to huge volume of upward network traffic. The authors utilize several of their previous publication results for most of the image processing components needs to be investigated to complete such a system. In addition, some of the remaining system components are covered by several on going work.

  8. Feature based omnidirectional sparse visual path following

    OpenAIRE

    Goedemé, Toon; Tuytelaars, Tinne; Van Gool, Luc; Vanacker, Gerolf; Nuttin, Marnix

    2005-01-01

    Goedemé T., Tuytelaars T., Van Gool L., Vanacker G., Nuttin M., ''Feature based omnidirectional sparse visual path following'', Proceedings IEEE/RSJ international conference on intelligent robots and systems - IROS2005, pp. 1003-1008, August 2-6, 2005, Edmonton, Alberta, Canada.

  9. Toward a universal, automated facial measurement tool in facial reanimation.

    Science.gov (United States)

    Hadlock, Tessa A; Urban, Luke S

    2012-01-01

    To describe a highly quantitative facial function-measuring tool that yields accurate, objective measures of facial position in significantly less time than existing methods. Facial Assessment by Computer Evaluation (FACE) software was designed for facial analysis. Outputs report the static facial landmark positions and dynamic facial movements relevant in facial reanimation. Fifty individuals underwent facial movement analysis using Photoshop-based measurements and the new software; comparisons of agreement and efficiency were made. Comparisons were made between individuals with normal facial animation and patients with paralysis to gauge sensitivity to abnormal movements. Facial measurements were matched using FACE software and Photoshop-based measures at rest and during expressions. The automated assessments required significantly less time than Photoshop-based assessments.FACE measurements easily revealed differences between individuals with normal facial animation and patients with facial paralysis. FACE software produces accurate measurements of facial landmarks and facial movements and is sensitive to paralysis. Given its efficiency, it serves as a useful tool in the clinical setting for zonal facial movement analysis in comprehensive facial nerve rehabilitation programs.

  10. Feature Selection Based on Mutual Correlation

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Somol, Petr; Ververidis, D.; Kotropoulos, C.

    2006-01-01

    Roč. 19, č. 4225 (2006), s. 569-577 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection Subject RIV: BD - Theory of Information Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/haindl-feature selection based on mutual correlation.pdf

  11. An object-oriented feature-based design system face-based detection of feature interactions

    International Nuclear Information System (INIS)

    Ariffin Abdul Razak

    1999-01-01

    This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

  12. Reconstruction of various perinasal defects using facial artery perforator-based nasolabial island flaps.

    Science.gov (United States)

    Yoon, Tae Ho; Yun, In Sik; Rha, Dong Kyun; Lee, Won Jai

    2013-11-01

    Classical flaps for perinasal defect reconstruction, such as forehead or nasolabial flaps, have some disadvantages involving limitations of the arc of rotation and two stages of surgery. However, a perforator-based flap is more versatile and allows freedom in flap design. We introduced our experience with reconstruction using a facial artery perforator-based propeller flap on the perinasal area. We describe the surgical differences between different defect subtypes. Between December 2005 and August 2013, 10 patients underwent perinasal reconstruction in which a facial artery perforator-based flap was used. We divided the perinasal defects into types A and B, according to location. The operative results, including flap size, arc of rotation, complications, and characteristics of the perforator were evaluated by retrospective chart review and photographic evaluation. Eight patients were male and 2 patients were female. Their mean age was 61 years (range, 35-75 years). The size of the flap ranged from 1 cm×1.5 cm to 3 cm×6 cm. Eight patients healed uneventfully, but 2 patients presented with mild flap congestion. However, these 2 patients healed by conservative management without any additional surgery. All of the flaps survived completely with aesthetically pleasing results. The facial artery perforator-based flap allowed for versatile customized flaps, and the donor site scar was concealed using the natural nasolabial fold.

  13. Feature Fusion Based Audio-Visual Speaker Identification Using Hidden Markov Model under Different Lighting Variations

    Directory of Open Access Journals (Sweden)

    Md. Rabiul Islam

    2014-01-01

    Full Text Available The aim of the paper is to propose a feature fusion based Audio-Visual Speaker Identification (AVSI system with varied conditions of illumination environments. Among the different fusion strategies, feature level fusion has been used for the proposed AVSI system where Hidden Markov Model (HMM is used for learning and classification. Since the feature set contains richer information about the raw biometric data than any other levels, integration at feature level is expected to provide better authentication results. In this paper, both Mel Frequency Cepstral Coefficients (MFCCs and Linear Prediction Cepstral Coefficients (LPCCs are combined to get the audio feature vectors and Active Shape Model (ASM based appearance and shape facial features are concatenated to take the visual feature vectors. These combined audio and visual features are used for the feature-fusion. To reduce the dimension of the audio and visual feature vectors, Principal Component Analysis (PCA method is used. The VALID audio-visual database is used to measure the performance of the proposed system where four different illumination levels of lighting conditions are considered. Experimental results focus on the significance of the proposed audio-visual speaker identification system with various combinations of audio and visual features.

  14. I care, even after the first impression: Facial appearance-based evaluations in healthcare context.

    Science.gov (United States)

    Mattarozzi, Katia; Colonnello, Valentina; De Gioia, Francesco; Todorov, Alexander

    2017-06-01

    Prior research has demonstrated that healthcare providers' implicit biases may contribute to healthcare disparities. Independent research in social psychology indicates that facial appearance-based evaluations affect social behavior in a variety of domains, influencing political, legal, and economic decisions. Whether and to what extent these evaluations influence approach behavior in healthcare contexts warrants research attention. Here we investigate the impact of facial appearance-based evaluations of trustworthiness on healthcare providers' caring inclination, and the moderating role of experience and information about the social identity of the faces. Novice and expert nurses rated their inclination to provide care when viewing photos of trustworthy-, neutral-, and untrustworthy-looking faces. To explore whether information about the target of care influences caring inclination, some participants were told that they would view patients' faces while others received no information about the faces. Both novice and expert nurses had higher caring inclination scores for trustworthy-than for untrustworthy-looking faces; however, experts had higher scores than novices for untrustworthy-looking faces. Regardless of a face's trustworthiness level, experts had higher caring inclination scores for patients than for unidentified individuals, while novices showed no differences. Facial appearance-based inferences can bias caring inclination in healthcare contexts. However, expert healthcare providers are less biased by these inferences and more sensitive to information about the target of care. These findings highlight the importance of promoting novice healthcare professionals' awareness of first impression biases. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. A dynamic texture-based approach to recognition of facial actions and their temporal models.

    Science.gov (United States)

    Koelstra, Sander; Pantic, Maja; Patras, Ioannis

    2010-11-01

    In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Nonrigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI facial expression database, the proposed method achieved an average event recognition accuracy of 89.2 percent for the MHI method and 94.3 percent for the FFD method. The generalization performance of the FFD method has been tested using the Cohn-Kanade database. Finally, we also explored the performance on spontaneous expressions in the Sensitive Artificial Listener data set.

  16. Facial paralysis

    Science.gov (United States)

    ... otherwise healthy, facial paralysis is often due to Bell palsy . This is a condition in which the facial ... speech, or occupational therapist. If facial paralysis from Bell palsy lasts for more than 6 to 12 months, ...

  17. Facial-based ethnic recognition: insights from two closely related but ethnically distinct groups

    Directory of Open Access Journals (Sweden)

    S. P. Henzi

    2010-02-01

    Full Text Available Previous studies on facial recognition have considered widely separated populations, both geographically and culturally, making it hard to disentangle effects of familiarity with an ability to identify ethnic groups per se.We used data from a highly intermixed population of African peoples from South Africa to test whether individuals from nine different ethnic groups could correctly differentiate between facial images of two of these, the Tswana and Pedi. Individuals could not assign ethnicity better than expected by chance, and there was no significant difference between genders in accuracy of assignment. Interestingly, we observed a trend that individuals of mixed ethnic origin were better at assigning ethnicity to Pedi and Tswanas, than individuals from less mixed backgrounds. This result supports the hypothesis that ethnic recognition is based on the visual

  18. Interactions between facial emotion and identity in face processing: evidence based on redundancy gains.

    Science.gov (United States)

    Yankouskaya, Alla; Booth, David A; Humphreys, Glyn

    2012-11-01

    Interactions between the processing of emotion expression and form-based information from faces (facial identity) were investigated using the redundant-target paradigm, in which we specifically tested whether identity and emotional expression are integrated in a superadditive manner (Miller, Cognitive Psychology 14:247-279, 1982). In Experiments 1 and 2, participants performed emotion and face identity judgments on faces with sad or angry emotional expressions. Responses to redundant targets were faster than responses to either single target when a universal emotion was conveyed, and performance violated the predictions from a model assuming independent processing of emotion and face identity. Experiment 4 showed that these effects were not modulated by varying interstimulus and nontarget contingencies, and Experiment 5 demonstrated that the redundancy gains were eliminated when faces were inverted. Taken together, these results suggest that the identification of emotion and facial identity interact in face processing.

  19. Management of the Facial Nerve in Lateral Skull Base Surgery Analytic Retrospective study

    Directory of Open Access Journals (Sweden)

    Mohamed A. El Shazly

    2011-01-01

    Full Text Available Background Surgical approaches to the jugular foramen are often complex and lengthy procedures associated with significant morbidity based on the anatomic and tumor characteristics. In addition to the risk of intra-operative hemorrhage from vascular tumors, lower cranial nerves deficits are frequently increased after intra-operative manipulation. Accordingly, modifications in the surgical techniques have been developed to minimize these risks. Preoperative embolization and intra-operative ligation of the external carotid artery have decreased the intraoperative blood loss. Accurate identification and exposure of the cranial nerves extracranially allows for their preservation during tumor resection. The modification of facial nerve mobilization provides widened infratemporal exposure with less postoperative facial weakness. The ideal approach should enable complete, one stage tumor resection with excellent infratemporal and posterior fossa exposure and would not aggravate or cause neurologic deficit. The aim of this study is to present our experience in handling jugular foramen lesions (mainly glomus jugulare without the need for anterior facial nerve transposition. Methods In this series we present our experience in Kasr ElEini University hospital (Cairo–-Egypt in handling 36 patients with jugular foramen lesions over a period of 20 years where the previously mentioned preoperative and operative rules were followed. The clinical status, operative technique and postoperative care and outcome are detailed and analyzed in relation to the outcome. Results Complete cure without complications was achieved in four cases of congenital cholesteatoma and four cases with class B glomus. In advanced cases of glomus jugulare (28 patients (C and D stages complete cure was achieved in 21 of them (75%. The operative complications were also related to this group of 28 patients, in the form of facial paralysis in 20 of them (55.6% and symptomatic vagal

  20. Facial asymmetry correction with moulded helmet therapy in infants with deformational skull base plagiocephaly.

    Science.gov (United States)

    Kreutz, Matthias; Fitze, Brigitte; Blecher, Christoph; Marcello, Augello; Simon, Ruben; Cremer, Rebecca; Zeilhofer, Hans-Florian; Kunz, Christoph; Mayr, Johannes

    2018-01-01

    The recommendation issued by the American Academy of Pediatrics in the early 1990s to position infants on their back during sleep to prevent sudden infant death syndrome (SIDS) has dramatically reduced the number of deaths due to SIDS but has also markedly increased the prevalence of positional skull deformation in infants. Deformation of the base of the skull occurs predominantly in very severe deformational plagiocephaly and is accompanied by facial asymmetry, as well as an altered ear position, called ear shift. Moulded helmet therapy has become an accepted treatment strategy for infants with deformational plagiocephaly. The aim of this study was to determine whether facial asymmetry could be corrected by moulded helmet therapy. In this retrospective, single-centre study, we analysed facial asymmetry of 71 infants with severe deformational plagiocephaly with or without deformational brachycephaly who were undergoing moulded helmet therapy between 2009 and 2013. Computer-assisted, three-dimensional, soft-tissue photographic scanning was used to record the head shape before and after moulded helmet therapy. The distance between two landmarks in the midline of the face (i.e., root of the nose and nasal septum) and the right and left tragus were measured on computer-generated indirect and objective 3D photogrammetry images. A quotient was calculated between the two right- and left-sided distances to the midline. Quotients were compared before and after moulded helmet therapy. Infants without any therapy served as a control group. The median age of the infants before onset of moulded helmet therapy was 5 months (range 3-16 months). The median duration of moulded helmet therapy was 5 months (range 1-16 months). Comparison of the pre- and post-treatment quotients of the left vs. right distances measured between the tragus and root of the nose (n = 71) and nasal septum (n = 71) revealed a significant reduction of the asymmetry (Tragus-Nasion-Line Quotient: 0

  1. Management of the facial nerve in lateral skull base surgery analytic retrospective study.

    Science.gov (United States)

    El Shazly, Mohamed A; Mokbel, Mahmoud A M; Elbadry, Amr A; Badran, Hatem S

    2011-01-01

    Surgical approaches to the jugular foramen are often complex and lengthy procedures associated with significant morbidity based on the anatomic and tumor characteristics. In addition to the risk of intra-operative hemorrhage from vascular tumors, lower cranial nerves deficits are frequently increased after intra-operative manipulation. Accordingly, modifications in the surgical techniques have been developed to minimize these risks. Preoperative embolization and intra-operative ligation of the external carotid artery have decreased the intraoperative blood loss. Accurate identification and exposure of the cranial nerves extracranially allows for their preservation during tumor resection. The modification of facial nerve mobilization provides widened infratemporal exposure with less postoperative facial weakness. The ideal approach should enable complete, one stage tumor resection with excellent infratemporal and posterior fossa exposure and would not aggravate or cause neurologic deficit. The aim of this study is to present our experience in handling jugular foramen lesions (mainly glomus jugulare) without the need for anterior facial nerve transposition. In this series we present our experience in Kasr ElEini University hospital (Cairo-Egypt) in handling 36 patients with jugular foramen lesions over a period of 20 years where the previously mentioned preoperative and operative rules were followed. The clinical status, operative technique and postoperative care and outcome are detailed and analyzed in relation to the outcome. Complete cure without complications was achieved in four cases of congenital cholesteatoma and four cases with class B glomus. In advanced cases of glomus jugulare (28 patients) (C and D stages) complete cure was achieved in 21 of them (75%). The operative complications were also related to this group of 28 patients, in the form of facial paralysis in 20 of them (55.6%) and symptomatic vagal paralysis in 18 of them (50%). Total anterior

  2. Morphometric studies on the facial skeleton of humans and pongids based on CT-scans.

    Science.gov (United States)

    Schumacher, K U; Koppe, T; Fanghänel, J; Schumacher, G H; Nagai, H

    1994-10-01

    The changes of the skull, which we can observe during the anthropogenesis, are reflected especially in the different skull proportions. We carried out metric measurements at the median level on 10 adult skulls each of humans, chimpanzees and gorillas as well as 11 skulls of orangutans. All skulls were scanned with a CT at the median level. We measured the lines and angles of the scans and the means and the standard deviations were calculated. We carried out a correlation analysis to observe the relation of their characteristics. We showed that there is a relation between the length of the skull base and the facial length in all species. From the results of the correlation analysis, we can also conclude that a relation exists between the degree of prognathism and the different length measurements of the facial skeleton. We also found a bending of the facial skeleton in relation to the cranial base towards the ventral side, also known as klinorhynchy, in all observed species. The highest degree of klinorhynchy was found in humans and the lowest in orangutans. We will discuss the different definition of the term klinorhynchy and its importance in the evolution of the hominoids.

  3. A Feature-Based Structural Measure: An Image Similarity Measure for Face Recognition

    Directory of Open Access Journals (Sweden)

    Noor Abdalrazak Shnain

    2017-08-01

    Full Text Available Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called the Feature-Based Structural Measure (FSM, combines the best features of the well-known SSIM (structural similarity index measure and FSIM (feature similarity index measure approaches, striking a balance between performance for similar and dissimilar images of human faces. In addition to the statistical structural properties provided by SSIM, edge detection is incorporated in FSM as a distinctive structural feature. Its performance is tested for a wide range of PSNR (peak signal-to-noise ratio, using ORL (Olivetti Research Laboratory, now AT&T Laboratory Cambridge and FEI (Faculty of Industrial Engineering, São Bernardo do Campo, São Paulo, Brazil databases. The proposed measure is tested under conditions of Gaussian noise; simulation results show that the proposed FSM outperforms the well-known SSIM and FSIM approaches in its efficiency of similarity detection and recognition of human faces.

  4. FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

    Directory of Open Access Journals (Sweden)

    R. Aishwarya

    2013-01-01

    Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

  5. Facial Action Unit Recognition under Incomplete Data Based on Multi-label Learning with Missing Labels

    KAUST Repository

    Li, Yongqiang

    2016-07-07

    Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.

  6. Facial Action Unit Recognition under Incomplete Data Based on Multi-label Learning with Missing Labels

    KAUST Repository

    Li, Yongqiang; Wu, Baoyuan; Ghanem, Bernard; Zhao, Yongping; Yao, Hongxun; Ji, Qiang

    2016-01-01

    Facial action unit (AU) recognition has been applied in a wild range of fields, and has attracted great attention in the past two decades. Most existing works on AU recognition assumed that the complete label assignment for each training image is available, which is often not the case in practice. Labeling AU is expensive and time consuming process. Moreover, due to the AU ambiguity and subjective difference, some AUs are difficult to label reliably and confidently. Many AU recognition works try to train the classifier for each AU independently, which is of high computation cost and ignores the dependency among different AUs. In this work, we formulate AU recognition under incomplete data as a multi-label learning with missing labels (MLML) problem. Most existing MLML methods usually employ the same features for all classes. However, we find this setting is unreasonable in AU recognition, as the occurrence of different AUs produce changes of skin surface displacement or face appearance in different face regions. If using the shared features for all AUs, much noise will be involved due to the occurrence of other AUs. Consequently, the changes of the specific AUs cannot be clearly highlighted, leading to the performance degradation. Instead, we propose to extract the most discriminative features for each AU individually, which are learned by the supervised learning method. The learned features are further embedded into the instance-level label smoothness term of our model, which also includes the label consistency and the class-level label smoothness. Both a global solution using st-cut and an approximated solution using conjugate gradient (CG) descent are provided. Experiments on both posed and spontaneous facial expression databases demonstrate the superiority of the proposed method in comparison with several state-of-the-art works.

  7. Feature-based RNN target recognition

    Science.gov (United States)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-09-01

    Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

  8. Improvements on a simple muscle-based 3D face for realistic facial expressions

    NARCIS (Netherlands)

    Bui, T.D.; Heylen, Dirk K.J.; Nijholt, Antinus; Badler, N.; Thalmann, D.

    2003-01-01

    Facial expressions play an important role in face-to-face communication. With the development of personal computers capable of rendering high quality graphics, computer facial animation has produced more and more realistic facial expressions to enrich human-computer communication. In this paper, we

  9. Comparative analysis of the anterior and posterior length and deflection angle of the cranial base, in individuals with facial Pattern I, II and III

    Directory of Open Access Journals (Sweden)

    Guilherme Thiesen

    2013-02-01

    Full Text Available OBJECTIVE: This study evaluated the variations in the anterior cranial base (S-N, posterior cranial base (S-Ba and deflection of the cranial base (SNBa among three different facial patterns (Pattern I, II and III. METHOD: A sample of 60 lateral cephalometric radiographs of Brazilian Caucasian patients, both genders, between 8 and 17 years of age was selected. The sample was divided into 3 groups (Pattern I, II and III of 20 individuals each. The inclusion criteria for each group were the ANB angle, Wits appraisal and the facial profile angle (G'.Sn.Pg'. To compare the mean values obtained from (SNBa, S-N, S-Ba each group measures, the ANOVA test and Scheffé's Post-Hoc test were applied. RESULTS AND CONCLUSIONS: There was no statistically significant difference for the deflection angle of the cranial base among the different facial patterns (Patterns I, II and III. There was no significant difference for the measures of the anterior and posterior cranial base between the facial Patterns I and II. The mean values for S-Ba were lower in facial Pattern III with statistically significant difference. The mean values of S-N in the facial Pattern III were also reduced, but without showing statistically significant difference. This trend of lower values in the cranial base measurements would explain the maxillary deficiency and/or mandibular prognathism features that characterize the facial Pattern III.OBJETIVO: o presente estudo avaliou as variações da base craniana anterior (S-N, base craniana posterior (S-Ba, e ângulo de deflexão da base do crânio (SNBa entre três diferentes padrões faciais (Padrão I, II e III. MÉTODOS: selecionou-se uma amostra de 60 telerradiografias em norma lateral de pacientes brasileiros leucodermas, de ambos os sexos, com idades entre 8 anos e 17 anos. A amostra foi dividida em três grupos (Padrão I, II e III, sendo cada grupo constituído de 20 indivíduos. Os critérios de seleção dos indivíduos para cada grupo

  10. Hirschsprung disease, microcephaly, mental retardation, and characteristic facial features: delineation of a new syndrome and identification of a locus at chromosome 2q22-q23.

    Science.gov (United States)

    Mowat, D R; Croaker, G D; Cass, D T; Kerr, B A; Chaitow, J; Adès, L C; Chia, N L; Wilson, M J

    1998-01-01

    We have identified six children with a distinctive facial phenotype in association with mental retardation (MR), microcephaly, and short stature, four of whom presented with Hirschsprung (HSCR) disease in the neonatal period. HSCR was diagnosed in a further child at the age of 3 years after investigation for severe chronic constipation and another child, identified as sharing the same facial phenotype, had chronic constipation, but did not have HSCR. One of our patients has an interstitial deletion of chromosome 2, del(2)(q21q23). These children strongly resemble the patient reported by Lurie et al with HSCR and dysmorphic features associated with del(2)(q22q23). All patients have been isolated cases, suggesting a contiguous gene syndrome or a dominant single gene disorder involving a locus for HSCR located at 2q22-q23. Review of published reports suggests that there is significant phenotypic and genetic heterogeneity within the group of patients with HSCR, MR, and microcephaly. In particular, our patients appear to have a separate disorder from Goldberg-Shprintzen syndrome, for which autosomal recessive inheritance has been proposed because of sib recurrence and consanguinity in some families. Images PMID:9719364

  11. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  12. Spoofing detection on facial images recognition using LBP and GLCM combination

    Science.gov (United States)

    Sthevanie, F.; Ramadhani, K. N.

    2018-03-01

    The challenge for the facial based security system is how to detect facial image falsification such as facial image spoofing. Spoofing occurs when someone try to pretend as a registered user to obtain illegal access and gain advantage from the protected system. This research implements facial image spoofing detection method by analyzing image texture. The proposed method for texture analysis combines the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) method. The experimental results show that spoofing detection using LBP and GLCM combination achieves high detection rate compared to that of using only LBP feature or GLCM feature.

  13. FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

    Directory of Open Access Journals (Sweden)

    Ratri Enggar Pawening

    2016-06-01

    Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

  14. Underwater Object Segmentation Based on Optical Features

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2018-01-01

    Full Text Available Underwater optical environments are seriously affected by various optical inputs, such as artificial light, sky light, and ambient scattered light. The latter two can block underwater object segmentation tasks, since they inhibit the emergence of objects of interest and distort image information, while artificial light can contribute to segmentation. Artificial light often focuses on the object of interest, and, therefore, we can initially identify the region of target objects if the collimation of artificial light is recognized. Based on this concept, we propose an optical feature extraction, calculation, and decision method to identify the collimated region of artificial light as a candidate object region. Then, the second phase employs a level set method to segment the objects of interest within the candidate region. This two-phase structure largely removes background noise and highlights the outline of underwater objects. We test the performance of the method with diverse underwater datasets, demonstrating that it outperforms previous methods.

  15. Quantative Evaluation of the Efficiency of Facial Bio-potential Signals Based on Forehead Three-Channel Electrode Placement For Facial Gesture Recognition Applicable in a Human-Machine Interface

    Directory of Open Access Journals (Sweden)

    Iman Mohammad Rezazadeh

    2010-06-01

    Full Text Available Introduction: Today, facial bio-potential signals are employed in many human-machine interface applications for enhancing and empowering the rehabilitation process. The main point to achieve that goal is to record appropriate bioelectric signals from the human face by placing and configuring electrodes over it in the right way. In this paper, heuristic geometrical position and configuration of the electrodes has been proposed for improving the quality of the acquired signals and consequently enhancing the performance of the facial gesture classifier. Materials and Methods: Investigation and evaluation of the electrodes' proper geometrical position and configuration can be performed using two methods: clinical and modeling. In the clinical method, the electrodes are placed in predefined positions and the elicited signals from them are then processed. The performance of the method is evaluated based on the results obtained. On the other hand, in the modeling approach, the quality of the recorded signals and their information content are evaluated only by modeling and simulation. In this paper, both methods have been utilized together. First, suitable electrode positions and configuration were proposed and evaluated by modeling and simulation. Then, the experiment was performed with a predefined protocol on 7 healthy subjects to validate the simulation results. Here, the recorded signals were passed through parallel butterworth filter banks to obtain facial EMG, EOG and EEG signals and the RMS features of each 256 msec time slot were extracted.  By using the power of Subtractive Fuzzy C-Mean (SFCM, 8 different facial gestures (including smiling, frowning, pulling up left and right lip corners, left/right/up and down movements of the eyes were discriminated. Results: According to the three-channel electrode configuration derived from modeling of the dipoles effects on the surface electrodes and by employing the SFCM classifier, an average 94

  16. Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

    Science.gov (United States)

    Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

    2018-01-01

    It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

  17. Automated facial acne assessment from smartphone images

    Science.gov (United States)

    Amini, Mohammad; Vasefi, Fartash; Valdebran, Manuel; Huang, Kevin; Zhang, Haomiao; Kemp, William; MacKinnon, Nicholas

    2018-02-01

    A smartphone mobile medical application is presented, that provides analysis of the health of skin on the face using a smartphone image and cloud-based image processing techniques. The mobile application employs the use of the camera to capture a front face image of a subject, after which the captured image is spatially calibrated based on fiducial points such as position of the iris of the eye. A facial recognition algorithm is used to identify features of the human face image, to normalize the image, and to define facial regions of interest (ROI) for acne assessment. We identify acne lesions and classify them into two categories: those that are papules and those that are pustules. Automated facial acne assessment was validated by performing tests on images of 60 digital human models and 10 real human face images. The application was able to identify 92% of acne lesions within five facial ROIs. The classification accuracy for separating papules from pustules was 98%. Combined with in-app documentation of treatment, lifestyle factors, and automated facial acne assessment, the app can be used in both cosmetic and clinical dermatology. It allows users to quantitatively self-measure acne severity and treatment efficacy on an ongoing basis to help them manage their chronic facial acne.

  18. Persistent facial pain conditions

    DEFF Research Database (Denmark)

    Forssell, Heli; Alstergren, Per; Bakke, Merete

    2016-01-01

    Persistent facial pains, especially temporomandibular disorders (TMD), are common conditions. As dentists are responsible for the treatment of most of these disorders, up-to date knowledge on the latest advances in the field is essential for successful diagnosis and management. The review covers...... TMD, and different neuropathic or putative neuropathic facial pains such as persistent idiopathic facial pain and atypical odontalgia, trigeminal neuralgia and painful posttraumatic trigeminal neuropathy. The article presents an overview of TMD pain as a biopsychosocial condition, its prevalence......, clinical features, consequences, central and peripheral mechanisms, diagnostic criteria (DC/TMD), and principles of management. For each of the neuropathic facial pain entities, the definitions, prevalence, clinical features, and diagnostics are described. The current understanding of the pathophysiology...

  19. Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

    Science.gov (United States)

    Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

    2018-02-01

    In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

  20. Nablus mask-like facial syndrome

    DEFF Research Database (Denmark)

    Allanson, Judith; Smith, Amanda; Hare, Heather

    2012-01-01

    Nablus mask-like facial syndrome (NMLFS) has many distinctive phenotypic features, particularly tight glistening skin with reduced facial expression, blepharophimosis, telecanthus, bulky nasal tip, abnormal external ear architecture, upswept frontal hairline, and sparse eyebrows. Over the last few...

  1. Sound-induced facial synkinesis following facial nerve paralysis.

    Science.gov (United States)

    Ma, Ming-San; van der Hoeven, Johannes H; Nicolai, Jean-Philippe A; Meek, Marcel F

    2009-08-01

    Facial synkinesis (or synkinesia) (FS) occurs frequently after paresis or paralysis of the facial nerve and is in most cases due to aberrant regeneration of (branches of) the facial nerve. Patients suffer from inappropriate and involuntary synchronous facial muscle contractions. Here we describe two cases of sound-induced facial synkinesis (SFS) after facial nerve injury. As far as we know, this phenomenon has not been described in the English literature before. Patient A presented with right hemifacial palsy after lesion of the facial nerve due to skull base fracture. He reported involuntary muscle activity at the right corner of the mouth, specifically on hearing ringing keys. Patient B suffered from left hemifacial palsy following otitis media and developed involuntary muscle contraction in the facial musculature specifically on hearing clapping hands or a trumpet sound. Both patients were evaluated by means of video, audio and EMG analysis. Possible mechanisms in the pathophysiology of SFS are postulated and therapeutic options are discussed.

  2. Web-based Visualisation of Head Pose and Facial Expressions Changes:

    DEFF Research Database (Denmark)

    Kalliatakis, Grigorios; Vidakis, Nikolaos; Triantafyllidis, Georgios

    2016-01-01

    Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating comprehensible visual representations from...... and accurately estimate head pose changes in unconstrained environment. In order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data...

  3. Innovations in individual feature history management - The significance of feature-based temporal model

    Science.gov (United States)

    Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

    2008-01-01

    A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

  4. The review and results of different methods for facial recognition

    Science.gov (United States)

    Le, Yifan

    2017-09-01

    In recent years, facial recognition draws much attention due to its wide potential applications. As a unique technology in Biometric Identification, facial recognition represents a significant improvement since it could be operated without cooperation of people under detection. Hence, facial recognition will be taken into defense system, medical detection, human behavior understanding, etc. Several theories and methods have been established to make progress in facial recognition: (1) A novel two-stage facial landmark localization method is proposed which has more accurate facial localization effect under specific database; (2) A statistical face frontalization method is proposed which outperforms state-of-the-art methods for face landmark localization; (3) It proposes a general facial landmark detection algorithm to handle images with severe occlusion and images with large head poses; (4) There are three methods proposed on Face Alignment including shape augmented regression method, pose-indexed based multi-view method and a learning based method via regressing local binary features. The aim of this paper is to analyze previous work of different aspects in facial recognition, focusing on concrete method and performance under various databases. In addition, some improvement measures and suggestions in potential applications will be put forward.

  5. Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

    Science.gov (United States)

    Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

    2017-10-12

    Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

  6. Variable developmental delays and characteristic facial features-A novel 7p22.3p22.2 microdeletion syndrome?

    Science.gov (United States)

    Yu, Andrea C; Zambrano, Regina M; Cristian, Ingrid; Price, Sue; Bernhard, Birgitta; Zucker, Marc; Venkateswaran, Sunita; McGowan-Jordan, Jean; Armour, Christine M

    2017-06-01

    Isolated 7p22.3p22.2 deletions are rarely described with only two reports in the literature. Most other reported cases either involve a much larger region of the 7p arm or have an additional copy number variation. Here, we report five patients with overlapping microdeletions at 7p22.3p22.2. The patients presented with variable developmental delays, exhibiting relative weaknesses in expressive language skills and relative strengths in gross, and fine motor skills. The most consistent facial features seen in these patients included a broad nasal root, a prominent forehead a prominent glabella and arched eyebrows. Additional variable features amongst the patients included microcephaly, metopic ridging or craniosynostosis, cleft palate, cardiac defects, and mild hypotonia. Although the patients' deletions varied in size, there was a 0.47 Mb region of overlap which contained 7 OMIM genes: EIP3B, CHST12, LFNG, BRAT1, TTYH3, AMZ1, and GNA12. We propose that monosomy of this region represents a novel microdeletion syndrome. We recommend that individuals with 7p22.3p22.2 deletions should receive a developmental assessment and a thorough cardiac exam, with consideration of an echocardiogram, as part of their initial evaluation. © 2017 Wiley Periodicals, Inc.

  7. Palmprint Based Verification System Using SURF Features

    Science.gov (United States)

    Srinivas, Badrinath G.; Gupta, Phalguni

    This paper describes the design and development of a prototype of robust biometric system for verification. The system uses features extracted using Speeded Up Robust Features (SURF) operator of human hand. The hand image for features is acquired using a low cost scanner. The palmprint region extracted is robust to hand translation and rotation on the scanner. The system is tested on IITK database of 200 images and PolyU database of 7751 images. The system is found to be robust with respect to translation and rotation. It has FAR 0.02%, FRR 0.01% and accuracy of 99.98% and can be a suitable system for civilian applications and high-security environments.

  8. Realistic Facial Expression of Virtual Human Based on Color, Sweat, and Tears Effects

    Directory of Open Access Journals (Sweden)

    Mohammed Hazim Alkawaz

    2014-01-01

    Full Text Available Generating extreme appearances such as scared awaiting sweating while happy fit for tears (cry and blushing (anger and happiness is the key issue in achieving the high quality facial animation. The effects of sweat, tears, and colors are integrated into a single animation model to create realistic facial expressions of 3D avatar. The physical properties of muscles, emotions, or the fluid properties with sweating and tears initiators are incorporated. The action units (AUs of facial action coding system are merged with autonomous AUs to create expressions including sadness, anger with blushing, happiness with blushing, and fear. Fluid effects such as sweat and tears are simulated using the particle system and smoothed-particle hydrodynamics (SPH methods which are combined with facial animation technique to produce complex facial expressions. The effects of oxygenation of the facial skin color appearance are measured using the pulse oximeter system and the 3D skin analyzer. The result shows that virtual human facial expression is enhanced by mimicking actual sweating and tears simulations for all extreme expressions. The proposed method has contribution towards the development of facial animation industry and game as well as computer graphics.

  9. Realistic facial expression of virtual human based on color, sweat, and tears effects.

    Science.gov (United States)

    Alkawaz, Mohammed Hazim; Basori, Ahmad Hoirul; Mohamad, Dzulkifli; Mohamed, Farhan

    2014-01-01

    Generating extreme appearances such as scared awaiting sweating while happy fit for tears (cry) and blushing (anger and happiness) is the key issue in achieving the high quality facial animation. The effects of sweat, tears, and colors are integrated into a single animation model to create realistic facial expressions of 3D avatar. The physical properties of muscles, emotions, or the fluid properties with sweating and tears initiators are incorporated. The action units (AUs) of facial action coding system are merged with autonomous AUs to create expressions including sadness, anger with blushing, happiness with blushing, and fear. Fluid effects such as sweat and tears are simulated using the particle system and smoothed-particle hydrodynamics (SPH) methods which are combined with facial animation technique to produce complex facial expressions. The effects of oxygenation of the facial skin color appearance are measured using the pulse oximeter system and the 3D skin analyzer. The result shows that virtual human facial expression is enhanced by mimicking actual sweating and tears simulations for all extreme expressions. The proposed method has contribution towards the development of facial animation industry and game as well as computer graphics.

  10. Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

    Directory of Open Access Journals (Sweden)

    Pachet François

    2009-01-01

    Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

  11. Decoding facial expressions based on face-selective and motion-sensitive areas.

    Science.gov (United States)

    Liang, Yin; Liu, Baolin; Xu, Junhai; Zhang, Gaoyan; Li, Xianglin; Wang, Peiyuan; Wang, Bin

    2017-06-01

    Humans can easily recognize others' facial expressions. Among the brain substrates that enable this ability, considerable attention has been paid to face-selective areas; in contrast, whether motion-sensitive areas, which clearly exhibit sensitivity to facial movements, are involved in facial expression recognition remained unclear. The present functional magnetic resonance imaging (fMRI) study used multi-voxel pattern analysis (MVPA) to explore facial expression decoding in both face-selective and motion-sensitive areas. In a block design experiment, participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise) in images, videos, and eyes-obscured videos. Due to the use of multiple stimulus types, the impacts of facial motion and eye-related information on facial expression decoding were also examined. It was found that motion-sensitive areas showed significant responses to emotional expressions and that dynamic expressions could be successfully decoded in both face-selective and motion-sensitive areas. Compared with static stimuli, dynamic expressions elicited consistently higher neural responses and decoding performance in all regions. A significant decrease in both activation and decoding accuracy due to the absence of eye-related information was also observed. Overall, the findings showed that emotional expressions are represented in motion-sensitive areas in addition to conventional face-selective areas, suggesting that motion-sensitive regions may also effectively contribute to facial expression recognition. The results also suggested that facial motion and eye-related information played important roles by carrying considerable expression information that could facilitate facial expression recognition. Hum Brain Mapp 38:3113-3125, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  12. Perioperative antibiotic usage by facial plastic surgeons: national survey results and comparison with evidence-based guidelines.

    Science.gov (United States)

    Grunebaum, Lisa Danielle; Reiter, David

    2006-01-01

    To determine current practice for use of perioperative antibiotics among facial plastic surgeons, to determine the extent of use of literature support for preferences of facial plastic surgeons, and to compare patterns of use with nationally supported evidence-based guidelines. A link to a Web site containing a questionnaire on perioperative antibiotic use was e-mailed to more than 1000 facial plastic surgeons in the United States. Responses were archived in a dedicated database and analyzed to determine patterns of use and methods of documenting that use. Current literature was used to develop evidence-based recommendations for perioperative antibiotic use, emphasizing current nationally supported guidelines. Preferences varied significantly for medication used, dosage and regimen, time of first dose relative to incision time, setting in which medication was administered, and procedures for which perioperative antibiotic was deemed necessary. Surgical site infection in facial plastic surgery can be reduced by better conformance to currently available evidence-based guidelines. We offer specific recommendations that are supported by the current literature.

  13. Graphical matching rules for cardinality based service feature diagrams

    Directory of Open Access Journals (Sweden)

    Faiza Kanwal

    2017-03-01

    Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.

  14. Histological image classification using biologically interpretable shape-based features

    International Nuclear Information System (INIS)

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  15. Facial trauma

    Science.gov (United States)

    Maxillofacial injury; Midface trauma; Facial injury; LeFort injuries ... Hockberger RS, Walls RM, eds. Rosen's Emergency Medicine: Concepts and Clinical Practice . 8th ed. Philadelphia, PA: Elsevier ...

  16. Fashion Evaluation Method for Clothing Recommendation Based on Weak Appearance Feature

    Directory of Open Access Journals (Sweden)

    Yan Zhang

    2017-01-01

    Full Text Available With the rapid rising of living standard, people gradually developed higher shopping enthusiasm and increasing demand for garment. Nowadays, an increasing number of people pursue fashion. However, facing too many types of garment, consumers need to try them on repeatedly, which is somewhat time- and energy-consuming. Besides, it is difficult for merchants to master the real-time demand of consumers. Herein, there is not enough cohesiveness between consumer information and merchants. Thus, a novel fashion evaluation method on the basis of the appearance weak feature is proposed in this paper. First of all, image database is established and three aspects of appearance weak feature are put forward to characterize the fashion level. Furthermore, the appearance weak features are extracted according to the characters’ facial feature localization method. Last but not least, consumers’ fashion level can be classified through support vector product, and the classification is verified with the hierarchical analysis method. The experimental results show that consumers’ fashion level can be accurately described based on the indexes of appearance weak feature and the approach has higher application value for the clothing recommendation system.

  17. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    Directory of Open Access Journals (Sweden)

    Rouzé Pierre

    2004-05-01

    Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

  18. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  19. Features and Characteristics of Problem Based Learning

    Science.gov (United States)

    Ceker, Eser; Ozdamli, Fezile

    2016-01-01

    Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements) of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look…

  20. Cognitive penetrability and emotion recognition in human facial expressions

    Directory of Open Access Journals (Sweden)

    Francesco eMarchi

    2015-06-01

    Full Text Available Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on cognitive penetration, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept cognitive penetration in some cases of emotion recognition. Finally, we highlight a recent model of social vision in order to propose a mechanism for cognitive penetration used in the face-based recognition of emotion.

  1. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  2. Features and characteristics of problem based learning

    Directory of Open Access Journals (Sweden)

    Eser Ceker

    2016-12-01

    Full Text Available Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look for the latest technology supported tools of Problem Based Learning. This research showed that the most researched characteristics of PBL are; teacher and student assessments on Problem Based Learning, Variety of disciplines in which Problem Based Learning strategies were tried and success evaluated, Using Problem Based Learning alone or with other strategies (Hybrid or Mix methods, Comparing Problem Based Learning with other strategies, and new trends and tendencies in Problem Based Learning related research. Our research may help us to identify the latest trends and tendencies referred to in the published studies related to “problem based learning” areas. In this research, Science Direct and Ulakbim were used as our main database resources. The sample of this study consists of 150 articles.

  3. Lack of support for the association between facial shape and aggression: a reappraisal based on a worldwide population genetics perspective.

    Directory of Open Access Journals (Sweden)

    Jorge Gómez-Valdés

    Full Text Available Antisocial and criminal behaviors are multifactorial traits whose interpretation relies on multiple disciplines. Since these interpretations may have social, moral and legal implications, a constant review of the evidence is necessary before any scientific claim is considered as truth. A recent study proposed that men with wider faces relative to facial height (fWHR are more likely to develop unethical behaviour mediated by a psychological sense of power. This research was based on reports suggesting that sexual dimorphism and selection would be responsible for a correlation between fWHR and aggression. Here we show that 4,960 individuals from 94 modern human populations belonging to a vast array of genetic and cultural contexts do not display significant amounts of fWHR sexual dimorphism. Further analyses using populations with associated ethnographical records as well as samples of male prisoners of the Mexico City Federal Penitentiary condemned by crimes of variable level of inter-personal aggression (homicide, robbery, and minor faults did not show significant evidence, suggesting that populations/individuals with higher levels of bellicosity, aggressive behaviour, or power-mediated behaviour display greater fWHR. Finally, a regression analysis of fWHR on individual's fitness showed no significant correlation between this facial trait and reproductive success. Overall, our results suggest that facial attributes are poor predictors of aggressive behaviour, or at least, that sexual selection was weak enough to leave a signal on patterns of between- and within-sex and population facial variation.

  4. Recognizing Facial Slivers.

    Science.gov (United States)

    Gilad-Gutnick, Sharon; Harmatz, Elia Samuel; Tsourides, Kleovoulos; Yovel, Galit; Sinha, Pawan

    2018-07-01

    We report here an unexpectedly robust ability of healthy human individuals ( n = 40) to recognize extremely distorted needle-like facial images, challenging the well-entrenched notion that veridical spatial configuration is necessary for extracting facial identity. In face identification tasks of parametrically compressed internal and external features, we found that the sum of performances on each cue falls significantly short of performance on full faces, despite the equal visual information available from both measures (with full faces essentially being a superposition of internal and external features). We hypothesize that this large deficit stems from the use of positional information about how the internal features are positioned relative to the external features. To test this, we systematically changed the relations between internal and external features and found preferential encoding of vertical but not horizontal spatial relationships in facial representations ( n = 20). Finally, we employ magnetoencephalography imaging ( n = 20) to demonstrate a close mapping between the behavioral psychometric curve and the amplitude of the M250 face familiarity, but not M170 face-sensitive evoked response field component, providing evidence that the M250 can be modulated by faces that are perceptually identifiable, irrespective of extreme distortions to the face's veridical configuration. We theorize that the tolerance to compressive distortions has evolved from the need to recognize faces across varying viewpoints. Our findings help clarify the important, but poorly defined, concept of facial configuration and also enable an association between behavioral performance and previously reported neural correlates of face perception.

  5. Facial Expression Recognition via Non-Negative Least-Squares Sparse Coding

    Directory of Open Access Journals (Sweden)

    Ying Chen

    2014-05-01

    Full Text Available Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of facial expression recognition via non-negative least squares (NNLS sparse coding is presented in this paper. The NNLS sparse coding is used to form a facial expression classifier. To testify the performance of the presented method, local binary patterns (LBP and the raw pixels are extracted for facial feature representation. Facial expression recognition experiments are conducted on the Japanese Female Facial Expression (JAFFE database. Compared with other widely used methods such as linear support vector machines (SVM, sparse representation-based classifier (SRC, nearest subspace classifier (NSC, K-nearest neighbor (KNN and radial basis function neural networks (RBFNN, the experiment results indicate that the presented NNLS method performs better than other used methods on facial expression recognition tasks.

  6. 3D facial expression recognition based on histograms of surface differential quantities

    KAUST Repository

    Li, Huibin; Morvan, Jean-Marie; Chen, Liming

    2011-01-01

    . To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle

  7. Cosmetics Alter Biologically-Based Factors of Beauty: Evidence from Facial Contrast

    Directory of Open Access Journals (Sweden)

    Alex L. Jones

    2015-01-01

    Full Text Available The use of cosmetics by women seems to consistently increase their attractiveness. What factors of attractiveness do cosmetics alter to achieve this? Facial contrast is a known cue to sexual dimorphism and youth, and cosmetics exaggerate sexual dimorphisms in facial contrast. Here, we demonstrate that the luminance contrast pattern of the eyes and eyebrows is consistently sexually dimorphic across a large sample of faces, with females possessing lower brow contrasts than males, and greater eye contrast than males. Red-green and yellow-blue color contrasts were not found to differ consistently between the sexes. We also show that women use cosmetics not only to exaggerate sexual dimorphisms of brow and eye contrasts, but also to increase contrasts that decline with age. These findings refine the notion of facial contrast, and demonstrate how cosmetics can increase attractiveness by manipulating factors of beauty associated with facial contrast.

  8. Cosmetics alter biologically-based factors of beauty: evidence from facial contrast.

    Science.gov (United States)

    Jones, Alex L; Russell, Richard; Ward, Robert

    2015-02-28

    The use of cosmetics by women seems to consistently increase their attractiveness. What factors of attractiveness do cosmetics alter to achieve this? Facial contrast is a known cue to sexual dimorphism and youth, and cosmetics exaggerate sexual dimorphisms in facial contrast. Here, we demonstrate that the luminance contrast pattern of the eyes and eyebrows is consistently sexually dimorphic across a large sample of faces, with females possessing lower brow contrasts than males, and greater eye contrast than males. Red-green and yellow-blue color contrasts were not found to differ consistently between the sexes. We also show that women use cosmetics not only to exaggerate sexual dimorphisms of brow and eye contrasts, but also to increase contrasts that decline with age. These findings refine the notion of facial contrast, and demonstrate how cosmetics can increase attractiveness by manipulating factors of beauty associated with facial contrast.

  9. A Web-based Game for Teaching Facial Expressions to Schizophrenic Patients.

    Science.gov (United States)

    Gülkesen, Kemal Hakan; Isleyen, Filiz; Cinemre, Buket; Samur, Mehmet Kemal; Sen Kaya, Semiha; Zayim, Nese

    2017-07-12

    Recognizing facial expressions is an important social skill. In some psychological disorders such as schizophrenia, loss of this skill may complicate the patient's daily life. Prior research has shown that information technology may help to develop facial expression recognition skills through educational software and games. To examine if a computer game designed for teaching facial expressions would improve facial expression recognition skills of patients with schizophrenia. We developed a website composed of eight serious games. Thirty-two patients were given a pre-test composed of 21 facial expression photographs. Eighteen patients were in the study group while 14 were in the control group. Patients in the study group were asked to play the games on the website. After a period of one month, we performed a post-test for all patients. The median score of the correct answers was 17.5 in the control group whereas it was 16.5 in the study group (of 21) in pretest. The median post-test score was 18 in the control group (p=0.052) whereas it was 20 in the study group (pgames may be used for the purpose of educating people who have difficulty in recognizing facial expressions.

  10. Genetics Home Reference: oral-facial-digital syndrome

    Science.gov (United States)

    ... related conditions that affect the development of the oral cavity (the mouth and teeth), facial features, and digits ( ... this disorder involve problems with development of the oral cavity , facial features, and digits. Most forms are also ...

  11. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    Hongguang Li

    2018-01-01

    Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

  12. Classical Music Clustering Based on Acoustic Features

    OpenAIRE

    Wang, Xindi; Haque, Syed Arefinul

    2017-01-01

    In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and performed spectral clustering to find the clusters. Based on different resolution, the output clusters distinctively indicate composition from different classical music era and different composing style of the musicians.

  13. Facial Fractures.

    Science.gov (United States)

    Ricketts, Sophie; Gill, Hameet S; Fialkov, Jeffery A; Matic, Damir B; Antonyshyn, Oleh M

    2016-02-01

    After reading this article, the participant should be able to: 1. Demonstrate an understanding of some of the changes in aspects of facial fracture management. 2. Assess a patient presenting with facial fractures. 3. Understand indications and timing of surgery. 4. Recognize exposures of the craniomaxillofacial skeleton. 5. Identify methods for repair of typical facial fracture patterns. 6. Discuss the common complications seen with facial fractures. Restoration of the facial skeleton and associated soft tissues after trauma involves accurate clinical and radiologic assessment to effectively plan a management approach for these injuries. When surgical intervention is necessary, timing, exposure, sequencing, and execution of repair are all integral to achieving the best long-term outcomes for these patients.

  14. Statistical feature extraction based iris recognition system

    Indian Academy of Sciences (India)

    Atul Bansal

    1 Department of Electronics and Communication, G.L.A. University, 17-km stone, NH#2, Delhi-Mathura Road, .... Based upon these range of values, a decision is taken about the ...... triplet half-band filter bank and flexible k-out-of-n: A post.

  15. Automated Analysis of Facial Cues from Videos as a Potential Method for Differentiating Stress and Boredom of Players in Games

    Directory of Open Access Journals (Sweden)

    Fernando Bevilacqua

    2018-01-01

    Full Text Available Facial analysis is a promising approach to detect emotions of players unobtrusively; however approaches are commonly evaluated in contexts not related to games or facial cues are derived from models not designed for analysis of emotions during interactions with games. We present a method for automated analysis of facial cues from videos as a potential tool for detecting stress and boredom of players behaving naturally while playing games. Computer vision is used to automatically and unobtrusively extract 7 facial features aimed at detecting the activity of a set of facial muscles. Features are mainly based on the Euclidean distance of facial landmarks and do not rely on predefined facial expressions, training of a model, or the use of facial standards. An empirical evaluation was conducted on video recordings of an experiment involving games as emotion elicitation sources. Results show statistically significant differences in the values of facial features during boring and stressful periods of gameplay for 5 of the 7 features. We believe our approach is more user-tailored, convenient, and better suited for contexts involving games.

  16. Individual discriminative face recognition models based on subsets of features

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

    2007-01-01

    The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

  17. Level Sets and Voronoi based Feature Extraction from any Imagery

    DEFF Research Database (Denmark)

    Sharma, O.; Anton, François; Mioc, Darka

    2012-01-01

    Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voron...

  18. Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

    Science.gov (United States)

    Li, Baopu; Meng, Max Q-H

    2012-05-01

    Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

  19. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

    Science.gov (United States)

    Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

    2016-01-01

    An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

  20. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

    Directory of Open Access Journals (Sweden)

    Seyed Mostafa Mousavi Kahaki

    Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

  1. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2012-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions

  2. Automatic Facial Expression Recognition and Operator Functional State

    Science.gov (United States)

    Blanson, Nina

    2011-01-01

    The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

  3. Multifunctional optical security features based on bacteriorhodopsin

    Science.gov (United States)

    Hampp, Norbert A.; Neebe, Martin; Juchem, Thorsten; Wolperdinger, Markus; Geiger, Markus; Schmuck, Arno

    2004-06-01

    Bacteriorhodopsin (BR), a photochromic retinal protein, has been developed into a new materials platform for applications in anti-counterfeiting. The combination of three different properties of the material on its molecular level, a light-inducible color change, photochemical data storage and traceability of the protein due to molecular marker sequences make this protein a promising material for security applications. The crystalline structure of the biopigment combines these properties with high stability. As BR is a biological material specialized knowledge for modification, cost- effective production and suitable processing of the material is required. Photochromic BR-based inks have been developed for screen printing, pad printing and ink jet printing. These prints show a high photochromic sensitivity towards variation of illumination. For this reason it is not possible to reproduce the dynamic color by photocopying. In addition to such visual inspection the printed symbols offer the possibility for digital write-once-read-many (WORM) data storage. Photochemical recording is accomplished by a two-photon process. Recording densities in a range from 106 bit/cm2 to 108 bit/cm2 have been achieved. Data structures are stored in a polarization sensitive mode which allows an easy and efficient data encryption.

  4. Estimation of human emotions using thermal facial information

    Science.gov (United States)

    Nguyen, Hung; Kotani, Kazunori; Chen, Fan; Le, Bac

    2014-01-01

    In recent years, research on human emotion estimation using thermal infrared (IR) imagery has appealed to many researchers due to its invariance to visible illumination changes. Although infrared imagery is superior to visible imagery in its invariance to illumination changes and appearance differences, it has difficulties in handling transparent glasses in the thermal infrared spectrum. As a result, when using infrared imagery for the analysis of human facial information, the regions of eyeglasses are dark and eyes' thermal information is not given. We propose a temperature space method to correct eyeglasses' effect using the thermal facial information in the neighboring facial regions, and then use Principal Component Analysis (PCA), Eigen-space Method based on class-features (EMC), and PCA-EMC method to classify human emotions from the corrected thermal images. We collected the Kotani Thermal Facial Emotion (KTFE) database and performed the experiments, which show the improved accuracy rate in estimating human emotions.

  5. Association of stress and depression with chronic facial pain: A case-control study based on the Northern Finland 1966 Birth Cohort.

    Science.gov (United States)

    Nevalainen, Netta; Lähdesmäki, Raija; Mäki, Pirjo; Ek, Ellen; Taanila, Anja; Pesonen, Paula; Sipilä, Kirsi

    2017-05-01

    The aim was to study the association between stress level and chronic facial pain, while controlling for the effect of depression on this association, during a three-year follow-up in a general population-based birth cohort. In the general population-based Northern Finland 1966 Birth Cohort, information about stress level, depression and facial pain were collected using questionnaires at the age of 31 years. Stress level was measured using the Work Ability Index. Depression was assessed using the 13-item depression subscale in the Hopkins Symptom Checklist-25. Three years later, a subsample of 52 subjects (42 women) with chronic facial pain and 52 pain-free controls (42 women) was formed. Of the subjects having high stress level at baseline, 73.3% had chronic facial pain, and 26.7% were pain-free three years later. The univariate logistic regression analysis showed that high stress level at 31 years increased the risk for chronic facial pain (crude OR 6.1, 95%, CI 1.3-28.7) three years later. When including depression in a multivariate model, depression associated statistically significantly with chronic facial pain (adjusted OR 2.5, 95%, CI 1.0-5.8), whereas stress level did not (adjusted OR 2.3, 95%, CI 0.6-8.4). High stress level is connected with increased risk for chronic facial pain. This association seems to mediate through depression.

  6. A Real-Time Interactive System for Facial Makeup of Peking Opera

    Science.gov (United States)

    Cai, Feilong; Yu, Jinhui

    In this paper we present a real-time interactive system for making facial makeup of Peking Opera. First, we analyze the process of drawing facial makeup and characteristics of the patterns used in it, and then construct a SVG pattern bank based on local features like eye, nose, mouth, etc. Next, we pick up some SVG patterns from the pattern bank and composed them to make a new facial makeup. We offer a vector-based free form deformation (FFD) tool to edit patterns and, based on editing, our system creates automatically texture maps for a template head model. Finally, the facial makeup is rendered on the 3D head model in real time. Our system offers flexibility in designing and synthesizing various 3D facial makeup. Potential applications of the system include decoration design, digital museum exhibition and education of Peking Opera.

  7. Perceived Sexual Orientation Based on Vocal and Facial Stimuli Is Linked to Self-Rated Sexual Orientation in Czech Men

    Science.gov (United States)

    Valentova, Jaroslava Varella; Havlíček, Jan

    2013-01-01

    Previous research has shown that lay people can accurately assess male sexual orientation based on limited information, such as face, voice, or behavioral display. Gender-atypical traits are thought to serve as cues to sexual orientation. We investigated the presumed mechanisms of sexual orientation attribution using a standardized set of facial and vocal stimuli of Czech men. Both types of stimuli were rated for sexual orientation and masculinity-femininity by non-student heterosexual women and homosexual men. Our data showed that by evaluating vocal stimuli both women and homosexual men can judge sexual orientation of the target men in agreement with their self-reported sexual orientation. Nevertheless, only homosexual men accurately attributed sexual orientation of the two groups from facial images. Interestingly, facial images of homosexual targets were rated as more masculine than heterosexual targets. This indicates that attributions of sexual orientation are affected by stereotyped association between femininity and male homosexuality; however, reliance on such cues can lead to frequent misjudgments as was the case with the female raters. Although our study is based on a community sample recruited in a non-English speaking country, the results are generally consistent with the previous research and thus corroborate the validity of sexual orientation attributions. PMID:24358180

  8. Perceived sexual orientation based on vocal and facial stimuli is linked to self-rated sexual orientation in Czech men.

    Directory of Open Access Journals (Sweden)

    Jaroslava Varella Valentova

    Full Text Available Previous research has shown that lay people can accurately assess male sexual orientation based on limited information, such as face, voice, or behavioral display. Gender-atypical traits are thought to serve as cues to sexual orientation. We investigated the presumed mechanisms of sexual orientation attribution using a standardized set of facial and vocal stimuli of Czech men. Both types of stimuli were rated for sexual orientation and masculinity-femininity by non-student heterosexual women and homosexual men. Our data showed that by evaluating vocal stimuli both women and homosexual men can judge sexual orientation of the target men in agreement with their self-reported sexual orientation. Nevertheless, only homosexual men accurately attributed sexual orientation of the two groups from facial images. Interestingly, facial images of homosexual targets were rated as more masculine than heterosexual targets. This indicates that attributions of sexual orientation are affected by stereotyped association between femininity and male homosexuality; however, reliance on such cues can lead to frequent misjudgments as was the case with the female raters. Although our study is based on a community sample recruited in a non-English speaking country, the results are generally consistent with the previous research and thus corroborate the validity of sexual orientation attributions.

  9. Readability assessment of internet-based patient education materials related to facial fractures.

    Science.gov (United States)

    Sanghvi, Saurin; Cherla, Deepa V; Shukla, Pratik A; Eloy, Jean Anderson

    2012-09-01

    Various professional societies, clinical practices, hospitals, and health care-related Web sites provide Internet-based patient education material (IPEMs) to the general public. However, this information may be written above the 6th-grade reading level recommended by the US Department of Health and Human Services. The purpose of this study is to assess the readability of facial fracture (FF)-related IPEMs and compare readability levels of IPEMs provided by four sources: professional societies, clinical practices, hospitals, and miscellaneous sources. Analysis of IPEMs on FFs available on Google.com. The readability of 41 FF-related IPEMs was assessed with four readability indices: Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (Gunning FOG). Averages were evaluated against national recommendations and between each source using analysis of variance and t tests. Only 4.9% of IPEMs were written at or below the 6th-grade reading level, based on FKGL. The mean readability scores were: FRES 54.10, FKGL 9.89, SMOG 12.73, and Gunning FOG 12.98, translating into FF-related IPEMs being written at a "difficult" writing level, which is above the level of reading understanding of the average American adult. IPEMs related to FFs are written above the recommended 6th-grade reading level. Consequently, this information would be difficult to understand by the average US patient. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

  10. Facial Fractures.

    Science.gov (United States)

    Ghosh, Rajarshi; Gopalkrishnan, Kulandaswamy

    2018-06-01

    The aim of this study is to retrospectively analyze the incidence of facial fractures along with age, gender predilection, etiology, commonest site, associated dental injuries, and any complications of patients operated in Craniofacial Unit of SDM College of Dental Sciences and Hospital. This retrospective study was conducted at the Department of OMFS, SDM College of Dental Sciences, Dharwad from January 2003 to December 2013. Data were recorded for the cause of injury, age and gender distribution, frequency and type of injury, localization and frequency of soft tissue injuries, dentoalveolar trauma, facial bone fractures, complications, concomitant injuries, and different treatment protocols.All the data were analyzed using statistical analysis that is chi-squared test. A total of 1146 patients reported at our unit with facial fractures during these 10 years. Males accounted for a higher frequency of facial fractures (88.8%). Mandible was the commonest bone to be fractured among all the facial bones (71.2%). Maxillary central incisors were the most common teeth to be injured (33.8%) and avulsion was the most common type of injury (44.6%). Commonest postoperative complication was plate infection (11%) leading to plate removal. Other injuries associated with facial fractures were rib fractures, head injuries, upper and lower limb fractures, etc., among these rib fractures were seen most frequently (21.6%). This study was performed to compare the different etiologic factors leading to diverse facial fracture patterns. By statistical analysis of this record the authors come to know about the relationship of facial fractures with gender, age, associated comorbidities, etc.

  11. Analysing co-articulation using frame-based feature trajectories

    CSIR Research Space (South Africa)

    Badenhorst, J

    2010-11-01

    Full Text Available The authors investigate several approaches aimed at a more detailed understanding of co-articulation in spoken utterances. They find that the Euclidean difference between instantaneous frame-based feature values and the mean values of these features...

  12. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  13. Effect of Feature Dimensionality on Object-based Land Cover ...

    African Journals Online (AJOL)

    Geographic object-based image analysis (GEOBIA) allows the easy integration of such additional features into the classification process. This paper compares the performance of three supervised classifiers in a GEOBIA environment as an increasing number of object features are included as classification input.

  14. Image feature extraction based on the camouflage effectiveness evaluation

    Science.gov (United States)

    Yuan, Xin; Lv, Xuliang; Li, Ling; Wang, Xinzhu; Zhang, Zhi

    2018-04-01

    The key step of camouflage effectiveness evaluation is how to combine the human visual physiological features, psychological features to select effectively evaluation indexes. Based on the predecessors' camo comprehensive evaluation method, this paper chooses the suitable indexes combining with the image quality awareness, and optimizes those indexes combining with human subjective perception. Thus, it perfects the theory of index extraction.

  15. Quantitative Comparison of Tolerance-Based Feature Transforms

    NARCIS (Netherlands)

    Reniers, Dennie; Telea, Alexandru

    2006-01-01

    Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary

  16. A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans

    Science.gov (United States)

    Liu, Fan; van der Lijn, Fedde; Schurmann, Claudia; Zhu, Gu; Chakravarty, M. Mallar; Hysi, Pirro G.; Wollstein, Andreas; Lao, Oscar; de Bruijne, Marleen; Ikram, M. Arfan; van der Lugt, Aad; Rivadeneira, Fernando; Uitterlinden, André G.; Hofman, Albert; Niessen, Wiro J.; Homuth, Georg; de Zubicaray, Greig; McMahon, Katie L.; Thompson, Paul M.; Daboul, Amro; Puls, Ralf; Hegenscheid, Katrin; Bevan, Liisa; Pausova, Zdenka; Medland, Sarah E.; Montgomery, Grant W.; Wright, Margaret J.; Wicking, Carol; Boehringer, Stefan; Spector, Timothy D.; Paus, Tomáš; Martin, Nicholas G.; Biffar, Reiner; Kayser, Manfred

    2012-01-01

    Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes—PRDM16, PAX3, TP63, C5orf50, and COL17A1—in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications. PMID:23028347

  17. A genome-wide association study identifies five loci influencing facial morphology in Europeans.

    Directory of Open Access Journals (Sweden)

    Fan Liu

    2012-09-01

    Full Text Available Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

  18. Finger vein recognition based on the hyperinformation feature

    Science.gov (United States)

    Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

    2014-01-01

    The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

  19. Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

    Science.gov (United States)

    Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

    2015-12-01

    Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

  20. Heartbeat Signal from Facial Video for Biometric Recognition

    DEFF Research Database (Denmark)

    Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

    2015-01-01

    Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate......, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time...... to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised...

  1. [Establishment of the database of the 3D facial models for the plastic surgery based on network].

    Science.gov (United States)

    Liu, Zhe; Zhang, Hai-Lin; Zhang, Zheng-Guo; Qiao, Qun

    2008-07-01

    To collect the three-dimensional (3D) facial data of 30 facial deformity patients by the 3D scanner and establish a professional database based on Internet. It can be helpful for the clinical intervention. The primitive point data of face topography were collected by the 3D scanner. Then the 3D point cloud was edited by reverse engineering software to reconstruct the 3D model of the face. The database system was divided into three parts, including basic information, disease information and surgery information. The programming language of the web system is Java. The linkages between every table of the database are credibility. The query operation and the data mining are convenient. The users can visit the database via the Internet and use the image analysis system to observe the 3D facial models interactively. In this paper we presented a database and a web system adapt to the plastic surgery of human face. It can be used both in clinic and in basic research.

  2. Face puzzle—two new video-based tasks for measuring explicit and implicit aspects of facial emotion recognition

    Science.gov (United States)

    Kliemann, Dorit; Rosenblau, Gabriela; Bölte, Sven; Heekeren, Hauke R.; Dziobek, Isabel

    2013-01-01

    Recognizing others' emotional states is crucial for effective social interaction. While most facial emotion recognition tasks use explicit prompts that trigger consciously controlled processing, emotional faces are almost exclusively processed implicitly in real life. Recent attempts in social cognition suggest a dual process perspective, whereby explicit and implicit processes largely operate independently. However, due to differences in methodology the direct comparison of implicit and explicit social cognition has remained a challenge. Here, we introduce a new tool to comparably measure implicit and explicit processing aspects comprising basic and complex emotions in facial expressions. We developed two video-based tasks with similar answer formats to assess performance in respective facial emotion recognition processes: Face Puzzle, implicit and explicit. To assess the tasks' sensitivity to atypical social cognition and to infer interrelationship patterns between explicit and implicit processes in typical and atypical development, we included healthy adults (NT, n = 24) and adults with autism spectrum disorder (ASD, n = 24). Item analyses yielded good reliability of the new tasks. Group-specific results indicated sensitivity to subtle social impairments in high-functioning ASD. Correlation analyses with established implicit and explicit socio-cognitive measures were further in favor of the tasks' external validity. Between group comparisons provide first hints of differential relations between implicit and explicit aspects of facial emotion recognition processes in healthy compared to ASD participants. In addition, an increased magnitude of between group differences in the implicit task was found for a speed-accuracy composite measure. The new Face Puzzle tool thus provides two new tasks to separately assess explicit and implicit social functioning, for instance, to measure subtle impairments as well as potential improvements due to social cognitive

  3. An Effective Combined Feature For Web Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    H.M.R.B Herath

    2015-08-01

    Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

  4. Feature selection gait-based gender classification under different circumstances

    Science.gov (United States)

    Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

    2014-05-01

    This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

  5. Feature-based Ontology Mapping from an Information Receivers’ Viewpoint

    DEFF Research Database (Denmark)

    Glückstad, Fumiko Kano; Mørup, Morten

    2012-01-01

    This paper compares four algorithms for computing feature-based similarities between concepts respectively possessing a distinctive set of features. The eventual purpose of comparing these feature-based similarity algorithms is to identify a candidate term in a Target Language (TL) that can...... optimally convey the original meaning of a culturally-specific Source Language (SL) concept to a TL audience by aligning two culturally-dependent domain-specific ontologies. The results indicate that the Bayesian Model of Generalization [1] performs best, not only for identifying candidate translation terms...

  6. Remembering facial configurations.

    Science.gov (United States)

    Bruce, V; Doyle, T; Dench, N; Burton, M

    1991-02-01

    Eight experiments are reported showing that subjects can remember rather subtle aspects of the configuration of facial features to which they have earlier been exposed. Subjects saw several slightly different configurations (formed by altering the relative placement of internal features of the face) of each of ten different faces, and they were asked to rate the apparent age and masculinity-femininity of each. Afterwards, subjects were asked to select from pairs of faces the configuration which was identical to one previously rated. Subjects responded strongly to the central or "prototypical" configuration of each studied face where this was included as one member of each test pair, whether or not it had been studied (Experiments 1, 2 and 4). Subjects were also quite accurate at recognizing one of the previously encountered extremes of the series of configurations that had been rated (Experiment 3), but when unseen prototypes were paired with seen exemplars subjects' performance was at chance (Experiment 5). Prototype learning of face patterns was shown to be stronger than that for house patterns, though both classes of patterns were affected equally by inversion (Experiment 6). The final two experiments demonstrated that preferences for the prototype could be affected by instructions at study and by whether different exemplars of the same face were shown consecutively or distributed through the study series. The discussion examines the implications of these results for theories of the representation of faces and for instance-based models of memory.

  7. Automatic feature-based grouping during multiple object tracking.

    Science.gov (United States)

    Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

    2013-12-01

    Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

  8. FaceWarehouse: a 3D facial expression database for visual computing.

    Science.gov (United States)

    Cao, Chen; Weng, Yanlin; Zhou, Shun; Tong, Yiying; Zhou, Kun

    2014-03-01

    We present FaceWarehouse, a database of 3D facial expressions for visual computing applications. We use Kinect, an off-the-shelf RGBD camera, to capture 150 individuals aged 7-80 from various ethnic backgrounds. For each person, we captured the RGBD data of her different expressions, including the neutral expression and 19 other expressions such as mouth-opening, smile, kiss, etc. For every RGBD raw data record, a set of facial feature points on the color image such as eye corners, mouth contour, and the nose tip are automatically localized, and manually adjusted if better accuracy is required. We then deform a template facial mesh to fit the depth data as closely as possible while matching the feature points on the color image to their corresponding points on the mesh. Starting from these fitted face meshes, we construct a set of individual-specific expression blendshapes for each person. These meshes with consistent topology are assembled as a rank-3 tensor to build a bilinear face model with two attributes: identity and expression. Compared with previous 3D facial databases, for every person in our database, there is a much richer matching collection of expressions, enabling depiction of most human facial actions. We demonstrate the potential of FaceWarehouse for visual computing with four applications: facial image manipulation, face component transfer, real-time performance-based facial image animation, and facial animation retargeting from video to image.

  9. Análisis comparativo de descriptores de forma 3D para detección de características faciales / Comparative analysis of 3D shape descriptors for facial feature detection

    OpenAIRE

    Cerón Correa, Alexander

    2011-01-01

    El rostro humano presenta una gran cantidad de características que actualmente pueden ser modeladas mediante un simple patrón 2D, un conjunto complejo de vértices 3D que forman una malla poligonal o un conjunto de par�ametros para cada grado de libertad o variación. La caracterización del rostro tiene gran cantidad de aplicaciones dentro de las cuales se tienen: identificación de rostros, modelado de la cara, síntesis de voz, identificación de expresiones y cirugía facial. Los modelos t...

  10. Facial Sports Injuries

    Science.gov (United States)

    ... Marketplace Find an ENT Doctor Near You Facial Sports Injuries Facial Sports Injuries Patient Health Information News ... should receive immediate medical attention. Prevention Of Facial Sports Injuries The best way to treat facial sports ...

  11. Facial Cosmetic Surgery

    Science.gov (United States)

    ... to find out more. Facial Cosmetic Surgery Facial Cosmetic Surgery Extensive education and training in surgical procedures ... to find out more. Facial Cosmetic Surgery Facial Cosmetic Surgery Extensive education and training in surgical procedures ...

  12. Spatiotemporal Features for Asynchronous Event-based Data

    Directory of Open Access Journals (Sweden)

    Xavier eLagorce

    2015-02-01

    Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

  13. Facial trauma.

    Science.gov (United States)

    Peeters, N; Lemkens, P; Leach, R; Gemels B; Schepers, S; Lemmens, W

    Facial trauma. Patients with facial trauma must be assessed in a systematic way so as to avoid missing any injury. Severe and disfiguring facial injuries can be distracting. However, clinicians must first focus on the basics of trauma care, following the Advanced Trauma Life Support (ATLS) system of care. Maxillofacial trauma occurs in a significant number of severely injured patients. Life- and sight-threatening injuries must be excluded during the primary and secondary surveys. Special attention must be paid to sight-threatening injuries in stabilized patients through early referral to an appropriate specialist or the early initiation of emergency care treatment. The gold standard for the radiographic evaluation of facial injuries is computed tomography (CT) imaging. Nasal fractures are the most frequent isolated facial fractures. Isolated nasal fractures are principally diagnosed through history and clinical examination. Closed reduction is the most frequently performed treatment for isolated nasal fractures, with a fractured nasal septum as a predictor of failure. Ear, nose and throat surgeons, maxillofacial surgeons and ophthalmologists must all develop an adequate treatment plan for patients with complex maxillofacial trauma.

  14. Collaborative Filtering Fusing Label Features Based on SDAE

    DEFF Research Database (Denmark)

    Huo, Huan; Liu, Xiufeng; Zheng, Deyuan

    2017-01-01

    problem, auxiliary information such as labels are utilized. Another approach of recommendation system is content-based model which can’t be directly integrated with CF-based model due to its inherent characteristics. Considering that deep learning algorithms are capable of extracting deep latent features......, this paper applies Stack Denoising Auto Encoder (SDAE) to content-based model and proposes LCF(Deep Learning for Collaborative Filtering) algorithm by combing CF-based model which fuses label features. Experiments on real-world data sets show that DLCF can largely overcome the sparsity problem...... and significantly improves the state of art approaches....

  15. SVM-based glioma grading. Optimization by feature reduction analysis

    International Nuclear Information System (INIS)

    Zoellner, Frank G.; Schad, Lothar R.; Emblem, Kyrre E.; Harvard Medical School, Boston, MA; Oslo Univ. Hospital

    2012-01-01

    We investigated the predictive power of feature reduction analysis approaches in support vector machine (SVM)-based classification of glioma grade. In 101 untreated glioma patients, three analytic approaches were evaluated to derive an optimal reduction in features; (i) Pearson's correlation coefficients (PCC), (ii) principal component analysis (PCA) and (iii) independent component analysis (ICA). Tumor grading was performed using a previously reported SVM approach including whole-tumor cerebral blood volume (CBV) histograms and patient age. Best classification accuracy was found using PCA at 85% (sensitivity = 89%, specificity = 84%) when reducing the feature vector from 101 (100-bins rCBV histogram + age) to 3 principal components. In comparison, classification accuracy by PCC was 82% (89%, 77%, 2 dimensions) and 79% by ICA (87%, 75%, 9 dimensions). For improved speed (up to 30%) and simplicity, feature reduction by all three methods provided similar classification accuracy to literature values (∝87%) while reducing the number of features by up to 98%. (orig.)

  16. RESEARCH ON FOREST FLAME RECOGNITION ALGORITHM BASED ON IMAGE FEATURE

    Directory of Open Access Journals (Sweden)

    Z. Wang

    2017-09-01

    Full Text Available In recent years, fire recognition based on image features has become a hotspot in fire monitoring. However, due to the complexity of forest environment, the accuracy of forest fireworks recognition based on image features is low. Based on this, this paper proposes a feature extraction algorithm based on YCrCb color space and K-means clustering. Firstly, the paper prepares and analyzes the color characteristics of a large number of forest fire image samples. Using the K-means clustering algorithm, the forest flame model is obtained by comparing the two commonly used color spaces, and the suspected flame area is discriminated and extracted. The experimental results show that the extraction accuracy of flame area based on YCrCb color model is higher than that of HSI color model, which can be applied in different scene forest fire identification, and it is feasible in practice.

  17. Feature-based tolerancing for intelligent inspection process definition

    International Nuclear Information System (INIS)

    Brown, C.W.

    1993-07-01

    This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

  18. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  19. 3-D FEATURE-BASED MATCHING BY RSTG APPROACH

    Directory of Open Access Journals (Sweden)

    J.-J. Jaw

    2012-07-01

    Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.

  20. Parametric classification of handvein patterns based on texture features

    Science.gov (United States)

    Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

    2018-04-01

    In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

  1. Rejuvenecimiento facial

    Directory of Open Access Journals (Sweden)

    L. Daniel Jacubovsky, Dr.

    2010-01-01

    Full Text Available El envejecimiento facial es un proceso único y particular a cada individuo y está regido en especial por su carga genética. El lifting facial es una compleja técnica desarrollada en nuestra especialidad desde principios de siglo, para revertir los principales signos de este proceso. Los factores secundarios que gravitan en el envejecimiento facial son múltiples y por ello las ritidectomías o lifting cérvico faciales descritas han buscado corregir los cambios fisonómicos del envejecimiento excursionando, como se describe, en todos los planos tisulares involucrados. Esta cirugía por lo tanto, exige conocimiento cabal de la anatomía quirúrgica, pericia y experiencia para reducir las complicaciones, estigmas quirúrgicos y revisiones secundarias. La ridectomía facial ha evolucionado hacia un procedimiento más simple, de incisiones más cortas y disecciones menos extensas. Las suspensiones musculares han variado en su ejecución y los vectores de montaje y resección cutánea son cruciales en los resultados estéticos de la cirugía cérvico facial. Hoy estos vectores son de tracción más vertical. La corrección de la flaccidez va acompañada de un interés en reponer el volumen de la superficie del rostro, en especial el tercio medio. Las técnicas quirúrgicas de rejuvenecimiento, en especial el lifting facial, exigen una planificación para cada paciente. Las técnicas adjuntas al lifting, como blefaroplastias, mentoplastía, lipoaspiración de cuello, implantes faciales y otras, también han tenido una positiva evolución hacia la reducción de riesgos y mejor éxito estético.

  2. Reconocimiento facial

    OpenAIRE

    Urtiaga Abad, Juan Alfonso

    2014-01-01

    El presente proyecto trata sobre uno de los campos más problemáticos de la inteligencia artificial, el reconocimiento facial. Algo tan sencillo para las personas como es reconocer una cara conocida se traduce en complejos algoritmos y miles de datos procesados en cuestión de segundos. El proyecto comienza con un estudio del estado del arte de las diversas técnicas de reconocimiento facial, desde las más utilizadas y probadas como el PCA y el LDA, hasta técnicas experimentales que utilizan ...

  3. Facial Resemblance Exaggerates Sex-Specific Jealousy-Based Decisions1

    Directory of Open Access Journals (Sweden)

    Steven M. Platek

    2007-01-01

    Full Text Available Sex differences in reaction to a romantic partner's infidelity are well documented and are hypothesized to be attributable to sex-specific jealousy mechanisms which are utilized to solve adaptive problems associated with risk of extra-pair copulation. Males, because of the risk of cuckoldry become more upset by sexual infidelity, while females, because of loss of resources and biparental investment tend to become more distressed by emotional infidelity. However, the degree to which these sex-specific reactions to jealousy interact with cues to kin are completely unknown. Here we investigated the interaction of facial resemblance with decisions about sex-specific jealousy scenarios. Fifty nine volunteers were asked to imagine that two different people (represented by facial composites informed them about their romantic partner's sexual or emotional infidelity. Consistent with previous research, males ranked sexual infidelity scenarios as most upsetting and females ranked emotional infidelity scenarios most upsetting. However, when information about the infidelity was provided by a face that resembled the subject, sex-specific reactions to jealousy were exaggerated. This finding highlights the use of facial resemblance as a putative self-referent phenotypic matching cue that impacts trusting behavior in sexual contexts.

  4. Quantitative Comparison of Tolerance-Based Feature Transforms

    OpenAIRE

    Reniers, Dennie; Telea, Alexandru

    2006-01-01

    Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary images. Of these, two are novel methods and two extend existing distance transform algorithms. We quantitatively and qualitatively compare all algorithms on speed and accuracy of both distance and...

  5. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  6. Skull base chordoid meningioma: Imaging features and pathology

    International Nuclear Information System (INIS)

    Soo, Mark Y.S.; Gomes, Lavier; Ng, Thomas; Cruz, Malville Da; Dexter, Mark

    2004-01-01

    The clinical, imaging and pathological features of a skull base chordoid meningioma (CM) are described. The huge tumour resulted in obstructive hydrocephalus and partial erosion of the clivus such that a chordoma was suspected. The lesion's MRI findings were similar to those of a meningioma. Light microscopic, immunohistochemistry and ultrastructural features were diagnostic of CM. Chordoid meningioma is a rare subtype of meningioma and has a great tendency to recur should surgical resection be incomplete Copyright (2004) Blackwell Publishing Asia Pty Ltd

  7. Adaptive Feature Based Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez

    2005-01-01

    Many have experienced the problem that their Compact Disc players have difficulties playing Compact Discs with surface faults like scratches and fingerprints. The cause of this is due to the two servo control loops used to keep the Optical Pick-up Unit focused and radially on the information track...... of the Compact Disc. The problem is to design servo controllers which are well suited for handling surface faults which disturb the position measurement and still react sufficiently against normal disturbances like mechanical shocks. In previous work of the same authors a feature based control scheme for CD......-players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...

  8. An emotion-based facial expression word activates laughter module in the human brain: a functional magnetic resonance imaging study.

    Science.gov (United States)

    Osaka, Naoyuki; Osaka, Mariko; Kondo, Hirohito; Morishita, Masanao; Fukuyama, Hidenao; Shibasaki, Hiroshi

    2003-04-10

    We report an fMRI experiment demonstrating that visualization of onomatopoeia, an emotion-based facial expression word, highly suggestive of laughter, heard by the ear, significantly activates both the extrastriate visual cortex near the inferior occipital gyrus and the premotor (PM)/supplementary motor area (SMA) in the superior frontal gyrus while non-onomatopoeic words under the same task that did not imply laughter do not activate these areas in humans. We tested the specific hypothesis that an activation in extrastriate visual cortex and PM/SMA would be modulated by image formation of onomatopoeia implying laughter and found the hypothesis to be true. Copyright 2003 Elsevier Science Ireland Ltd.

  9. Multistage feature extraction for accurate face alignment

    NARCIS (Netherlands)

    Zuo, F.; With, de P.H.N.

    2004-01-01

    We propose a novel multistage facial feature extraction approach using a combination of 'global' and 'local' techniques. At the first stage, we use template matching, based on an Edge-Orientation-Map for fast feature position estimation. Using this result, a statistical framework applying the Active

  10. Facial soft tissue thickness in North Indian adult population

    Directory of Open Access Journals (Sweden)

    Tanushri Saxena

    2012-01-01

    Full Text Available Objectives: Forensic facial reconstruction is an attempt to reproduce a likeness of facial features of an individual, based on characteristics of the skull, for the purpose of individual identification - The aim of this study was to determine the soft tissue thickness values of individuals of Bareilly population, Uttar Pradesh, India and to evaluate whether these values can help in forensic identification. Study design: A total of 40 individuals (19 males, 21 females were evaluated using spiral computed tomographic (CT scan with 2 mm slice thickness in axial sections and soft tissue thicknesses were measured at seven midfacial anthropological facial landmarks. Results: It was found that facial soft tissue thickness values decreased with age. Soft tissue thickness values were less in females than in males, except at ramus region. Comparing the left and right values in individuals it was found to be not significant. Conclusion: Soft tissue thickness values are an important factor in facial reconstruction and also help in forensic identification of an individual. CT scan gives a good representation of these values and hence is considered an important tool in facial reconstruction- This study has been conducted in North Indian population and further studies with larger sample size can surely add to the data regarding soft tissue thicknesses.

  11. Caricaturing facial expressions.

    Science.gov (United States)

    Calder, A J; Rowland, D; Young, A W; Nimmo-Smith, I; Keane, J; Perrett, D I

    2000-08-14

    The physical differences between facial expressions (e.g. fear) and a reference norm (e.g. a neutral expression) were altered to produce photographic-quality caricatures. In Experiment 1, participants rated caricatures of fear, happiness and sadness for their intensity of these three emotions; a second group of participants rated how 'face-like' the caricatures appeared. With increasing levels of exaggeration the caricatures were rated as more emotionally intense, but less 'face-like'. Experiment 2 demonstrated a similar relationship between emotional intensity and level of caricature for six different facial expressions. Experiments 3 and 4 compared intensity ratings of facial expression caricatures prepared relative to a selection of reference norms - a neutral expression, an average expression, or a different facial expression (e.g. anger caricatured relative to fear). Each norm produced a linear relationship between caricature and rated intensity of emotion; this finding is inconsistent with two-dimensional models of the perceptual representation of facial expression. An exemplar-based multidimensional model is proposed as an alternative account.

  12. FEATURES BASED ON NEIGHBORHOOD PIXELS DENSITY - A STUDY AND COMPARISON

    Directory of Open Access Journals (Sweden)

    Satish Kumar

    2016-02-01

    Full Text Available In optical character recognition applications, the feature extraction method(s used to recognize document images play an important role. The features are the properties of the pattern that can be statistical, structural and/or transforms or series expansion. The structural features are difficult to compute particularly from hand-printed images. The structure of the strokes present inside the hand-printed images can be estimated using statistical means. In this paper three features have been purposed, those are based on the distribution of B/W pixels on the neighborhood of a pixel in an image. We name these features as Spiral Neighbor Density, Layer Pixel Density and Ray Density. The recognition performance of these features has been compared with two more features Neighborhood Pixels Weight and Total Distances in Four Directions already studied in our work. We have used more than 20000 Devanagari handwritten character images for conducting experiments. The experiments are conducted with two classifiers i.e. PNN and k-NN.

  13. Feature-based attentional modulation of orientation perception in somatosensation

    Directory of Open Access Journals (Sweden)

    Meike Annika Schweisfurth

    2014-07-01

    Full Text Available In a reaction time study of human tactile orientation detection the effects of spatial attention and feature-based attention were investigated. Subjects had to give speeded responses to target orientations (parallel and orthogonal to the finger axis in a random stream of oblique tactile distractor orientations presented to their index and ring fingers. Before each block of trials, subjects received a tactile cue at one finger. By manipulating the validity of this cue with respect to its location and orientation (feature, we provided an incentive to subjects to attend spatially to the cued location and only there to the cued orientation. Subjects showed quicker responses to parallel compared to orthogonal targets, pointing to an orientation anisotropy in sensory processing. Also, faster reaction times were observed in location-matched trials, i.e. when targets appeared on the cued finger, representing a perceptual benefit of spatial attention. Most importantly, reaction times were shorter to orientations matching the cue, both at the cued and at the uncued location, documenting a global enhancement of tactile sensation by feature-based attention. This is the first report of a perceptual benefit of feature-based attention outside the spatial focus of attention in somatosensory perception. The similarity to effects of feature-based attention in visual perception supports the notion of matching attentional mechanisms across sensory domains.

  14. A biometric identification system based on eigenpalm and eigenfinger features.

    Science.gov (United States)

    Ribaric, Slobodan; Fratric, Ivan

    2005-11-01

    This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

  15. FACIAL PAIN·

    African Journals Online (AJOL)

    -As the conditions which cause pain in the facial structures are many and varied, the ... involvement of the auriculo-temporal nerve and is usually relieved by avulsion of that .... of its effects. If it is uspected that a lesion in the po terior fossa ma ...

  16. Feature-based component model for design of embedded systems

    Science.gov (United States)

    Zha, Xuan Fang; Sriram, Ram D.

    2004-11-01

    An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

  17. Eye movement identification based on accumulated time feature

    Science.gov (United States)

    Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

    2017-06-01

    Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

  18. Linear feature selection in texture analysis - A PLS based method

    DEFF Research Database (Denmark)

    Marques, Joselene; Igel, Christian; Lillholm, Martin

    2013-01-01

    We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

  19. Art or Science? An Evidence-Based Approach to Human Facial Beauty a Quantitative Analysis Towards an Informed Clinical Aesthetic Practice.

    Science.gov (United States)

    Harrar, Harpal; Myers, Simon; Ghanem, Ali M

    2018-02-01

    Patients often seek guidance from the aesthetic practitioners regarding treatments to enhance their 'beauty'. Is there a science behind the art of assessment and if so is it measurable? Through the centuries, this question has challenged scholars, artists and surgeons. This study aims to undertake a review of the evidence behind quantitative facial measurements in assessing beauty to help the practitioner in everyday aesthetic practice. A Medline, Embase search for beauty, facial features and quantitative analysis was undertaken. Inclusion criteria were studies on adults, and exclusions included studies undertaken for dental, cleft lip, oncology, burns or reconstructive surgeries. The abstracts and papers were appraised, and further studies excluded that were considered inappropriate. The data were extracted using a standardised table. The final dataset was appraised in accordance with the PRISMA checklist and Holland and Rees' critique tools. Of the 1253 studies screened, 1139 were excluded from abstracts and a further 70 excluded from full text articles. The remaining 44 were assessed qualitatively and quantitatively. It became evident that the datasets were not comparable. Nevertheless, common themes were obvious, and these were summarised. Despite measures of the beauty of individual components to the sum of all the parts, such as symmetry and the golden ratio, we are yet far from establishing what truly constitutes quantitative beauty. Perhaps beauty is truly in the 'eyes of the beholder' (and perhaps in the eyes of the subject too). This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

  20. Methods to quantify soft-tissue based facial growth and treatment outcomes in children: a systematic review.

    Directory of Open Access Journals (Sweden)

    Sander Brons

    Full Text Available CONTEXT: Technological advancements have led craniofacial researchers and clinicians into the era of three-dimensional digital imaging for quantitative evaluation of craniofacial growth and treatment outcomes. OBJECTIVE: To give an overview of soft-tissue based methods for quantitative longitudinal assessment of facial dimensions in children until six years of age and to assess the reliability of these methods in studies with good methodological quality. DATA SOURCE: PubMed, EMBASE, Cochrane Library, Web of Science, Scopus and CINAHL were searched. A hand search was performed to check for additional relevant studies. STUDY SELECTION: Primary publications on facial growth and treatment outcomes in children younger than six years of age were included. DATA EXTRACTION: Independent data extraction by two observers. A quality assessment instrument was used to determine the methodological quality. Methods, used in studies with good methodological quality, were assessed for reliability expressed as the magnitude of the measurement error and the correlation coefficient between repeated measurements. RESULTS: In total, 47 studies were included describing 4 methods: 2D x-ray cephalometry; 2D photography; anthropometry; 3D imaging techniques (surface laser scanning, stereophotogrammetry and cone beam computed tomography. In general the measurement error was below 1 mm and 1° and correlation coefficients range from 0.65 to 1.0. CONCLUSION: Various methods have shown to be reliable. However, at present stereophotogrammetry seems to be the best 3D method for quantitative longitudinal assessment of facial dimensions in children until six years of age due to its millisecond fast image capture, archival capabilities, high resolution and no exposure to ionizing radiation.

  1. Analyzing locomotion synthesis with feature-based motion graphs.

    Science.gov (United States)

    Mahmudi, Mentar; Kallmann, Marcelo

    2013-05-01

    We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

  2. Fault Features Extraction and Identification based Rolling Bearing Fault Diagnosis

    International Nuclear Information System (INIS)

    Qin, B; Sun, G D; Zhang L Y; Wang J G; HU, J

    2017-01-01

    For the fault classification model based on extreme learning machine (ELM), the diagnosis accuracy and stability of rolling bearing is greatly influenced by a critical parameter, which is the number of nodes in hidden layer of ELM. An adaptive adjustment strategy is proposed based on vibrational mode decomposition, permutation entropy, and nuclear kernel extreme learning machine to determine the tunable parameter. First, the vibration signals are measured and then decomposed into different fault feature models based on variation mode decomposition. Then, fault feature of each model is formed to a high dimensional feature vector set based on permutation entropy. Second, the ELM output function is expressed by the inner product of Gauss kernel function to adaptively determine the number of hidden layer nodes. Finally, the high dimension feature vector set is used as the input to establish the kernel ELM rolling bearing fault classification model, and the classification and identification of different fault states of rolling bearings are carried out. In comparison with the fault classification methods based on support vector machine and ELM, the experimental results show that the proposed method has higher classification accuracy and better generalization ability. (paper)

  3. A Distributed Feature-based Environment for Collaborative Design

    Directory of Open Access Journals (Sweden)

    Wei-Dong Li

    2003-02-01

    Full Text Available This paper presents a client/server design environment based on 3D feature-based modelling and Java technologies to enable design information to be shared efficiently among members within a design team. In this environment, design tasks and clients are organised through working sessions generated and maintained by a collaborative server. The information from an individual design client during a design process is updated and broadcast to other clients in the same session through an event-driven and call-back mechanism. The downstream manufacturing analysis modules can be wrapped as agents and plugged into the open environment to support the design activities. At the server side, a feature-feature relationship is established and maintained to filter the varied information of a working part, so as to facilitate efficient information update during the design process.

  4. Image Mosaic Method Based on SIFT Features of Line Segment

    Directory of Open Access Journals (Sweden)

    Jun Zhu

    2014-01-01

    Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  5. [Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

    Science.gov (United States)

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

    In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

  6. Face Recognition by Bunch Graph Method Using a Group Based Adaptive Tolerant Neural Network

    OpenAIRE

    Aradhana D.; Girish H.; Karibasappa K.; Reddy A. Chennakeshava

    2011-01-01

    This paper presents a new method for feature extraction from the facial image by using bunch graph method. These extracted geometric features of the face are used subsequently for face recognition by utilizing the group based adaptive neural network. This method is suitable, when the facial images are rotation and translation invariant. Further the technique also free from size invariance of facial image and is capable of identifying the facial images correctly when corrupted w...

  7. An expert botanical feature extraction technique based on phenetic features for identifying plant species.

    Directory of Open Access Journals (Sweden)

    Hoshang Kolivand

    Full Text Available In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

  8. An expert botanical feature extraction technique based on phenetic features for identifying plant species

    Science.gov (United States)

    Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

    2018-01-01

    In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

  9. Sequence-based classification using discriminatory motif feature selection.

    Directory of Open Access Journals (Sweden)

    Hao Xiong

    Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

  10. Feature-Based Statistical Analysis of Combustion Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

    2011-11-18

    We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

  11. Feature-based morphometry: discovering group-related anatomical patterns.

    Science.gov (United States)

    Toews, Matthew; Wells, William; Collins, D Louis; Arbel, Tal

    2010-02-01

    This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). Copyright (c) 2009 Elsevier Inc. All rights reserved.

  12. Logic based feature detection on incore neutron spectra

    Energy Technology Data Exchange (ETDEWEB)

    Racz, A.; Kiss, S.; Bende-Farkas, S. (Hungarian Academy of Sciences, Budapest (Hungary). Central Research Inst. for Physics)

    1993-04-01

    A general framework for detecting features of incore neutron spectra with a rule-based methodology is presented. As an example, we determine the meaningful peaks in the APSD-s. This work is part of a larger project, aimed at developing a noise diagnostic expert system. (Author).

  13. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  14. Digital video steganalysis using motion vector recovery-based features.

    Science.gov (United States)

    Deng, Yu; Wu, Yunjie; Zhou, Linna

    2012-07-10

    As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.

  15. An opinion formation based binary optimization approach for feature selection

    Science.gov (United States)

    Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

    2018-02-01

    This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

  16. Novel dynamic Bayesian networks for facial action element recognition and understanding

    Science.gov (United States)

    Zhao, Wei; Park, Jeong-Seon; Choi, Dong-You; Lee, Sang-Woong

    2011-12-01

    In daily life, language is an important tool of communication between people. Besides language, facial action can also provide a great amount of information. Therefore, facial action recognition has become a popular research topic in the field of human-computer interaction (HCI). However, facial action recognition is quite a challenging task due to its complexity. In a literal sense, there are thousands of facial muscular movements, many of which have very subtle differences. Moreover, muscular movements always occur simultaneously when the pose is changed. To address this problem, we first build a fully automatic facial points detection system based on a local Gabor filter bank and principal component analysis. Then, novel dynamic Bayesian networks are proposed to perform facial action recognition using the junction tree algorithm over a limited number of feature points. In order to evaluate the proposed method, we have used the Korean face database for model training. For testing, we used the CUbiC FacePix, facial expressions and emotion database, Japanese female facial expression database, and our own database. Our experimental results clearly demonstrate the feasibility of the proposed approach.

  17. Automatic Human Facial Expression Recognition Based on Integrated Classifier From Monocular Video with Uncalibrated Camera

    Directory of Open Access Journals (Sweden)

    Yu Tao

    2017-01-01

    Full Text Available An automatic recognition framework for human facial expressions from a monocular video with an uncalibrated camera is proposed. The expression characteristics are first acquired from a kind of deformable template, similar to a facial muscle distribution. After associated regularization, the time sequences from the trait changes in space-time under complete expressional production are then arranged line by line in a matrix. Next, the matrix dimensionality is reduced by a method of manifold learning of neighborhood-preserving embedding. Finally, the refined matrix containing the expression trait information is recognized by a classifier that integrates the hidden conditional random field (HCRF and support vector machine (SVM. In an experiment using the Cohn–Kanade database, the proposed method showed a comparatively higher recognition rate than the individual HCRF or SVM methods in direct recognition from two-dimensional human face traits. Moreover, the proposed method was shown to be more robust than the typical Kotsia method because the former contains more structural characteristics of the data to be classified in space-time

  18. Annotation-based feature extraction from sets of SBML models.

    Science.gov (United States)

    Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron

    2015-01-01

    Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.

  19. Feature Recognition of Froth Images Based on Energy Distribution Characteristics

    Directory of Open Access Journals (Sweden)

    WU Yanpeng

    2014-09-01

    Full Text Available This paper proposes a determining algorithm for froth image features based on the amplitude spectrum energy statistics by applying Fast Fourier Transformation to analyze the energy distribution of various-sized froth. The proposed algorithm has been used to do a froth feature analysis of the froth images from the alumina flotation processing site, and the results show that the consistency rate reaches 98.1 % and the usability rate 94.2 %; with its good robustness and high efficiency, the algorithm is quite suitable for flotation processing state recognition.

  20. Dependence of the appearance-based perception of criminality, suggestibility, and trustworthiness on the level of pixelation of facial images.

    Science.gov (United States)

    Nurmoja, Merle; Eamets, Triin; Härma, Hanne-Loore; Bachmann, Talis

    2012-10-01

    While the dependence of face identification on the level of pixelation-transform of the images of faces has been well studied, similar research on face-based trait perception is underdeveloped. Because depiction formats used for hiding individual identity in visual media and evidential material recorded by surveillance cameras often consist of pixelized images, knowing the effects of pixelation on person perception has practical relevance. Here, the results of two experiments are presented showing the effect of facial image pixelation on the perception of criminality, trustworthiness, and suggestibility. It appears that individuals (N = 46, M age = 21.5 yr., SD = 3.1 for criminality ratings; N = 94, M age = 27.4 yr., SD = 10.1 for other ratings) have the ability to discriminate between facial cues ndicative of these perceived traits from the coarse level of image pixelation (10-12 pixels per face horizontally) and that the discriminability increases with a decrease in the coarseness of pixelation. Perceived criminality and trustworthiness appear to be better carried by the pixelized images than perceived suggestibility.

  1. Colesteatoma causando paralisia facial Cholesteatoma causing facial paralysis

    Directory of Open Access Journals (Sweden)

    José Ricardo Gurgel Testa

    2003-10-01

    blood supply or production of neurotoxic substances secreted from either the cholesteatoma matrix or bacteria enclosed in the tumor. AIM: To evaluate the incidence, clinical features and treatment of the facial palsy due cholesteatoma. STUDY DESIGN: Clinical retrospective. MATERIAL AND METHOD: Retrospective study of 10 cases of facial paralysis due cholesteatoma selected through a survey of 206 decompressions of the facial nerve due various aetiologies realized in the last 10 years in UNIFESP-EPM. RESULTS: The incidence of facial paralysis due cholesteatoma in this study was 4,85%, with female predominance (60%. The average age of the patients was 39 years. The duration and severity of the facial palsy associated with the extension of lesion were important for the functional recovery of the facial nerve. CONCLUSION: Early surgical approach is necessary in these cases to improve the nerve function more adequately. When disruption or intense fibrous replacement occurs in the facial nerve, nerve grafting (greater auricular/sural nerves and/or hypoglossal facial anastomosis may be suggested.

  2. [Facial injections of hyaluronic acid-based fillers for malformations. Preliminary study regarding scar tissue improvement and cosmetic betterment].

    Science.gov (United States)

    Franchi, G; Neiva-Vaz, C; Picard, A; Vazquez, M-P

    2018-02-02

    Cross-linked hyaluronic acid-based fillers have gained rapid acceptance for treating facial wrinkles, deep tissue folds and sunken areas due to aging. This study evaluates, in addition to space-filling properties, their effects on softness and elasticity as a secondary effect, following injection of 3 commercially available cross-linked hyaluronic acid-based fillers (15mg/mL, 17,5mg/mL and 20mg/mL) in patients presenting with congenital or acquired facial malformations. We started injecting gels of cross-linked hyaluronic acid-based fillers in those cases in 2013; we performed 46 sessions of injections in 32 patients, aged from 13-32. Clinical assessment was performed by the patient himself and by a plastic surgeon, 15 days after injections and 6-18 months later. Cross-linked hyaluronic acid-based fillers offered very subtle cosmetic results and supplemented surgery with a very high level of satisfaction of the patients. When injected in fibrosis, the first session enhanced softness and elasticity; the second session enhanced the volume. Cross-linked hyaluronic acid-based fillers fill sunken areas and better softness and elasticity of scar tissues. In addition to their well-understood space-filling function, as a secondary effect, the authors demonstrate that cross-linked hyaluronic acid-based fillers improve softness and elasticity of scarring tissues. Many experimental studies support our observations, showing that cross-linked hyaluronic acid stimulates the production of several extra-cellular matrix components, including dermal collagen and elastin. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  3. An Aerial Video Stabilization Method Based on SURF Feature

    Directory of Open Access Journals (Sweden)

    Wu Hao

    2016-01-01

    Full Text Available The video captured by Micro Aerial Vehicle is often degraded due to unexpected random trembling and jitter caused by wind and the shake of the aerial platform. An approach for stabilizing the aerial video based on SURF feature and Kalman filter is proposed. SURF feature points are extracted in each frame, and the feature points between adjacent frames are matched using Fast Library for Approximate Nearest Neighbors search method. Then Random Sampling Consensus matching algorithm and Least Squares Method are used to remove mismatching points pairs, and estimate the transformation between the adjacent images. Finally, Kalman filter is applied to smooth the motion parameters and separate Intentional Motion from Unwanted Motion to stabilize the aerial video. Experiments results show that the approach can stabilize aerial video efficiently with high accuracy, and it is robust to the translation, rotation and zooming motion of camera.

  4. Dissociable roles of internal feelings and face recognition ability in facial expression decoding.

    Science.gov (United States)

    Zhang, Lin; Song, Yiying; Liu, Ling; Liu, Jia

    2016-05-15

    The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Chinese character recognition based on Gabor feature extraction and CNN

    Science.gov (United States)

    Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

    2018-03-01

    As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

  6. A Method to Measure the Bracelet Based on Feature Energy

    Science.gov (United States)

    Liu, Hongmin; Li, Lu; Wang, Zhiheng; Huo, Zhanqiang

    2017-12-01

    To measure the bracelet automatically, a novel method based on feature energy is proposed. Firstly, the morphological method is utilized to preprocess the image, and the contour consisting of a concentric circle is extracted. Then, a feature energy function, which is relevant to the distances from one pixel to the edge points, is defined taking into account the geometric properties of the concentric circle. The input image is subsequently transformed to the feature energy distribution map (FEDM) by computing the feature energy of each pixel. The center of the concentric circle is thus located by detecting the maximum on the FEDM; meanwhile, the radii of the concentric circle are determined according to the feature energy function of the center pixel. Finally, with the use of a calibration template, the internal diameter and thickness of the bracelet are measured. The experimental results show that the proposed method can measure the true sizes of the bracelet accurately with the simplicity, directness and robustness compared to the existing methods.

  7. SVM-based glioma grading. Optimization by feature reduction analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zoellner, Frank G.; Schad, Lothar R. [University Medical Center Mannheim, Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Emblem, Kyrre E. [Massachusetts General Hospital, Charlestown, A.A. Martinos Center for Biomedical Imaging, Boston MA (United States). Dept. of Radiology; Harvard Medical School, Boston, MA (United States); Oslo Univ. Hospital (Norway). The Intervention Center

    2012-11-01

    We investigated the predictive power of feature reduction analysis approaches in support vector machine (SVM)-based classification of glioma grade. In 101 untreated glioma patients, three analytic approaches were evaluated to derive an optimal reduction in features; (i) Pearson's correlation coefficients (PCC), (ii) principal component analysis (PCA) and (iii) independent component analysis (ICA). Tumor grading was performed using a previously reported SVM approach including whole-tumor cerebral blood volume (CBV) histograms and patient age. Best classification accuracy was found using PCA at 85% (sensitivity = 89%, specificity = 84%) when reducing the feature vector from 101 (100-bins rCBV histogram + age) to 3 principal components. In comparison, classification accuracy by PCC was 82% (89%, 77%, 2 dimensions) and 79% by ICA (87%, 75%, 9 dimensions). For improved speed (up to 30%) and simplicity, feature reduction by all three methods provided similar classification accuracy to literature values ({proportional_to}87%) while reducing the number of features by up to 98%. (orig.)

  8. Unconscious analyses of visual scenes based on feature conjunctions.

    Science.gov (United States)

    Tachibana, Ryosuke; Noguchi, Yasuki

    2015-06-01

    To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

  9. Influence of gravity upon some facial signs.

    Science.gov (United States)

    Flament, F; Bazin, R; Piot, B

    2015-06-01

    Facial clinical signs and their integration are the basis of perception than others could have from ourselves, noticeably the age they imagine we are. Facial modifications in motion and their objective measurements before and after application of skin regimen are essential to go further in evaluation capacities to describe efficacy in facial dynamics. Quantification of facial modifications vis à vis gravity will allow us to answer about 'control' of facial shape in daily activities. Standardized photographs of the faces of 30 Caucasian female subjects of various ages (24-73 year) were successively taken at upright and supine positions within a short time interval. All these pictures were therefore reframed - any bias due to facial features was avoided when evaluating one single sign - for clinical quotation by trained experts of several facial signs regarding published standardized photographic scales. For all subjects, the supine position increased facial width but not height, giving a more fuller appearance to the face. More importantly, the supine position changed the severity of facial ageing features (e.g. wrinkles) compared to an upright position and whether these features were attenuated or exacerbated depended on their facial location. Supine station mostly modifies signs of the lower half of the face whereas those of the upper half appear unchanged or slightly accentuated. These changes appear much more marked in the older groups, where some deep labial folds almost vanish. These alterations decreased the perceived ages of the subjects by an average of 3.8 years. Although preliminary, this study suggests that a 90° rotation of the facial skin vis à vis gravity induces rapid rearrangements among which changes in tensional forces within and across the face, motility of interstitial free water among underlying skin tissue and/or alterations of facial Langer lines, likely play a significant role. © 2015 Society of Cosmetic Scientists and the Société Fran

  10. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-01-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  11. [Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

    Science.gov (United States)

    Li, Jing; Hong, Wenxue

    2014-12-01

    The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

  12. Features fusion based approach for handwritten Gujarati character recognition

    Directory of Open Access Journals (Sweden)

    Ankit Sharma

    2017-02-01

    Full Text Available Handwritten character recognition is a challenging area of research. Lots of research activities in the area of character recognition are already done for Indian languages such as Hindi, Bangla, Kannada, Tamil and Telugu. Literature review on handwritten character recognition indicates that in comparison with other Indian scripts research activities on Gujarati handwritten character recognition are very less.  This paper aims to bring Gujarati character recognition in attention. Recognition of isolated Gujarati handwritten characters is proposed using three different kinds of features and their fusion. Chain code based, zone based and projection profiles based features are utilized as individual features. One of the significant contribution of proposed work is towards the generation of large and representative dataset of 88,000 handwritten Gujarati characters. Experiments are carried out on this developed dataset. Artificial Neural Network (ANN, Support Vector Machine (SVM and Naive Bayes (NB classifier based methods are implemented for handwritten Gujarati character recognition. Experimental results show substantial enhancement over state-of-the-art and authenticate our proposals.

  13. 3D Facial Pattern Analysis for Autism

    Science.gov (United States)

    2010-07-01

    et al. (2001) proposed a two-level Garbor wavelet network (GWN) to detect eight facial features. In Bhuiyan et al. (2003) six facial features are...Toyama, K., Krüger, V., 2001. Hierarchical Wavelet Networks for Facial Feature Localization. ICCV’01 Workshop on Recognition, Analysis and... pathological  (red) and normal structure (blue) (b)  signed distance map (negative distance indicates the  pathological  shape is inside) (c) raw

  14. NetProt: Complex-based Feature Selection.

    Science.gov (United States)

    Goh, Wilson Wen Bin; Wong, Limsoon

    2017-08-04

    Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

  15. Biosensor method and system based on feature vector extraction

    Science.gov (United States)

    Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

    2012-04-17

    A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

  16. Collaborative Tracking of Image Features Based on Projective Invariance

    Science.gov (United States)

    Jiang, Jinwei

    -mode sensors for improving the flexibility and robustness of the system. From the experimental results during three field tests for the LASOIS system, we observed that most of the errors in the image processing algorithm are caused by the incorrect feature tracking. This dissertation addresses the feature tracking problem in image sequences acquired from cameras. Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow equation has been the most popular approach used by many in the field. This dissertation attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem, which provides collaboration among features. In contrast to alternative geometry based methods, the proposed approach provides an online solution to optical flow estimation in a collaborative fashion by exploiting Horn and Schunck flow estimation regularized by view geometric constraints. Proposed collaborative tracker estimates the motion of a feature based on the geometry of the scene and how the other features are moving. Alternative to this approach, a new closed form solution to tracking that combines the image appearance with the view geometry is also introduced. We particularly use invariants in the projective coordinates and conjecture that the traditional appearance solution can be significantly improved using view geometry. The geometric constraint is introduced by defining a new optical flow equation which exploits the scene geometry from a set drawn from tracked features. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template. The proposed collaborative tracking method is also tested in the visual navigation

  17. Cattle identification based in biometric features of the muzzle

    OpenAIRE

    Monteiro, Marta; Cadavez, Vasco; Monteiro, Fernando C.

    2015-01-01

    Cattle identification has been a serious problem for breeding association. Muzzle pattern or nose print has the same characteristic with the human fingerprint which is the most popular biometric marker. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle images using Speed-up Robust Features matching. The matching refinement technique based on the mat...

  18. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    OpenAIRE

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...

  19. Facial EMG responses to dynamic emotional facial expressions in boys with disruptive behavior disorders

    NARCIS (Netherlands)

    Wied, de M.; Boxtel, van Anton; Zaalberg, R.; Goudena, P.P.; Matthys, W.

    2006-01-01

    Based on the assumption that facial mimicry is a key factor in emotional empathy, and clinical observations that children with disruptive behavior disorders (DBD) are weak empathizers, the present study explored whether DBD boys are less facially responsive to facial expressions of emotions than

  20. A window-based time series feature extraction method.

    Science.gov (United States)

    Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

    2017-10-01

    This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Inpatient treatment of patients with acute idiopathic peripheral facial palsy: A population-based healthcare research study.

    Science.gov (United States)

    Plumbaum, K; Volk, G F; Boeger, D; Buentzel, J; Esser, D; Steinbrecher, A; Hoffmann, K; Jecker, P; Mueller, A; Radtke, G; Witte, O W; Guntinas-Lichius, O

    2017-12-01

    To determine the inpatient management for patients with acute idiopathic facial palsy (IFP) in Thuringia, Germany. Population-based study. All inpatients with IFP in all hospitals with departments of otolaryngology and neurology in 2012, in the German federal state, Thuringia. Patients' characteristics and treatment were compared between departments, and the probability of recovery was tested. A total of 291 patients were mainly treated in departments of otolaryngology (55%) and neurology (36%). Corticosteroid treatment was the predominant therapy (84.5%). The probability to receive a facial nerve grading (odds ratio [OR=12.939; 95% confidence interval [CI]=3.599 to 46.516), gustatory testing (OR=6.878; CI=1.064 to 44.474) and audiometry (OR=32.505; CI=1.485 to 711.257) was significantly higher in otolaryngology departments, but lower for cranial CT (OR=0.192; CI=0.061 to 0.602), cerebrospinal fluid examination (OR=0.024; CI=0.006 to 0.102). A total of 131 patients (45%) showed a recovery to House-Brackmann grade≤II. A pathological stapedial reflex test (Hazard ratio [HR]=0.416; CI=0.180 to 0.959) was the only independent diagnostic predictor of worse outcome. Prednisolone dose >500 mg (HR=0.579; CI 0.400 to 0.838) and no adjuvant physiotherapy (HR=0.568; CI=0.407 to 0.794) were treatment-related predictors of worse outcome. Inpatient treatment of IFP seems to be highly variable in daily practice, partly depending on the treating discipline and despite the availability of evidence-based guidelines. The population-based recovery rate was worse than reported in clinical trials. © 2017 John Wiley & Sons Ltd.

  2. A statistical method for 2D facial landmarking

    NARCIS (Netherlands)

    Dibeklioğlu, H.; Salah, A.A.; Gevers, T.

    2012-01-01

    Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in

  3. Validation of Underwater Sensor Package Using Feature Based SLAM

    Directory of Open Access Journals (Sweden)

    Christopher Cain

    2016-03-01

    Full Text Available Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.

  4. Validation of Underwater Sensor Package Using Feature Based SLAM

    Science.gov (United States)

    Cain, Christopher; Leonessa, Alexander

    2016-01-01

    Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package. PMID:26999142

  5. Iris-based medical analysis by geometric deformation features.

    Science.gov (United States)

    Ma, Lin; Zhang, D; Li, Naimin; Cai, Yan; Zuo, Wangmeng; Wang, Kuanguan

    2013-01-01

    Iris analysis studies the relationship between human health and changes in the anatomy of the iris. Apart from the fact that iris recognition focuses on modeling the overall structure of the iris, iris diagnosis emphasizes the detecting and analyzing of local variations in the characteristics of irises. This paper focuses on studying the geometrical structure changes in irises that are caused by gastrointestinal diseases, and on measuring the observable deformations in the geometrical structures of irises that are related to roundness, diameter and other geometric forms of the pupil and the collarette. Pupil and collarette based features are defined and extracted. A series of experiments are implemented on our experimental pathological iris database, including manual clustering of both normal and pathological iris images, manual classification by non-specialists, manual classification by individuals with a medical background, classification ability verification for the proposed features, and disease recognition by applying the proposed features. The results prove the effectiveness and clinical diagnostic significance of the proposed features and a reliable recognition performance for automatic disease diagnosis. Our research results offer a novel systematic perspective for iridology studies and promote the progress of both theoretical and practical work in iris diagnosis.

  6. Single-labelled music genre classification using content-based features

    CSIR Research Space (South Africa)

    Ajoodha, R

    2015-11-01

    Full Text Available In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these features into four groups: features extracted from the Fourier transform’s magnitude spectrum, features designed...

  7. Facial Displays Are Tools for Social Influence.

    Science.gov (United States)

    Crivelli, Carlos; Fridlund, Alan J

    2018-05-01

    Based on modern theories of signal evolution and animal communication, the behavioral ecology view of facial displays (BECV) reconceives our 'facial expressions of emotion' as social tools that serve as lead signs to contingent action in social negotiation. BECV offers an externalist, functionalist view of facial displays that is not bound to Western conceptions about either expressions or emotions. It easily accommodates recent findings of diversity in facial displays, their public context-dependency, and the curious but common occurrence of solitary facial behavior. Finally, BECV restores continuity of human facial behavior research with modern functional accounts of non-human communication, and provides a non-mentalistic account of facial displays well-suited to new developments in artificial intelligence and social robotics. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Feature-Based versus Category-Based Induction with Uncertain Categories

    Science.gov (United States)

    Griffiths, Oren; Hayes, Brett K.; Newell, Ben R.

    2012-01-01

    Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is…

  9. Novel Noninvasive Brain Disease Detection System Using a Facial Image Sensor

    Directory of Open Access Journals (Sweden)

    Ting Shu

    2017-12-01

    Full Text Available Brain disease including any conditions or disabilities that affect the brain is fast becoming a leading cause of death. The traditional diagnostic methods of brain disease are time-consuming, inconvenient and non-patient friendly. As more and more individuals undergo examinations to determine if they suffer from any form of brain disease, developing noninvasive, efficient, and patient friendly detection systems will be beneficial. Therefore, in this paper, we propose a novel noninvasive brain disease detection system based on the analysis of facial colors. The system consists of four components. A facial image is first captured through a specialized sensor, where four facial key blocks are next located automatically from the various facial regions. Color features are extracted from each block to form a feature vector for classification via the Probabilistic Collaborative based Classifier. To thoroughly test the system and its performance, seven facial key block combinations were experimented. The best result was achieved using the second facial key block, where it showed that the Probabilistic Collaborative based Classifier is the most suitable. The overall performance of the proposed system achieves an accuracy −95%, a sensitivity −94.33%, a specificity −95.67%, and an average processing time (for one sample of <1 min at brain disease detection.

  10. Facial expression influences face identity recognition during the attentional blink.

    Science.gov (United States)

    Bach, Dominik R; Schmidt-Daffy, Martin; Dolan, Raymond J

    2014-12-01

    Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry-suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

  11. Forensic Facial Reconstruction: Relationship Between the Alar Cartilage and Piriform Aperture.

    Science.gov (United States)

    Strapasson, Raíssa Ananda Paim; Herrera, Lara Maria; Melani, Rodolfo Francisco Haltenhoff

    2017-11-01

    During forensic facial reconstruction, facial features may be predicted based on the parameters of the skull. This study evaluated the relationships between alar cartilage and piriform aperture and nose morphology and facial typology. Ninety-six cone beam computed tomography images of Brazilian subjects (49 males and 47 females) were used in this study. OsiriX software was used to perform the following measurements: nasal width, distance between alar base insertion points, lower width of the piriform aperture, and upper width of the piriform aperture. Nasal width was associated with the lower width of the piriform aperture, sex, skeletal vertical pattern of the face, and age. The current study contributes to the improvement of forensic facial guides by identifying the relationships between the alar cartilages and characteristics of the biological profile of members of a population that has been little studied thus far. © 2017 American Academy of Forensic Sciences.

  12. Estimador de calidad en sistemas de reconocimiento facial

    OpenAIRE

    Espejo Caballero, Daniel

    2015-01-01

    El fin de este proyecto es conseguir obtener una estimación de la calidad de una imagen facial, a partir del estudio y extracción de características obtenidas, a partir de las imágenes faciales. The goal of this project is get a quality estimation of a facial image, using the extraction and learning of the differents features that we can extract from a facial image.

  13. Iris features-based heart disease diagnosis by computer vision

    Science.gov (United States)

    Nguchu, Benedictor A.; Li, Li

    2017-07-01

    The study takes advantage of several new breakthroughs in computer vision technology to develop a new mid-irisbiomedical platform that processes iris image for early detection of heart-disease. Guaranteeing early detection of heart disease provides a possibility of having non-surgical treatment as suggested by biomedical researchers and associated institutions. However, our observation discovered that, a clinical practicable solution which could be both sensible and specific for early detection is still lacking. Due to this, the rate of majority vulnerable to death is highly increasing. The delayed diagnostic procedures, inefficiency, and complications of available methods are the other reasons for this catastrophe. Therefore, this research proposes the novel IFB (Iris Features Based) method for diagnosis of premature, and early stage heart disease. The method incorporates computer vision and iridology to obtain a robust, non-contact, nonradioactive, and cost-effective diagnostic tool. The method analyzes abnormal inherent weakness in tissues, change in color and patterns, of a specific region of iris that responds to impulses of heart organ as per Bernard Jensen-iris Chart. The changes in iris infer the presence of degenerative abnormalities in heart organ. These changes are precisely detected and analyzed by IFB method that includes, tensor-based-gradient(TBG), multi orientations gabor filters(GF), textural oriented features(TOF), and speed-up robust features(SURF). Kernel and Multi class oriented support vector machines classifiers are used for classifying normal and pathological iris features. Experimental results demonstrated that the proposed method, not only has better diagnostic performance, but also provides an insight for early detection of other diseases.

  14. Sympathicotomy for isolated facial blushing

    DEFF Research Database (Denmark)

    Licht, Peter Bjørn; Pilegaard, Hans K; Ladegaard, Lars

    2012-01-01

    Background. Facial blushing is one of the most peculiar of human expressions. The pathophysiology is unclear, and the prevalence is unknown. Thoracoscopic sympathectomy may cure the symptom and is increasingly used in patients with isolated facial blushing. The evidence base for the optimal level...... of targeting the sympathetic chain is limited to retrospective case studies. We present a randomized clinical trial. Methods. 100 patients were randomized (web-based, single-blinded) to rib-oriented (R2 or R2-R3) sympathicotomy for isolated facial blushing at two university hospitals during a 6-year period...... between R2 and R2-R3 sympathicotomy for isolated facial blushing. Both were effective, and QOL increased significantly. Despite very frequent side effects, the vast majority of patients were satisfied. Surprisingly, many patients experienced mild recurrent symptoms within the first year; this should...

  15. Improved image retrieval based on fuzzy colour feature vector

    Science.gov (United States)

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  16. Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

    Science.gov (United States)

    Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

    2015-04-01

    Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Smart Images Search based on Visual Features Fusion

    International Nuclear Information System (INIS)

    Saad, M.H.

    2013-01-01

    Image search engines attempt to give fast and accurate access to the wide range of the huge amount images available on the Internet. There have been a number of efforts to build search engines based on the image content to enhance search results. Content-Based Image Retrieval (CBIR) systems have achieved a great interest since multimedia files, such as images and videos, have dramatically entered our lives throughout the last decade. CBIR allows automatically extracting target images according to objective visual contents of the image itself, for example its shapes, colors and textures to provide more accurate ranking of the results. The recent approaches of CBIR differ in terms of which image features are extracted to be used as image descriptors for matching process. This thesis proposes improvements of the efficiency and accuracy of CBIR systems by integrating different types of image features. This framework addresses efficient retrieval of images in large image collections. A comparative study between recent CBIR techniques is provided. According to this study; image features need to be integrated to provide more accurate description of image content and better image retrieval accuracy. In this context, this thesis presents new image retrieval approaches that provide more accurate retrieval accuracy than previous approaches. The first proposed image retrieval system uses color, texture and shape descriptors to form the global features vector. This approach integrates the yc b c r color histogram as a color descriptor, the modified Fourier descriptor as a shape descriptor and modified Edge Histogram as a texture descriptor in order to enhance the retrieval results. The second proposed approach integrates the global features vector, which is used in the first approach, with the SURF salient point technique as local feature. The nearest neighbor matching algorithm with a proposed similarity measure is applied to determine the final image rank. The second approach

  18. Dynamic Facial Prosthetics for Sufferers of Facial Paralysis

    Directory of Open Access Journals (Sweden)

    Fergal Coulter

    2011-10-01

    Full Text Available BackgroundThis paper discusses the various methods and the materialsfor the fabrication of active artificial facial muscles. Theprimary use for these will be the reanimation of paralysedor atrophied muscles in sufferers of non-recoverableunilateral facial paralysis.MethodThe prosthetic solution described in this paper is based onsensing muscle motion of the contralateral healthy musclesand replicating that motion across a patient’s paralysed sideof the face, via solid state and thin film actuators. Thedevelopment of this facial prosthetic device focused onrecreating a varying intensity smile, with emphasis ontiming, displacement and the appearance of the wrinklesand folds that commonly appear around the nose and eyesduring the expression.An animatronic face was constructed with actuations beingmade to a silicone representation musculature, usingmultiple shape-memory alloy cascades. Alongside theartificial muscle physical prototype, a facial expressionrecognition software system was constructed. This formsthe basis of an automated calibration and reconfigurationsystem for the artificial muscles following implantation, soas to suit the implantee’s unique physiognomy.ResultsAn animatronic model face with silicone musculature wasdesigned and built to evaluate the performance of ShapeMemory Alloy artificial muscles, their power controlcircuitry and software control systems. A dual facial motionsensing system was designed to allow real time control overmodel – a piezoresistive flex sensor to measure physicalmotion, and a computer vision system to evaluate real toartificial muscle performance.Analysis of various facial expressions in real subjects wasmade, which give useful data upon which to base thesystems parameter limits.ConclusionThe system performed well, and the various strengths andshortcomings of the materials and methods are reviewedand considered for the next research phase, when newpolymer based artificial muscles are constructed

  19. Facial Prototype Formation in Children.

    Science.gov (United States)

    Inn, Donald; And Others

    This study examined memory representation as it is exhibited in young children's formation of facial prototypes. In the first part of the study, researchers constructed images of faces using an Identikit that provided the features of hair, eyes, mouth, nose, and chin. Images were varied systematically. A series of these images, called exemplar…

  20. MRI-based diagnostic imaging of the intratemporal facial nerve; Die kernspintomographische Darstellung des intratemporalen N. facialis

    Energy Technology Data Exchange (ETDEWEB)

    Kress, B.; Baehren, W. [Bundeswehrkrankenhaus Ulm (Germany). Abt. fuer Radiologie

    2001-07-01

    Detailed imaging of the five sections of the full intratemporal course of the facial nerve can be achieved by MRI and using thin tomographic section techniques and surface coils. Contrast media are required for tomographic imaging of pathological processes. Established methods are available for diagnostic evaluation of cerebellopontine angle tumors and chronic Bell's palsy, as well as hemifacial spasms. A method still under discussion is MRI for diagnostic evaluation of Bell's palsy in the presence of fractures of the petrous bone, when blood volumes in the petrous bone make evaluation even more difficult. MRI-based diagnostic evaluation of the idiopatic facial paralysis currently is subject to change. Its usual application cannot be recommended for routine evaluation at present. However, a quantitative analysis of contrast medium uptake of the nerve may be an approach to improve the prognostic value of MRI in acute phases of Bell's palsy. (orig./CB) [German] Die detaillierte kernspintomographische Darstellung des aus 5 Abschnitten bestehenden intratemporalen Verlaufes des N. facialis gelingt mit der MRI unter Einsatz von Duennschichttechniken und Oberflaechenspulen. Zur Darstellung von pathologischen Vorgaengen ist die Gabe von Kontrastmittel notwendig. Die Untersuchung in der Diagnostik von Kleinhirnbrueckenwinkeltumoren und der chronischen Facialisparese ist etabliert, ebenso wie die Diagnostik des Hemispasmus facialis. In der Diskussion ist die MRI zur Dokumentation der Facialisparese bei Felsenbeinfrakturen, wobei die Einblutungen im Felsenbein die Beurteilung erschweren. Die kernspintomographische Diagnostik der idiopathischen Facialisparese befindet sich im Wandel. In der herkoemmlichen Form wird sie nicht zur Routinediagnostik empfohlen. Die quantitative Analyse der Kontrastmittelaufnahme im Nerv koennte jedoch die prognostische Bedeutung der MRI in der Akutphase der Bell's palsy erhoehen. (orig.)

  1. Text feature extraction based on deep learning: a review.

    Science.gov (United States)

    Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

    2017-01-01

    Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

  2. Three-Dimensional Facial Adaptation for MPEG-4 Talking Heads

    Directory of Open Access Journals (Sweden)

    Nikos Grammalidis

    2002-10-01

    Full Text Available This paper studies a new method for three-dimensional (3D facial model adaptation and its integration into a text-to-speech (TTS system. The 3D facial adaptation requires a set of two orthogonal views of the user′s face with a number of feature points located on both views. Based on the correspondences of the feature points′ positions, a generic face model is deformed nonrigidly treating every facial part as a separate entity. A cylindrical texture map is then built from the two image views. The generated head models are compared to corresponding models obtained by the commonly used adaptation method that utilizes 3D radial bases functions. The generated 3D models are integrated into a talking head system, which consists of two distinct parts: a multilingual text to speech sub-system and an MPEG-4 compliant facial animation sub-system. Support for the Greek language has been added, while preserving lip and speech synchronization.

  3. Complex chromosome rearrangement in a child with microcephaly, dysmorphic facial features and mosaicism for a terminal deletion del(18(q21.32-qter investigated by FISH and array-CGH: Case report

    Directory of Open Access Journals (Sweden)

    Kokotas Haris

    2008-11-01

    Full Text Available Abstract We report on a 7 years and 4 months old Greek boy with mild microcephaly and dysmorphic facial features. He was a sociable child with maxillary hypoplasia, epicanthal folds, upslanting palpebral fissures with long eyelashes, and hypertelorism. His ears were prominent and dysmorphic, he had a long philtrum and a high arched palate. His weight was 17 kg (25th percentile and his height 120 cm (50th percentile. High resolution chromosome analysis identified in 50% of the cells a normal male karyotype, and in 50% of the cells one chromosome 18 showed a terminal deletion from 18q21.32. Molecular cytogenetic investigation confirmed a del(18(q21.32-qter in the one chromosome 18, but furthermore revealed the presence of a duplication in q21.2 in the other chromosome 18. The case is discussed concerning comparable previously reported cases and the possible mechanisms of formation.

  4. Characters Feature Extraction Based on Neat Oracle Bone Rubbings

    OpenAIRE

    Lei Guo

    2013-01-01

    In order to recognize characters on the neat oracle bone rubbings, a new mesh point feature extraction algorithm was put forward in this paper by researching and improving of the existing coarse mesh feature extraction algorithm and the point feature extraction algorithm. Some improvements of this algorithm were as followings: point feature was introduced into the coarse mesh feature, the absolute address was converted to relative address, and point features have been changed grid and positio...

  5. Kernel-based discriminant feature extraction using a representative dataset

    Science.gov (United States)

    Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.

    2002-07-01

    Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.

  6. Javanese Character Feature Extraction Based on Shape Energy

    Directory of Open Access Journals (Sweden)

    Galih Hendra Wibowo

    2017-07-01

    Full Text Available Javanese character is one of Indonesia's noble culture, especially in Java. However, the number of Javanese people who are able to read the letter has decreased so that there need to be conservation efforts in the form of a system that is able to recognize the characters. One solution to these problem lies in Optical Character Recognition (OCR studies, where one of its heaviest points lies in feature extraction which is to distinguish each character. Shape Energy is one of feature extraction method with the basic idea of how the character can be distinguished simply through its skeleton. Based on the basic idea, then the development of feature extraction is done based on its components to produce an angular histogram with various variations of multiples angle. Furthermore, the performance test of this method and its basic method is performed in Javanese character dataset, which has been obtained from various images, is 240 data with 19 labels by using K-Nearest Neighbors as its classification method. Performance values were obtained based on the accuracy which is generated through the Cross-Validation process of 80.83% in the angular histogram with an angle of 20 degrees, 23% better than Shape Energy. In addition, other test results show that this method is able to recognize rotated character with the lowest performance value of 86% at 180-degree rotation and the highest performance value of 96.97% at 90-degree rotation. It can be concluded that this method is able to improve the performance of Shape Energy in the form of recognition of Javanese characters as well as robust to the rotation.

  7. Feature-based automatic color calibration for networked camera system

    Science.gov (United States)

    Yamamoto, Shoji; Taki, Keisuke; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

    2011-01-01

    In this paper, we have developed a feature-based automatic color calibration by using an area-based detection and adaptive nonlinear regression method. Simple color matching of chartless is achieved by using the characteristic of overlapping image area with each camera. Accurate detection of common object is achieved by the area-based detection that combines MSER with SIFT. Adaptive color calibration by using the color of detected object is calculated by nonlinear regression method. This method can indicate the contribution of object's color for color calibration, and automatic selection notification for user is performed by this function. Experimental result show that the accuracy of the calibration improves gradually. It is clear that this method can endure practical use of multi-camera color calibration if an enough sample is obtained.

  8. Image Relaxation Matching Based on Feature Points for DSM Generation

    Institute of Scientific and Technical Information of China (English)

    ZHENG Shunyi; ZHANG Zuxun; ZHANG Jianqing

    2004-01-01

    In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlaton matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.

  9. Mutual information based feature selection for medical image retrieval

    Science.gov (United States)

    Zhi, Lijia; Zhang, Shaomin; Li, Yan

    2018-04-01

    In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

  10. Proton Conductivity and Operational Features Of PBI-Based Membranes

    DEFF Research Database (Denmark)

    Qingfeng, Li; Jensen, Jens Oluf; Precht Noyé, Pernille

    2005-01-01

    As an approach to high temperature operation of PEMFCs, acid-doped PBI membranes are under active development. The membrane exhibits high proton conductivity under low water contents at temperatures up to 200°C. Mechanisms of proton conduction for the membranes have been proposed. Based on the me...... on the membranes fuel cell tests have been demonstrated. Operating features of the PBI cell include no humidification, high CO tolerance, better heat utilization and possible integration with fuel processing units. Issues for further development are also discussed....

  11. Magnetoencephalographic study on facial movements

    Directory of Open Access Journals (Sweden)

    Kensaku eMiki

    2014-07-01

    Full Text Available In this review, we introduced our three studies that focused on facial movements. In the first study, we examined the temporal characteristics of neural responses elicited by viewing mouth movements, and assessed differences between the responses to mouth opening and closing movements and an averting eyes condition. Our results showed that the occipitotemporal area, the human MT/V5 homologue, was active in the perception of both mouth and eye motions. Viewing mouth and eye movements did not elicit significantly different activity in the occipitotemporal area, which indicated that perception of the movement of facial parts may be processed in the same manner, and this is different from motion in general. In the second study, we investigated whether early activity in the occipitotemporal region evoked by eye movements was influenced by a face contour and/or features such as the mouth. Our results revealed specific information processing for eye movements in the occipitotemporal region, and this activity was significantly influenced by whether movements appeared with the facial contour and/or features, in other words, whether the eyes moved, even if the movement itself was the same. In the third study, we examined the effects of inverting the facial contour (hair and chin and features (eyes, nose, and mouth on processing for static and dynamic face perception. Our results showed the following: (1 In static face perception, activity in the right fusiform area was affected more by the inversion of features while that in the left fusiform area was affected more by a disruption in the spatial relationship between the contour and features, and (2 In dynamic face perception, activity in the right occipitotemporal area was affected by the inversion of the facial contour.

  12. Three dimensional pattern recognition using feature-based indexing and rule-based search

    Science.gov (United States)

    Lee, Jae-Kyu

    In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

  13. Pupil size reflects the focus of feature-based attention.

    Science.gov (United States)

    Binda, Paola; Pereverzeva, Maria; Murray, Scott O

    2014-12-15

    We measured pupil size in adult human subjects while they selectively attended to one of two surfaces, bright and dark, defined by coherently moving dots. The two surfaces were presented at the same location; therefore, subjects could select the cued surface only on the basis of its features. With no luminance change in the stimulus, we find that pupil size was smaller when the bright surface was attended and larger when the dark surface was attended: an effect of feature-based (or surface-based) attention. With the same surfaces at nonoverlapping locations, we find a similar effect of spatial attention. The pupil size modulation cannot be accounted for by differences in eye position and by other variables known to affect pupil size such as task difficulty, accommodation, or the mere anticipation (imagery) of bright/dark stimuli. We conclude that pupil size reflects not just luminance or cognitive state, but the interaction between the two: it reflects which luminance level in the visual scene is relevant for the task at hand. Copyright © 2014 the American Physiological Society.

  14. Iris recognition based on key image feature extraction.

    Science.gov (United States)

    Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

    2008-01-01

    In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

  15. Efficient Identification Using a Prime-Feature-Based Technique

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Haq, Shaiq A.; Valente, Andrea

    2011-01-01

    . Fingerprint identification system, implemented on PC/104 based real-time systems, can accurately identify the operator. Traditionally, the uniqueness of a fingerprint is determined by the overall pattern of ridges and valleys as well as the local ridge anomalies e.g., a ridge bifurcation or a ridge ending......, which are called minutiae points. Designing a reliable automatic fingerprint matching algorithm for minimal platform is quite challenging. In real-time systems, efficiency of the matching algorithm is of utmost importance. To achieve this goal, a prime-feature-based indexing algorithm is proposed......Identification of authorized train drivers through biometrics is a growing area of interest in locomotive radio remote control systems. The existing technique of password authentication is not very reliable and potentially unauthorized personnel may also operate the system on behalf of the operator...

  16. Facial Symmetry: An Illusion?

    Directory of Open Access Journals (Sweden)

    Naveen Reddy Admala

    2013-01-01

    Materials and methods: A sample of 120 patients (60 males and 60 females; mean age, 15 years; range, 16-22 years who had received orthodontic clinical examination at AME′s Dental College and Hospital were selected. Selection was made in such a way that following malocclusions with equal sexual distribution was possible from the patient database. Patients selected were classified into skeletal Class I (25 males and 25 females, Class II (25 males and 25 females and Class III (10 males and 10 females based on ANB angle. The number was predecided to be the same and also was based on the number of patients with following malocclusions reported to the department. Differences in length between distances from the points at which ear rods were inserted to the facial midline and the perpendicular distance from the softtissue menton to the facial midline were measured on a frontofacial photograph. Subjects with a discrepancy of more than three standard deviations of the measurement error were categorized as having left- or right-sided laterality. Results: Of subjects with facial asymmetry, 74.1% had a wider right hemiface, and 51.6% of those with chin deviation had left-sided laterality. These tendencies were independent of sex or skeletal jaw relationships. Conclusion: These results suggest that laterality in the normal asymmetry of the face, which is consistently found in humans, is likely to be a hereditary rather than an acquired trait.

  17. Research of image retrieval technology based on color feature

    Science.gov (United States)

    Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

    2009-10-01

    Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

  18. Intact Rapid Facial Mimicry as well as Generally Reduced Mimic Responses in Stable Schizophrenia Patients

    Science.gov (United States)

    Chechko, Natalya; Pagel, Alena; Otte, Ellen; Koch, Iring; Habel, Ute

    2016-01-01

    Spontaneous emotional expressions (rapid facial mimicry) perform both emotional and social functions. In the current study, we sought to test whether there were deficits in automatic mimic responses to emotional facial expressions in patients (15 of them) with stable schizophrenia compared to 15 controls. In a perception-action interference paradigm (the Simon task; first experiment), and in the context of a dual-task paradigm (second experiment), the task-relevant stimulus feature was the gender of a face, which, however, displayed a smiling or frowning expression (task-irrelevant stimulus feature). We measured the electromyographical activity in the corrugator supercilii and zygomaticus major muscle regions in response to either compatible or incompatible stimuli (i.e., when the required response did or did not correspond to the depicted facial expression). The compatibility effect based on interactions between the implicit processing of a task-irrelevant emotional facial expression and the conscious production of an emotional facial expression did not differ between the groups. In stable patients (in spite of a reduced mimic reaction), we observed an intact capacity to respond spontaneously to facial emotional stimuli. PMID:27303335

  19. Vehicle Unsteady Dynamics Characteristics Based on Tire and Road Features

    Directory of Open Access Journals (Sweden)

    Bin Ma

    2013-01-01

    Full Text Available During automotive related accidents, tire and road play an important role in vehicle unsteady dynamics as they have a significant impact on the sliding friction. The calculation of the rubber viscoelastic energy loss modulus and the true contact area model is improved based on the true contact area and the rubber viscoelastic theory. A 10 DOF full vehicle dynamic model in consideration of the kinetic sliding friction coefficient which has good accuracy and reality is developed. The stability test is carried out to evaluate the effectiveness of the model, and the simulation test is done in MATLAB to analyze the impact of tire feature and road self-affine characteristics on the sport utility vehicle (SUV unsteady dynamics under different weights. The findings show that it is a great significance to analyze the SUV dynamics equipped with different tire on different roads, which may provide useful insights into solving the explicit-implicit features of tire prints in systematically and designing active safety systems.

  20. Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

    Science.gov (United States)

    Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

    How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

  1. Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data

    OpenAIRE

    Kalliatakis, Grigorios; Vidakis, Nikolaos; Triantafyllidis, Georgios

    2017-01-01

    Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating comprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor)...

  2. Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

    Science.gov (United States)

    Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

    2015-01-01

    In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

  3. Recurrent unilateral facial nerve palsy in a child with dehiscent facial nerve canal

    Directory of Open Access Journals (Sweden)

    Christopher Liu

    2016-12-01

    Full Text Available Objective: The dehiscent facial nerve canal has been well documented in histopathological studies of temporal bones as well as in clinical setting. We describe clinical and radiologic features of a child with recurrent facial nerve palsy and dehiscent facial nerve canal. Methods: Retrospective chart review. Results: A 5-year-old male was referred to the otolaryngology clinic for evaluation of recurrent acute otitis media and hearing loss. He also developed recurrent left peripheral FN palsy associated with episodes of bilateral acute otitis media. High resolution computed tomography of the temporal bones revealed incomplete bony coverage of the tympanic segment of the left facial nerve. Conclusions: Recurrent peripheral FN palsy may occur in children with recurrent acute otitis media in the presence of a dehiscent facial nerve canal. Facial nerve canal dehiscence should be considered in the differential diagnosis of children with recurrent peripheral FN palsy.

  4. How Transferable are CNN-based Features for Age and Gender Classification?

    OpenAIRE

    Özbulak, Gökhan; Aytar, Yusuf; Ekenel, Hazım Kemal

    2016-01-01

    Age and gender are complementary soft biometric traits for face recognition. Successful estimation of age and gender from facial images taken under real-world conditions can contribute improving the identification results in the wild. In this study, in order to achieve robust age and gender classification in the wild, we have benefited from Deep Convolutional Neural Networks based representation. We have explored transferability of existing deep convolutional neural network (CNN) models for a...

  5. Facial Expression Recognition Through Machine Learning

    Directory of Open Access Journals (Sweden)

    Nazia Perveen

    2015-08-01

    Full Text Available Facial expressions communicate non-verbal cues which play an important role in interpersonal relations. Automatic recognition of facial expressions can be an important element of normal human-machine interfaces it might likewise be utilized as a part of behavioral science and in clinical practice. In spite of the fact that people perceive facial expressions for all intents and purposes immediately solid expression recognition by machine is still a challenge. From the point of view of automatic recognition a facial expression can be considered to comprise of disfigurements of the facial parts and their spatial relations or changes in the faces pigmentation. Research into automatic recognition of the facial expressions addresses the issues encompassing the representation and arrangement of static or dynamic qualities of these distortions or face pigmentation. We get results by utilizing the CVIPtools. We have taken train data set of six facial expressions of three persons and for train data set purpose we have total border mask sample 90 and 30 border mask sample for test data set purpose and we use RST- Invariant features and texture features for feature analysis and then classified them by using k- Nearest Neighbor classification algorithm. The maximum accuracy is 90.

  6. Soft computing based feature selection for environmental sound classification

    NARCIS (Netherlands)

    Shakoor, A.; May, T.M.; Van Schijndel, N.H.

    2010-01-01

    Environmental sound classification has a wide range of applications,like hearing aids, mobile communication devices, portable media players, and auditory protection devices. Sound classification systemstypically extract features from the input sound. Using too many features increases complexity

  7. Arabic Feature-Based Level Sentiment Analysis Using Lexicon ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... structured reviews being prior knowledge for mining unstructured reviews. ... FDSO has been introduced, which defines a space of product features ... polarity of a review using feature ontology and sentiment lexicons.

  8. In search of Leonardo: computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject

    Science.gov (United States)

    Tyler, Christopher W.; Smith, William A. P.; Stork, David G.

    2012-03-01

    One of the enduring mysteries in the history of the Renaissance is the adult appearance of the archetypical "Renaissance Man," Leonardo da Vinci. His only acknowledged self-portrait is from an advanced age, and various candidate images of younger men are difficult to assess given the absence of documentary evidence. One clue about Leonardo's appearance comes from the remark of the contemporary historian, Vasari, that the sculpture of David by Leonardo's master, Andrea del Verrocchio, was based on the appearance of Leonardo when he was an apprentice. Taking a cue from this statement, we suggest that the more mature sculpture of St. Thomas, also by Verrocchio, might also have been a portrait of Leonardo. We tested the possibility Leonardo was the subject for Verrocchio's sculpture by a novel computational technique for the comparison of three-dimensional facial configurations. Based on quantitative measures of similarities, we also assess whether another pair of candidate two-dimensional images are plausibly attributable as being portraits of Leonardo as a young adult. Our results are consistent with the claim Leonardo is indeed the subject in these works, but we need comparisons with images in a larger corpora of candidate artworks before our results achieve statistical significance.

  9. Development of the Korean Facial Emotion Stimuli: Korea University Facial Expression Collection 2nd Edition

    Directory of Open Access Journals (Sweden)

    Sun-Min Kim

    2017-05-01

    Full Text Available Background: Developing valid emotional facial stimuli for specific ethnicities creates ample opportunities to investigate both the nature of emotional facial information processing in general and clinical populations as well as the underlying mechanisms of facial emotion processing within and across cultures. Given that most entries in emotional facial stimuli databases were developed with western samples, and given that very few of the eastern emotional facial stimuli sets were based strictly on the Ekman’s Facial Action Coding System, developing valid emotional facial stimuli of eastern samples remains a high priority.Aims: To develop and examine the psychometric properties of six basic emotional facial stimuli recruiting professional Korean actors and actresses based on the Ekman’s Facial Action Coding System for the Korea University Facial Expression Collection-Second Edition (KUFEC-II.Materials And Methods: Stimulus selection was done in two phases. First, researchers evaluated the clarity and intensity of each stimulus developed based on the Facial Action Coding System. Second, researchers selected a total of 399 stimuli from a total of 57 actors and actresses, which were then rated on accuracy, intensity, valence, and arousal by 75 independent raters.Conclusion: The hit rates between the targeted and rated expressions of the KUFEC-II were all above 80%, except for fear (50% and disgust (63%. The KUFEC-II appears to be a valid emotional facial stimuli database, providing the largest set of emotional facial stimuli. The mean intensity score was 5.63 (out of 7, suggesting that the stimuli delivered the targeted emotions with great intensity. All positive expressions were rated as having a high positive valence, whereas all negative expressions were rated as having a high negative valence. The KUFEC II is expected to be widely used in various psychological studies on emotional facial expression. KUFEC-II stimuli can be obtained through

  10. Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

    Science.gov (United States)

    Wang, Rui; Zhu, Zhengdan; Zhang, Liang

    2015-05-01

    Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

  11. Deletion of 11q12.3-11q13.1 in a patient with intellectual disability and childhood facial features resembling Cornelia de Lange syndrome

    DEFF Research Database (Denmark)

    Boyle, Martine Isabel; Jespersgaard, Cathrine; Nazaryan, Lusine

    2015-01-01

    Deletions within 11q12.3-11q13.1 are very rare and to date only two cases have been described in the literature. In this study we describe a 23-year-old male patient with intellectual disability, behavioral problems, dysmorphic features, dysphagia, gastroesophageal reflux and skeletal abnormalities...

  12. Feature-Based Retinal Image Registration Using D-Saddle Feature

    Directory of Open Access Journals (Sweden)

    Roziana Ramli

    2017-01-01

    Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

  13. Distinct facial processing in schizophrenia and schizoaffective disorders

    Science.gov (United States)

    Chen, Yue; Cataldo, Andrea; Norton, Daniel J; Ongur, Dost

    2011-01-01

    Although schizophrenia and schizoaffective disorders have both similar and differing clinical features, it is not well understood whether similar or differing pathophysiological processes mediate patients’ cognitive functions. Using psychophysical methods, this study compared the performances of schizophrenia (SZ) patients, patients with schizoaffective disorder (SA), and a healthy control group in two face-related cognitive tasks: emotion discrimination, which tested perception of facial affect, and identity discrimination, which tested perception of non-affective facial features. Compared to healthy controls, SZ patients, but not SA patients, exhibited deficient performance in both fear and happiness discrimination, as well as identity discrimination. SZ patients, but not SA patients, also showed impaired performance in a theory-of-mind task for which emotional expressions are identified based upon the eye regions of face images. This pattern of results suggests distinct processing of face information in schizophrenia and schizoaffective disorders. PMID:21868199

  14. Additivity of Feature-based and Symmetry-based Grouping Effects in Multiple Object Tracking

    Directory of Open Access Journals (Sweden)

    Chundi eWang

    2016-05-01

    Full Text Available Multiple object tracking (MOT is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the laws of perceptual organization proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. Additive effect refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The where and what pathways might have played an important role in the additive grouping effect.

  15. Three-dimensional facial analyses of Indian and Malaysian women.

    Science.gov (United States)

    Kusugal, Preethi; Ruttonji, Zarir; Gowda, Roopa; Rajpurohit, Ladusingh; Lad, Pritam; Ritu

    2015-01-01

    Facial measurements serve as a valuable tool in the treatment planning of maxillofacial rehabilitation, orthodontic treatment, and orthognathic surgeries. The esthetic guidelines of face are still based on neoclassical canons, which were used in the ancient art. These canons are considered to be highly subjective, and there is ample evidence in the literature, which raises such questions as whether or not these canons can be applied for the modern population. This study was carried out to analyze the facial features of Indian and Malaysian women by using three-dimensional (3D) scanner and thus determine the prevalence of neoclassical facial esthetic canons in both the groups. The study was carried out on 60 women in the age range of 18-25 years, out of whom 30 were Indian and 30 Malaysian. As many as 16 facial measurements were taken by using a noncontact 3D scanner. Unpaired t-test was used for comparison of facial measurements between Indian and Malaysian females. Two-tailed Fisher exact test was used to determine the prevalence of neoclassical canons. Orbital Canon was prevalent in 80% of Malaysian women; the same was found only in 16% of Indian women (P = 0.00013). About 43% of Malaysian women exhibited orbitonasal canon (P = 0.0470) whereas nasoaural canon was prevalent in 73% of Malaysian and 33% of Indian women (P = 0.0068). Orbital, orbitonasal, and nasoaural canon were more prevalent in Malaysian women. Facial profile canon, nasooral, and nasofacial canons were not seen in either group. Though some canons provide guidelines in esthetic analyses of face, complete reliance on these canons is not justifiable.

  16. Are Rich People Perceived as More Trustworthy? Perceived Socioeconomic Status Modulates Judgments of Trustworthiness and Trust Behavior Based on Facial Appearance

    Directory of Open Access Journals (Sweden)

    Yue Qi

    2018-04-01

    Full Text Available In the era of globalization, people meet strangers from different countries more often than ever. Previous research indicates that impressions of trustworthiness based on facial appearance play an important role in interpersonal cooperation behaviors. The current study examined whether additional information about socioeconomic status (SES, including national prosperity and individual monthly income, affects facial judgments and appearance-based trust decisions. Besides reproducing previous conclusions that trustworthy faces receive more money than untrustworthy faces, the present study showed that high-income individuals were judged as more trustworthy than low-income individuals, and also were given more money in a trust game. However, trust behaviors were not modulated by the nationality of the faces. The present research suggests that people are more likely to trust strangers with a high income, compared with individuals with a low income.

  17. Topological Embedding Feature Based Resource Allocation in Network Virtualization

    Directory of Open Access Journals (Sweden)

    Hongyan Cui

    2014-01-01

    Full Text Available Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.

  18. Classification of Textures Using Filter Based Local Feature Extraction

    Directory of Open Access Journals (Sweden)

    Bocekci Veysel Gokhan

    2016-01-01

    Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

  19. Grammar-based feature generation for time-series prediction

    CERN Document Server

    De Silva, Anthony Mihirana

    2015-01-01

    This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

  20. [Idiopathic facial paralysis in children].

    Science.gov (United States)

    Achour, I; Chakroun, A; Ayedi, S; Ben Rhaiem, Z; Mnejja, M; Charfeddine, I; Hammami, B; Ghorbel, A

    2015-05-01

    Idiopathic facial palsy is the most common cause of facial nerve palsy in children. Controversy exists regarding treatment options. The objectives of this study were to review the epidemiological and clinical characteristics as well as the outcome of idiopathic facial palsy in children to suggest appropriate treatment. A retrospective study was conducted on children with a diagnosis of idiopathic facial palsy from 2007 to 2012. A total of 37 cases (13 males, 24 females) with a mean age of 13.9 years were included in this analysis. The mean duration between onset of Bell's palsy and consultation was 3 days. Of these patients, 78.3% had moderately severe (grade IV) or severe paralysis (grade V on the House and Brackmann grading). Twenty-seven patients were treated in an outpatient context, three patients were hospitalized, and seven patients were treated as outpatients and subsequently hospitalized. All patients received corticosteroids. Eight of them also received antiviral treatment. The complete recovery rate was 94.6% (35/37). The duration of complete recovery was 7.4 weeks. Children with idiopathic facial palsy have a very good prognosis. The complete recovery rate exceeds 90%. However, controversy exists regarding treatment options. High-quality studies have been conducted on adult populations. Medical treatment based on corticosteroids alone or combined with antiviral treatment is certainly effective in improving facial function outcomes in adults. In children, the recommendation for prescription of steroids and antiviral drugs based on adult treatment appears to be justified. Randomized controlled trials in the pediatric population are recommended to define a strategy for management of idiopathic facial paralysis. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  1. A Cross-Sectional Clinic-Based Study in Patients With Side-Locked Unilateral Headache and Facial Pain.

    Science.gov (United States)

    Prakash, Sanjay; Rathore, Chaturbhuj; Makwana, Prayag; Dave, Ankit

    2016-07-01

    To undertake the epidemiological evaluation of the patients presenting with side-locked headache and facial pain in a tertiary neurology outpatient clinic. Side-locked unilateral headache and facial pain include a large number of primary and secondary headaches and cranial neuropathies. A diagnostic approach for the patients presenting with strictly unilateral headaches is important as many of these headache disorders respond to a highly selective drug. Epidemiological data may guide us to formulate a proper approach for such patients. However, the literature is sparse on strictly unilateral headache and facial pain. We prospectively recruited 307 consecutive adult patients (>18 years) with side-locked headache and facial pain presenting to a neurology outpatient clinic between July 2014 and December 2015. All patients were subjected to MRI brain and other investigations to find out the different secondary causes. The diagnosis was carried out by at least two headache specialists together. All patients were classified according to the International Classification of Headache Disorder-third edition (ICHD-3β). The mean age at the time of examination was 42.4 ± 13.6 years (range 18-80 years). Forty-eight percent of patients were male. Strictly unilateral headaches accounted for 19.2% of the total headaches seen in the clinic. Headaches were classified as primary in 58%, secondary in 18%, and cranial neuropathies and other facial pain in 16% patients. Five percent of patients could not be classified. Three percent of patients were classified as per the Appendix section of ICHD-3β. The prevalence of secondary headaches and painful cranial neuropathies increased with age. A total of 36 different diagnoses were made. Only two diseases (migraine and cluster headache) had a prevalence of more than 10%. The prevalence of 13 diseases varied between 6 and 9%. The prevalence of other 14 groups was ≤1%. Migraine was the most common diagnosis (15%). Cervicogenic headache

  2. The Speed of Feature-Based Attention: Attentional Advantage Is Slow, but Selection Is Fast

    Science.gov (United States)

    Huang, Liqiang

    2010-01-01

    When paying attention to a feature (e.g., red), no attentional advantage is gained in perceiving items with this feature in very brief displays. Therefore, feature-based attention seems to be slow. In previous feature-based attention studies, attention has often been measured as the difference in performance in a secondary task. In our recent work…

  3. Palm-vein classification based on principal orientation features.

    Directory of Open Access Journals (Sweden)

    Yujia Zhou

    Full Text Available Personal recognition using palm-vein patterns has emerged as a promising alternative for human recognition because of its uniqueness, stability, live body identification, flexibility, and difficulty to cheat. With the expanding application of palm-vein pattern recognition, the corresponding growth of the database has resulted in a long response time. To shorten the response time of identification, this paper proposes a simple and useful classification for palm-vein identification based on principal direction features. In the registration process, the Gaussian-Radon transform is adopted to extract the orientation matrix and then compute the principal direction of a palm-vein image based on the orientation matrix. The database can be classified into six bins based on the value of the principal direction. In the identification process, the principal direction of the test sample is first extracted to ascertain the corresponding bin. One-by-one matching with the training samples is then performed in the bin. To improve recognition efficiency while maintaining better recognition accuracy, two neighborhood bins of the corresponding bin are continuously searched to identify the input palm-vein image. Evaluation experiments are conducted on three different databases, namely, PolyU, CASIA, and the database of this study. Experimental results show that the searching range of one test sample in PolyU, CASIA and our database by the proposed method for palm-vein identification can be reduced to 14.29%, 14.50%, and 14.28%, with retrieval accuracy of 96.67%, 96.00%, and 97.71%, respectively. With 10,000 training samples in the database, the execution time of the identification process by the traditional method is 18.56 s, while that by the proposed approach is 3.16 s. The experimental results confirm that the proposed approach is more efficient than the traditional method, especially for a large database.

  4. The Prevalence of Cosmetic Facial Plastic Procedures among Facial Plastic Surgeons.

    Science.gov (United States)

    Moayer, Roxana; Sand, Jordan P; Han, Albert; Nabili, Vishad; Keller, Gregory S

    2018-04-01

    This is the first study to report on the prevalence of cosmetic facial plastic surgery use among facial plastic surgeons. The aim of this study is to determine the frequency with which facial plastic surgeons have cosmetic procedures themselves. A secondary aim is to determine whether trends in usage of cosmetic facial procedures among facial plastic surgeons are similar to that of nonsurgeons. The study design was an anonymous, five-question, Internet survey distributed via email set in a single academic institution. Board-certified members of the American Academy of Facial Plastic and Reconstructive Surgery (AAFPRS) were included in this study. Self-reported history of cosmetic facial plastic surgery or minimally invasive procedures were recorded. The survey also queried participants for demographic data. A total of 216 members of the AAFPRS responded to the questionnaire. Ninety percent of respondents were male ( n  = 192) and 10.3% were female ( n  = 22). Thirty-three percent of respondents were aged 31 to 40 years ( n  = 70), 25% were aged 41 to 50 years ( n  = 53), 21.4% were aged 51 to 60 years ( n  = 46), and 20.5% were older than 60 years ( n  = 44). Thirty-six percent of respondents had a surgical cosmetic facial procedure and 75% has at least one minimally invasive cosmetic facial procedure. Facial plastic surgeons are frequent users of cosmetic facial plastic surgery. This finding may be due to access, knowledge base, values, or attitudes. By better understanding surgeon attitudes toward facial plastic surgery, we can improve communication with patients and delivery of care. This study is a first step in understanding use of facial plastic procedures among facial plastic surgeons. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  5. Feature-based motion control for near-repetitive structures

    NARCIS (Netherlands)

    Best, de J.J.T.H.

    2011-01-01

    In many manufacturing processes, production steps are carried out on repetitive structures which consist of identical features placed in a repetitive pattern. In the production of these repetitive structures one or more consecutive steps are carried out on the features to create the final product.

  6. Biometric features and privacy : condemned, based upon your finger print

    NARCIS (Netherlands)

    Bullee, Jan-Willem; Veldhuis, Raymond N.J.

    What information is available in biometric features besides that needed for the biometric recognition process? What if a biometric feature contains Personally Identifiable Information? Will the whole biometric system become a threat to privacy? This paper is an attempt to quantifiy the link between

  7. Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold.

    Science.gov (United States)

    Palacios, Jonathan; Yeh, Harry; Wang, Wenping; Zhang, Yue; Laramee, Robert S; Sharma, Ritesh; Schultz, Thomas; Zhang, Eugene

    2016-03-01

    Three-dimensional symmetric tensor fields have a wide range of applications in solid and fluid mechanics. Recent advances in the (topological) analysis of 3D symmetric tensor fields focus on degenerate tensors which form curves. In this paper, we introduce a number of feature surfaces, such as neutral surfaces and traceless surfaces, into tensor field analysis, based on the notion of eigenvalue manifold. Neutral surfaces are the boundary between linear tensors and planar tensors, and the traceless surfaces are the boundary between tensors of positive traces and those of negative traces. Degenerate curves, neutral surfaces, and traceless surfaces together form a partition of the eigenvalue manifold, which provides a more complete tensor field analysis than degenerate curves alone. We also extract and visualize the isosurfaces of tensor modes, tensor isotropy, and tensor magnitude, which we have found useful for domain applications in fluid and solid mechanics. Extracting neutral and traceless surfaces using the Marching Tetrahedra method can cause the loss of geometric and topological details, which can lead to false physical interpretation. To robustly extract neutral surfaces and traceless surfaces, we develop a polynomial description of them which enables us to borrow techniques from algebraic surface extraction, a topic well-researched by the computer-aided design (CAD) community as well as the algebraic geometry community. In addition, we adapt the surface extraction technique, called A-patches, to improve the speed of finding degenerate curves. Finally, we apply our analysis to data from solid and fluid mechanics as well as scalar field analysis.

  8. Feature extraction algorithm for space targets based on fractal theory

    Science.gov (United States)

    Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

    2007-11-01

    In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

  9. Historical feature pattern extraction based network attack situation sensing algorithm.

    Science.gov (United States)

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  10. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    Directory of Open Access Journals (Sweden)

    Yong Zeng

    2014-01-01

    Full Text Available The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE. First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  11. Facial Sports Injuries

    Science.gov (United States)

    ... the patient has HIV or hepatitis. Facial Fractures Sports injuries can cause potentially serious broken bones or fractures of the face. Common symptoms of facial fractures include: swelling and bruising, ...

  12. A novel malformation complex of bilateral and symmetric preaxial radial ray-thumb aplasia and lower limb defects with minimal facial dysmorphic features: a case report and literature review.

    Science.gov (United States)

    Al Kaissi, Ali; Klaushofer, Klaus; Krebs, Alexander; Grill, Franz

    2008-10-24

    Radial hemimelia is a congenital abnormality characterised by the partial or complete absence of the radius. The longitudinal hemimelia indicates the absence of one or more bones along the preaxial (medial) or postaxial (lateral) side of the limb. Preaxial limb defects occurred more frequently with a combination of microtia, esophageal atresia, anorectal atresia, heart defects, unilateral kidney dysgenesis, and some axial skeletal defects. Postaxial acrofacial dysostoses are characterised by distinctive facies and postaxial limb deficiencies, involving the 5th finger, metacarpal/ulnar/fibular/and metatarsal. The patient, an 8-year-old-boy with minimal craniofacial dysmorphic features but with profound upper limb defects of bilateral and symmetrical absence of the radius and the thumbs respectively. In addition, there was a unilateral tibio-fibular hypoplasia (hemimelia) associated with hypoplasia of the terminal phalanges and malsegmentation of the upper thoracic vertebrae, causing effectively the development of thoracic kyphosis. In the typical form of the preaxial acrofacial dysostosis, there are aberrations in the development of the first and second branchial arches and limb buds. The craniofacial dysmorphic features are characteristic such as micrognathia, zygomatic hypoplasia, cleft palate, and preaxial limb defects. Nager and de Reynier in 1948, who used the term acrofacial dysostosis (AFD) to distinguish the condition from mandibulofacial dysostosis. Neither the facial features nor the limb defects in our present patient appear to be absolutely typical with the previously reported cases of AFD. Our patient expands the phenotype of syndromic preaxial limb malformation complex. He might represent a new syndromic entity of mild naso-maxillary malformation in connection with axial and extra-axial malformation complex.

  13. Dogs Evaluate Threatening Facial Expressions by Their Biological Validity--Evidence from Gazing Patterns.

    Directory of Open Access Journals (Sweden)

    Sanni Somppi

    Full Text Available Appropriate response to companions' emotional signals is important for all social creatures. The emotional expressions of humans and non-human animals have analogies in their form and function, suggesting shared evolutionary roots, but very little is known about how animals other than primates view and process facial expressions. In primates, threat-related facial expressions evoke exceptional viewing patterns compared with neutral or positive stimuli. Here, we explore if domestic dogs (Canis familiaris have such an attentional bias toward threatening social stimuli and whether observed emotional expressions affect dogs' gaze fixation distribution among the facial features (eyes, midface and mouth. We recorded the voluntary eye gaze of 31 domestic dogs during viewing of facial photographs of humans and dogs with three emotional expressions (threatening, pleasant and neutral. We found that dogs' gaze fixations spread systematically among facial features. The distribution of fixations was altered by the seen expression, but eyes were the most probable targets of the first fixations and gathered longer looking durations than mouth regardless of the viewed expression. The examination of the inner facial features as a whole revealed more pronounced scanning differences among expressions. This suggests that dogs do not base their perception of facial expressions on the viewing of single structures, but the interpretation of the composition formed by eyes, midface and mouth. Dogs evaluated social threat rapidly and this evaluation led to attentional bias, which was dependent on the depicted species: threatening conspecifics' faces evoked heightened attention but threatening human faces instead an avoidance response. We propose that threatening signals carrying differential biological validity are processed via distinctive neurocognitive pathways. Both of these mechanisms may have an adaptive significance for domestic dogs. The findings provide a novel

  14. Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli

    Directory of Open Access Journals (Sweden)

    Tanja S. H. Wingenbach

    2018-06-01

    Full Text Available According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a explicit imitation of viewed facial emotional expressions (stimulus-congruent condition, (b pen-holding with the lips (stimulus-incongruent condition, and (c passive viewing (control condition. It was hypothesised that (1 experimental condition (a and (b result in greater facial muscle activity than (c, (2 experimental condition (a increases emotion recognition accuracy from others’ faces compared to (c, (3 experimental condition (b lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c. Participants (42 males, 42 females underwent a facial emotion recognition experiment (ADFES-BIV while electromyography (EMG was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.

  15. Incongruence Between Observers' and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli.

    Science.gov (United States)

    Wingenbach, Tanja S H; Brosnan, Mark; Pfaltz, Monique C; Plichta, Michael M; Ashwin, Chris

    2018-01-01

    According to embodied cognition accounts, viewing others' facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others' facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others' faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions' order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.

  16. Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli

    Science.gov (United States)

    Wingenbach, Tanja S. H.; Brosnan, Mark; Pfaltz, Monique C.; Plichta, Michael M.; Ashwin, Chris

    2018-01-01

    According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed. PMID:29928240

  17. Subspace-Based Holistic Registration for Low-Resolution Facial Images

    Directory of Open Access Journals (Sweden)

    Boom BJ

    2010-01-01

    Full Text Available Subspace-based holistic registration is introduced as an alternative to landmark-based face registration, which has a poor performance on low-resolution images, as obtained in camera surveillance applications. The proposed registration method finds the alignment by maximizing the similarity score between a probe and a gallery image. We use a novel probabilistic framework for both user-independent as well as user-specific face registration. The similarity is calculated using the probability that the face image is correctly aligned in a face subspace, but additionally we take the probability into account that the face is misaligned based on the residual error in the dimensions perpendicular to the face subspace. We perform extensive experiments on the FRGCv2 database to evaluate the impact that the face registration methods have on face recognition. Subspace-based holistic registration on low-resolution images can improve face recognition in comparison with landmark-based registration on high-resolution images. The performance of the tested face recognition methods after subspace-based holistic registration on a low-resolution version of the FRGC database is similar to that after manual registration.

  18. Genetics Home Reference: branchio-oculo-facial syndrome

    Science.gov (United States)

    ... face and neck. Its characteristic features include skin anomalies on the neck, malformations of the eyes and ears, and distinctive facial features. "Branchio-" refers to the branchial arches, which are structures in the developing embryo ...

  19. A brain-computer interface for potential non-verbal facial communication based on EEG signals related to specific emotions.

    Science.gov (United States)

    Kashihara, Koji

    2014-01-01

    Unlike assistive technology for verbal communication, the brain-machine or brain-computer interface (BMI/BCI) has not been established as a non-verbal communication tool for amyotrophic lateral sclerosis (ALS) patients. Face-to-face communication enables access to rich emotional information, but individuals suffering from neurological disorders, such as ALS and autism, may not express their emotions or communicate their negative feelings. Although emotions may be inferred by looking at facial expressions, emotional prediction for neutral faces necessitates advanced judgment. The process that underlies brain neuronal responses to neutral faces and causes emotional changes remains unknown. To address this problem, therefore, this study attempted to decode conditioned emotional reactions to neutral face stimuli. This direction was motivated by the assumption that if electroencephalogram (EEG) signals can be used to detect patients' emotional responses to specific inexpressive faces, the results could be incorporated into the design and development of BMI/BCI-based non-verbal communication tools. To these ends, this study investigated how a neutral face associated with a negative emotion modulates rapid central responses in face processing and then identified cortical activities. The conditioned neutral face-triggered event-related potentials that originated from the posterior temporal lobe statistically significantly changed during late face processing (600-700 ms) after stimulus, rather than in early face processing activities, such as P1 and N170 responses. Source localization revealed that the conditioned neutral faces increased activity in the right fusiform gyrus (FG). This study also developed an efficient method for detecting implicit negative emotional responses to specific faces by using EEG signals. A classification method based on a support vector machine enables the easy classification of neutral faces that trigger specific individual emotions. In

  20. Factors contributing to the adaptation aftereffects of facial expression.

    Science.gov (United States)

    Butler, Andrea; Oruc, Ipek; Fox, Christopher J; Barton, Jason J S

    2008-01-29

    Previous studies have demonstrated the existence of adaptation aftereffects for facial expressions. Here we investigated which aspects of facial stimuli contribute to these aftereffects. In Experiment 1, we examined the role of local adaptation to image elements such as curvature, shape and orientation, independent of expression, by using hybrid faces constructed from either the same or opposing expressions. While hybrid faces made with consistent expressions generated aftereffects as large as those with normal faces, there were no aftereffects from hybrid faces made from different expressions, despite the fact that these contained the same local image elements. In Experiment 2, we examined the role of facial features independent of the normal face configuration by contrasting adaptation with whole faces to adaptation with scrambled faces. We found that scrambled faces also generated significant aftereffects, indicating that expressive features without a normal facial configuration could generate expression aftereffects. In Experiment 3, we examined the role of facial configuration by using schematic faces made from line elements that in isolation do not carry expression-related information (e.g. curved segments and straight lines) but that convey an expression when arranged in a normal facial configuration. We obtained a significant aftereffect for facial configurations but not scrambled configurations of these line elements. We conclude that facial expression aftereffects are not due to local adaptation to image elements but due to high-level adaptation of neural representations that involve both facial features and facial configuration.

  1. Riparian erosion vulnerability model based on environmental features.

    Science.gov (United States)

    Botero-Acosta, Alejandra; Chu, Maria L; Guzman, Jorge A; Starks, Patrick J; Moriasi, Daniel N

    2017-12-01

    Riparian erosion is one of the major causes of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and land loss hazards. Land and soil management practices are implemented as conservation and restoration measures to mitigate the environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along the riparian zone that are susceptible to erosion. The methodology was developed by integrating the physically-based watershed model MIKE-SHE, to simulate water movement, and a habitat suitability model, MaxEnt, to quantify the probability of presences of elevation changes (i.e., erosion) across the watershed. The presences of elevation changes were estimated based on two LiDAR-based elevation datasets taken in 2009 and 2012. The changes in elevation were grouped into four categories: low (0.5 - 0.7 m), medium (0.7 - 1.0 m), high (1.0 - 1.7 m) and very high (1.7 - 5.9 m), considering each category as a studied "species". The categories' locations were then used as "species location" map in MaxEnt. The environmental features used as constraints to the presence of erosion were land cover, soil, stream power index, overland flow, lateral inflow, and discharge. The modeling framework was evaluated in the Fort Cobb Reservoir Experimental watershed in southcentral Oklahoma. Results showed that the most vulnerable areas for erosion were located at the upper riparian zones of the Cobb and Lake sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to streambank erosion. Approximatively 80% of the riparian zone (streambank

  2. Effect of Feature Dimensionality on Object-based Land Cover ...

    African Journals Online (AJOL)

    Myburgh, G, Mnr

    features, it has not been demonstrated with land cover mapping in an ... classifiers were chosen for benchmarking as the latter is the most commonly .... Additional open-source libraries were acquired to complete the implementation of the.

  3. Advances in face detection and facial image analysis

    CERN Document Server

    Celebi, M; Smolka, Bogdan

    2016-01-01

    This book presents the state-of-the-art in face detection and analysis. It outlines new research directions, including in particular psychology-based facial dynamics recognition, aimed at various applications such as behavior analysis, deception detection, and diagnosis of various psychological disorders. Topics of interest include face and facial landmark detection, face recognition, facial expression and emotion analysis, facial dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as applications of face analysis.

  4. Cascaded face alignment via intimacy definition feature

    Science.gov (United States)

    Li, Hailiang; Lam, Kin-Man; Chiu, Man-Yau; Wu, Kangheng; Lei, Zhibin

    2017-09-01

    Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement.

  5. Peripheral facial weakness (Bell's palsy).

    Science.gov (United States)

    Basić-Kes, Vanja; Dobrota, Vesna Dermanović; Cesarik, Marijan; Matovina, Lucija Zadro; Madzar, Zrinko; Zavoreo, Iris; Demarin, Vida

    2013-06-01

    Peripheral facial weakness is a facial nerve damage that results in muscle weakness on one side of the face. It may be idiopathic (Bell's palsy) or may have a detectable cause. Almost 80% of peripheral facial weakness cases are primary and the rest of them are secondary. The most frequent causes of secondary peripheral facial weakness are systemic viral infections, trauma, surgery, diabetes, local infections, tumor, immune disorders, drugs, degenerative diseases of the central nervous system, etc. The diagnosis relies upon the presence of typical signs and symptoms, blood chemistry tests, cerebrospinal fluid investigations, nerve conduction studies and neuroimaging methods (cerebral MRI, x-ray of the skull and mastoid). Treatment of secondary peripheral facial weakness is based on therapy for the underlying disorder, unlike the treatment of Bell's palsy that is controversial due to the lack of large, randomized, controlled, prospective studies. There are some indications that steroids or antiviral agents are beneficial but there are also studies that show no beneficial effect. Additional treatments include eye protection, physiotherapy, acupuncture, botulinum toxin, or surgery. Bell's palsy has a benign prognosis with complete recovery in about 80% of patients, 15% experience some mode of permanent nerve damage and severe consequences remain in 5% of patients.

  6. A feature dictionary supporting a multi-domain medical knowledge base.

    Science.gov (United States)

    Naeymi-Rad, F

    1989-01-01

    Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

  7. A Brain–Computer Interface for Potential Nonverbal Facial Communication Based on EEG Signals Related to Specific Emotions

    Directory of Open Access Journals (Sweden)

    Koji eKashihara

    2014-08-01

    Full Text Available Unlike assistive technology for verbal communication, the brain–machine or brain–computer interface (BMI/BCI has not been established as a nonverbal communication tool for amyotrophic lateral sclerosis (ALS patients. Face-to-face communication enables access to rich emotional information, but individuals suffering from neurological disorders, such as ALS and autism, may not express their emotions or communicate their negative feelings. Although emotions may be inferred by looking at facial expressions, emotional prediction for neutral faces necessitates advanced judgment. The process that underlies brain neuronal responses to neutral faces and causes emotional changes remains unknown. To address this problem, therefore, this study attempted to decode conditioned emotional reactions to neutral face stimuli. This direction was motivated by the assumption that if electroencephalogram (EEG signals can be used to detect patients’ emotional responses to specific inexpressive faces, the results could be incorporated into the design and development of BMI/BCI-based nonverbal communication tools. To these ends, this study investigated how a neutral face associated with a negative emotion modulates rapid central responses in face processing and then identified cortical activities. The conditioned neutral face-triggered event-related potentials that originated from the posterior temporal lobe statistically significantly changed during late face processing (600–700 ms after stimulus, rather than in early face processing activities, such as P1 and N170 responses. Source localization revealed that the conditioned neutral faces increased activity in the right fusiform gyrus. This study also developed an efficient method for detecting implicit negative emotional responses to specific faces by using EEG signals.

  8. Facial Asymmetry Evaluation in Juvenile Idiopathic Arthritis Patients Based On Cone-Beam Computed Tomography And 3D Photography

    DEFF Research Database (Denmark)

    Economou, Stalo; Stoustrup, Peter Bangsgaard; Kristensen, Kasper Dahl

    AIMS: The aim of the study was to assess the degree of and correlation between facial hard and soft tissue asymmetry in patients with juvenile idiopathic arthritis, identify valid soft tissue points for clinical examination and assess the smallest clinical detectable level of dentofacial asymmetr...

  9. Eagle's syndrome with facial palsy

    Directory of Open Access Journals (Sweden)

    Mohammed Al-Hashim

    2017-01-01

    Full Text Available Eagle's syndrome (ES is a rare disease in which the styloid process is elongated and compressing adjacent structures. We describe a rare presentation of ES in which the patient presented with facial palsy. Facial palsy as a presentation of ES is very rare. A review of the English literature revealed only one previously reported case. Our case is a 39-year-old male who presented with left facial palsy. He also reported a 9-year history of the classical symptoms of ES. A computed tomography scan with three-dimensional reconstruction confirmed the diagnoses. He was started on conservative management but without significant improvement. Surgical intervention was offered, but the patient refused. It is important for otolaryngologists, dentists, and other specialists who deal with head and neck problems to be able to recognize ES despite its rarity. Although the patient responded to a treatment similar to that of Bell's palsy because of the clinical features and imaging, ES was most likely the cause of his facial palsy.

  10. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  11. Selecting protein families for environmental features based on manifold regularization.

    Science.gov (United States)

    Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

    2014-06-01

    Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data.

  12. The optimal extraction of feature algorithm based on KAZE

    Science.gov (United States)

    Yao, Zheyi; Gu, Guohua; Qian, Weixian; Wang, Pengcheng

    2015-10-01

    As a novel method of 2D features extraction algorithm over the nonlinear scale space, KAZE provide a special method. However, the computation of nonlinear scale space and the construction of KAZE feature vectors are more expensive than the SIFT and SURF significantly. In this paper, the given image is used to build the nonlinear space up to a maximum evolution time through the efficient Additive Operator Splitting (AOS) techniques and the variable conductance diffusion. Changing the parameter can improve the construction of nonlinear scale space and simplify the image conductivities for each dimension space, with the predigest computation. Then, the detection for points of interest can exhibit a maxima of the scale-normalized determinant with the Hessian response in the nonlinear scale space. At the same time, the detection of feature vectors is optimized by the Wavelet Transform method, which can avoid the second Gaussian smoothing in the KAZE Features and cut down the complexity of the algorithm distinctly in the building and describing vectors steps. In this way, the dominant orientation is obtained, similar to SURF, by summing the responses within a sliding circle segment covering an angle of π/3 in the circular area of radius 6σ with a sampling step of size σ one by one. Finally, the extraction in the multidimensional patch at the given scale, centered over the points of interest and rotated to align its dominant orientation to a canonical direction, is able to simplify the description of feature by reducing the description dimensions, just as the PCA-SIFT method. Even though the features are somewhat more expensive to compute than SIFT due to the construction of nonlinear scale space, but compared to SURF, the result revels a step forward in performance in detection, description and application against the previous ways by the following contrast experiments.

  13. Object detection based on improved color and scale invariant features

    Science.gov (United States)

    Chen, Mengyang; Men, Aidong; Fan, Peng; Yang, Bo

    2009-10-01

    A novel object detection method which combines color and scale invariant features is presented in this paper. The detection system mainly adopts the widely used framework of SIFT (Scale Invariant Feature Transform), which consists of both a keypoint detector and descriptor. Although SIFT has some impressive advantages, it is not only computationally expensive, but also vulnerable to color images. To overcome these drawbacks, we employ the local color kernel histograms and Haar Wavelet Responses to enhance the descriptor's distinctiveness and computational efficiency. Extensive experimental evaluations show that the method has better robustness and lower computation costs.

  14. A Fourier-based textural feature extraction procedure

    Science.gov (United States)

    Stromberg, W. D.; Farr, T. G.

    1986-01-01

    A procedure is presented to discriminate and characterize regions of uniform image texture. The procedure utilizes textural features consisting of pixel-by-pixel estimates of the relative emphases of annular regions of the Fourier transform. The utility and derivation of the features are described through presentation of a theoretical justification of the concept followed by a heuristic extension to a real environment. Two examples are provided that validate the technique on synthetic images and demonstrate its applicability to the discrimination of geologic texture in a radar image of a tropical vegetated area.

  15. Gender in facial representations: a contrast-based study of adaptation within and between the sexes.

    Science.gov (United States)

    Oruç, Ipek; Guo, Xiaoyue M; Barton, Jason J S

    2011-01-18

    Face aftereffects are proving to be an effective means of examining the properties of face-specific processes in the human visual system. We examined the role of gender in the neural representation of faces using a contrast-based adaptation method. If faces of different genders share the same representational face space, then adaptation to a face of one gender should affect both same- and different-gender faces. Further, if these aftereffects differ in magnitude, this may indicate distinct gender-related factors in the organization of this face space. To control for a potential confound between physical similarity and gender, we used a Bayesian ideal observer and human discrimination data to construct a stimulus set in which pairs of different-gender faces were equally dissimilar as same-gender pairs. We found that the recognition of both same-gender and different-gender faces was suppressed following a brief exposure of 100 ms. Moreover, recognition was more suppressed for test faces of a different-gender than those of the same-gender as the adaptor, despite the equivalence in physical and psychophysical similarity. Our results suggest that male and female faces likely occupy the same face space, allowing transfer of aftereffects between the genders, but that there are special properties that emerge along gender-defining dimensions of this space.

  16. A regression-based Kansei engineering system based on form feature lines for product form design

    Directory of Open Access Journals (Sweden)

    Yan Xiong

    2016-06-01

    Full Text Available When developing new products, it is important for a designer to understand users’ perceptions and develop product form with the corresponding perceptions. In order to establish the mapping between users’ perceptions and product design features effectively, in this study, we presented a regression-based Kansei engineering system based on form feature lines for product form design. First according to the characteristics of design concept representation, product form features–product form feature lines were defined. Second, Kansei words were chosen to describe image perceptions toward product samples. Then, multiple linear regression and support vector regression were used to construct the models, respectively, that predicted users’ image perceptions. Using mobile phones as experimental samples, Kansei prediction models were established based on the front view form feature lines of the samples. From the experimental results, these two predict models were of good adaptability. But in contrast to multiple linear regression, the predict performance of support vector regression model was better, and support vector regression is more suitable for form regression prediction. The results of the case showed that the proposed method provided an effective means for designers to manipulate product features as a whole, and it can optimize Kansei model and improve practical values.

  17. Idiopathic ophthalmodynia and idiopathic rhinalgia: two topographic facial pain syndromes.

    Science.gov (United States)

    Pareja, Juan A; Cuadrado, María L; Porta-Etessam, Jesús; Fernández-de-las-Peñas, César; Gili, Pablo; Caminero, Ana B; Cebrián, José L

    2010-09-01

    To describe 2 topographic facial pain conditions with the pain clearly localized in the eye (idiopathic ophthalmodynia) or in the nose (idiopathic rhinalgia), and to propose their distinction from persistent idiopathic facial pain. Persistent idiopathic facial pain, burning mouth syndrome, atypical odontalgia, and facial arthromyalgia are idiopathic facial pain syndromes that have been separated according to topographical criteria. Still, some other facial pain syndromes might have been veiled under the broad term of persistent idiopathic facial pain. Through a 10-year period we have studied all patients referred to our neurological clinic because of facial pain of unknown etiology that might deviate from all well-characterized facial pain syndromes. In a group of patients we have identified 2 consistent clinical pictures with pain precisely located either in the eye (n=11) or in the nose (n=7). Clinical features resembled those of other localized idiopathic facial syndromes, the key differences relying on the topographic distribution of the pain. Both idiopathic ophthalmodynia and idiopathic rhinalgia seem specific pain syndromes with a distinctive location, and may deserve a nosologic status just as other focal pain syndromes of the face. Whether all such focal syndromes are topographic variants of persistent idiopathic facial pain or independent disorders remains a controversial issue.

  18. Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

    International Nuclear Information System (INIS)

    Wang Xiaojia; Mao Qirong; Zhan Yongzhao

    2008-01-01

    There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction

  19. A Feature Fusion Based Forecasting Model for Financial Time Series

    Science.gov (United States)

    Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

    2014-01-01

    Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

  20. Clustering-based Feature Learning on Variable Stars

    Science.gov (United States)

    Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

    2016-04-01

    The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

  1. Limits in feature-based attention to multiple colors.

    Science.gov (United States)

    Liu, Taosheng; Jigo, Michael

    2017-11-01

    Attention to a feature enhances the sensory representation of that feature. Although much has been learned about the properties of attentional modulation when attending to a single feature, the effectiveness of attending to multiple features is not well understood. We investigated this question in a series of experiments using a color-detection task while varying the number of attended colors in a cueing paradigm. Observers were shown either a single cue, two cues, or no cue (baseline) before detecting a coherent color target. We measured detection threshold by varying the coherence level of the target. Compared to the baseline condition, we found consistent facilitation of detection performance in the one-cue and two-cue conditions, but performance in the two-cue condition was lower than that in the one-cue condition. In the final experiment, we presented a 50% valid cue to emulate the situation in which observers were only able to attend a single color in the two-cue condition, and found equivalent detection thresholds with the standard two-cue condition. These results indicate a limit in attending to two colors and further imply that observers could effectively attend a single color at a time. Such a limit is likely due to an inability to maintain multiple active attentional templates for colors.

  2. Emotion of Physiological Signals Classification Based on TS Feature Selection

    Institute of Scientific and Technical Information of China (English)

    Wang Yujing; Mo Jianlin

    2015-01-01

    This paper propose a method of TS-MLP about emotion recognition of physiological signal.It can recognize emotion successfully by Tabu search which selects features of emotion’s physiological signals and multilayer perceptron that is used to classify emotion.Simulation shows that it has achieved good emotion classification performance.

  3. FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS

    Directory of Open Access Journals (Sweden)

    F. Maiwald

    2018-05-01

    Full Text Available This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings. It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

  4. Microarray-based large scale detection of single feature ...

    Indian Academy of Sciences (India)

    2015-12-08

    Dec 8, 2015 ... mental stages was used to identify single feature polymorphisms (SFPs). ... on a high-density oligonucleotide expression array in which. ∗ ..... The sign (+/−) with SFPs indicates direction of polymorphism. In the. (−) sign (i.e. ...

  5. CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

    International Nuclear Information System (INIS)

    Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

    2016-01-01

    The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline

  6. CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

    Energy Technology Data Exchange (ETDEWEB)

    Mackenzie, Cristóbal; Pichara, Karim [Computer Science Department, Pontificia Universidad Católica de Chile, Santiago (Chile); Protopapas, Pavlos [Institute for Applied Computational Science, Harvard University, Cambridge, MA (United States)

    2016-04-01

    The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

  7. Feature-based engineering of compensations in web service environment

    DEFF Research Database (Denmark)

    Schaefer, Michael; Dolog, Peter

    2009-01-01

    In this paper, we introduce a product line approach for developing Web services with extended compensation capabilities. We adopt a feature modelling approach in order to describe variable and common compensation properties of Web service variants, as well as service consumer application...

  8. Sequence-based feature prediction and annotation of proteins

    DEFF Research Database (Denmark)

    Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea

    2009-01-01

    A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....

  9. Genetic determinants of facial clefting

    DEFF Research Database (Denmark)

    Jugessur, Astanand; Shi, Min; Gjessing, Håkon Kristian

    2009-01-01

    BACKGROUND: Facial clefts are common birth defects with a strong genetic component. To identify fetal genetic risk factors for clefting, 1536 SNPs in 357 candidate genes were genotyped in two population-based samples from Scandinavia (Norway: 562 case-parent and 592 control-parent triads; Denmark...

  10. Variant facial artery in the submandibular region.

    Science.gov (United States)

    Vadgaonkar, Rajanigandha; Rai, Rajalakshmi; Prabhu, Latha V; Bv, Murlimanju; Samapriya, Neha

    2012-07-01

    Facial artery has been considered to be the most important vascular pedicle in facial rejuvenation procedures and submandibular gland (SMG) resection. It usually arises from the external carotid artery and passes from the carotid to digastric triangle, deep to the posterior belly of digastric muscle, and lodges in a groove at the posterior end of the SMG. It then passes between SMG and the mandible to reach the face after winding around the base of the mandible. During a routine dissection, in a 62-year-old female cadaver, in Kasturba Medical College Mangalore, an unusual pattern in the cervical course of facial artery was revealed. The right facial artery was found to pierce the whole substance of the SMG before winding around the lower border of the mandible to enter the facial region. Awareness of existence of such a variant and its comparison to the normal anatomy will be useful to oral and maxillofacial surgeons.

  11. Does Facial Amimia Impact the Recognition of Facial Emotions? An EMG Study in Parkinson’s Disease

    Science.gov (United States)

    Argaud, Soizic; Delplanque, Sylvain; Houvenaghel, Jean-François; Auffret, Manon; Duprez, Joan; Vérin, Marc; Grandjean, Didier; Sauleau, Paul

    2016-01-01

    According to embodied simulation theory, understanding other people’s emotions is fostered by facial mimicry. However, studies assessing the effect of facial mimicry on the recognition of emotion are still controversial. In Parkinson’s disease (PD), one of the most distinctive clinical features is facial amimia, a reduction in facial expressiveness, but patients also show emotional disturbances. The present study used the pathological model of PD to examine the role of facial mimicry on emotion recognition by investigating EMG responses in PD patients during a facial emotion recognition task (anger, joy, neutral). Our results evidenced a significant decrease in facial mimicry for joy in PD, essentially linked to the absence of reaction of the zygomaticus major and the orbicularis oculi muscles in response to happy avatars, whereas facial mimicry for expressions of anger was relatively preserved. We also confirmed that PD patients were less accurate in recognizing positive and neutral facial expressions and highlighted a beneficial effect of facial mimicry on the recognition of emotion. We thus provide additional arguments for embodied simulation theory suggesting that facial mimicry is a potential lever for therapeutic actions in PD even if it seems not to be necessarily required in recognizing emotion as such. PMID:27467393

  12. Feature-Based Analysis of Plasma-Based Particle Acceleration Data

    Energy Technology Data Exchange (ETDEWEB)

    Rubel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Geddes, Cameron G. R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Min [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cormier-Michel, Estelle [Tech-X Corp., Boulder, CO (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-02-01

    Plasma-based particle accelerators can produce and sustain thousands of times stronger acceleration fields than conventional particle accelerators, providing a potential solution to the problem of the growing size and cost of conventional particle accelerators. To facilitate scientific knowledge discovery from the ever growing collections of accelerator simulation data generated by accelerator physicists to investigate next-generation plasma-based particle accelerator designs, we describe a novel approach for automatic detection and classification of particle beams and beam substructures due to temporal differences in the acceleration process, here called acceleration features. The automatic feature detection in combination with a novel visualization tool for fast, intuitive, query-based exploration of acceleration features enables an effective top-down data exploration process, starting from a high-level, feature-based view down to the level of individual particles. We describe the application of our analysis in practice to analyze simulations of single pulse and dual and triple colliding pulse accelerator designs, and to study the formation and evolution of particle beams, to compare substructures of a beam and to investigate transverse particle loss.

  13. Greater perceptual sensitivity to happy facial expression.

    Science.gov (United States)

    Maher, Stephen; Ekstrom, Tor; Chen, Yue

    2014-01-01

    Perception of subtle facial expressions is essential for social functioning; yet it is unclear if human perceptual sensitivities differ in detecting varying types of facial emotions. Evidence diverges as to whether salient negative versus positive emotions (such as sadness versus happiness) are preferentially processed. Here, we measured perceptual thresholds for the detection of four types of emotion in faces--happiness, fear, anger, and sadness--using psychophysical methods. We also evaluated the association of the perceptual performances with facial morphological changes between neutral and respective emotion types. Human observers were highly sensitive to happiness compared with the other emotional expressions. Further, this heightened perceptual sensitivity to happy expressions can be attributed largely to the emotion-induced morphological change of a particular facial feature (end-lip raise).

  14. Automatic facial animation parameters extraction in MPEG-4 visual communication

    Science.gov (United States)

    Yang, Chenggen; Gong, Wanwei; Yu, Lu

    2002-01-01

    Facial Animation Parameters (FAPs) are defined in MPEG-4 to animate a facial object. The algorithm proposed in this paper to extract these FAPs is applied to very low bit-rate video communication, in which the scene is composed of a head-and-shoulder object with complex background. This paper addresses the algorithm to automatically extract all FAPs needed to animate a generic facial model, estimate the 3D motion of head by points. The proposed algorithm extracts human facial region by color segmentation and intra-frame and inter-frame edge detection. Facial structure and edge distribution of facial feature such as vertical and horizontal gradient histograms are used to locate the facial feature region. Parabola and circle deformable templates are employed to fit facial feature and extract a part of FAPs. A special data structure is proposed to describe deformable templates to reduce time consumption for computing energy functions. Another part of FAPs, 3D rigid head motion vectors, are estimated by corresponding-points method. A 3D head wire-frame model provides facial semantic information for selection of proper corresponding points, which helps to increase accuracy of 3D rigid object motion estimation.

  15. Feature-based and object-based attention orientation during short-term memory maintenance.

    Science.gov (United States)

    Ku, Yixuan

    2015-12-01

    Top-down attention biases the short-term memory (STM) processing at multiple stages. Orienting attention during the maintenance period of STM by a retrospective cue (retro-cue) strengthens the representation of the cued item and improves the subsequent STM performance. In a recent article, Backer et al. (Backer KC, Binns MA, Alain C. J Neurosci 35: 1307-1318, 2015) extended these findings from the visual to the auditory domain and combined electroencephalography to dissociate neural mechanisms underlying feature-based and object-based attention orientation. Both event-related potentials and neural oscillations explained the behavioral benefits of retro-cues and favored the theory that feature-based and object-based attention orientation were independent. Copyright © 2015 the American Physiological Society.

  16. Gamelan Music Onset Detection based on Spectral Features

    Directory of Open Access Journals (Sweden)

    Yoyon Kusnendar Suprapto

    2013-03-01

    Full Text Available This research detects onsets of percussive instruments by examining the performance on the sound signals of gamelan instruments as one of traditional music instruments in Indonesia. Onset plays important role in determining musical rythmic structure, like beat, tempo, and is highly required in many applications of music information retrieval. There are four onset detection methods compared that employ spectral features, such as magnitude, phase, and the combination of both, which are phase slope (PS, weighted phase deviation (WPD, spectral flux (SF, and rectified complex domain (RCD. These features are extracted by representing the sound signals into time-frequency domain using overlapped Short-time Fourier Transform (STFT and varying the window length. Onset detection functions are processed through peak-picking using dynamic threshold. The results showed that by using suitable window length and parameter setting of dynamic threshold, F-measure which is greater than 0.80 can be obtained for certain methods.

  17. GA Based Optimal Feature Extraction Method for Functional Data Classification

    OpenAIRE

    Jun Wan; Zehua Chen; Yingwu Chen; Zhidong Bai

    2010-01-01

    Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper...

  18. Shape based automated detection of pulmonary nodules with surface feature based false positive reduction

    International Nuclear Information System (INIS)

    Nomura, Y.; Itoh, H.; Masutani, Y.; Ohtomo, K.; Maeda, E.; Yoshikawa, T.; Hayashi, N.

    2007-01-01

    We proposed a shape based automated detection of pulmonary nodules with surface feature based false positive (FP) reduction. In the proposed system, the FP existing in internal of vessel bifurcation is removed using extracted surface of vessels and nodules. From the validation with 16 chest CT scans, we find that the proposed CAD system achieves 18.7 FPs/scan at 90% sensitivity, and 7.8 FPs/scan at 80% sensitivity. (orig.)

  19. The face is not an empty canvas: how facial expressions interact with facial appearance.

    Science.gov (United States)

    Hess, Ursula; Adams, Reginald B; Kleck, Robert E

    2009-12-12

    Faces are not simply blank canvases upon which facial expressions write their emotional messages. In fact, facial appearance and facial movement are both important social signalling systems in their own right. We here provide multiple lines of evidence for the notion that the social signals derived from facial appearance on the one hand and facial movement on the other interact in a complex manner, sometimes reinforcing and sometimes contradicting one another. Faces provide information on who a person is. Sex, age, ethnicity, personality and other characteristics that can define a person and the social group the person belongs to can all be derived from the face alone. The present article argues that faces interact with the perception of emotion expressions because this information informs a decoder's expectations regarding an expresser's probable emotional reactions. Facial appearance also interacts more directly with the interpretation of facial movement because some of the features that are used to derive personality or sex information are also features that closely resemble certain emotional expressions, thereby enhancing or diluting the perceived strength of particular expressions.

  20. Facial paresis in patients with mesial temporal sclerosis: clinical and quantitative MRI-based evidence of widespread disease.

    Science.gov (United States)

    Lin, Katia; Carrete, Henrique; Lin, Jaime; de Oliveira, Pedro Alessandro Leite; Caboclo, Luis Otávio Sales Ferreira; Sakamoto, Américo Ceiki; Yacubian, Elza Márcia Targas

    2007-08-01

    To assess the frequency and significance of facial paresis (FP) in a well-defined cohort of mesial temporal lobe epilepsy (MTLE) patients. One hundred consecutive patients with MRI findings consistent with mesial temporal sclerosis (MTS) and concordant electroclinical data underwent facial motor examination at rest, with voluntary expression, and with spontaneous smiling. Hippocampal, amygdaloid, and temporopolar (TP) volumetric measures were acquired. Thirty healthy subjects, matched according to age and sex, were taken as controls. Central-type FP was found in 46 patients. In 41 (89%) of 46, it was visualized at rest, with voluntary and emotional expression characterizing true facial motor paresis. In 33 (72%) of 46 patients, FP was contralateral to the side of MTS. By using a 2-SD cutoff from the mean of normal controls, we found reduction in TP volume ipsilateral to MTS in 61% of patients with FP and in 33% of those without (p = 0.01). Febrile seizures as initial precipitating injury (IPI) were observed in 34% of the patients and were classified as complex in 12 (26%) of 46 of those with FP and in five (9%) of 54 of those without (p = 0.02). The presence of FP was significantly associated with a shorter latent period and younger age at onset of habitual seizures, in particular, with secondarily generalized tonic-clonic seizures. Facial paresis is a reliable lateralizing sign in MTLE and was associated with history of complex febrile seizures as IPI, younger age at onset of disease, and atrophy of temporal pole ipsilateral to MTS, indicating more widespread disease.

  1. Real Time Facial Expression Recognition Using Webcam and SDK Affectiva

    Directory of Open Access Journals (Sweden)

    Martin Magdin

    2018-06-01

    Full Text Available Facial expression is an essential part of communication. For this reason, the issue of human emotions evaluation using a computer is a very interesting topic, which has gained more and more attention in recent years. It is mainly related to the possibility of applying facial expression recognition in many fields such as HCI, video games, virtual reality, and analysing customer satisfaction etc. Emotions determination (recognition process is often performed in 3 basic phases: face detection, facial features extraction, and last stage - expression classification. Most often you can meet the so-called Ekman’s classification of 6 emotional expressions (or 7 - neutral expression as well as other types of classification - the Russell circular model, which contains up to 24 or the Plutchik’s Wheel of Emotions. The methods used in the three phases of the recognition process have not only improved over the last 60 years, but new methods and algorithms have also emerged that can determine the ViolaJones detector with greater accuracy and lower computational demands. Therefore, there are currently various solutions in the form of the Software Development Kit (SDK. In this publication, we point to the proposition and creation of our system for real-time emotion classification. Our intention was to create a system that would use all three phases of the recognition process, work fast and stable in real time. That’s why we’ve decided to take advantage of existing Affectiva SDKs. By using the classic webcamera we can detect facial landmarks on the image automatically using the Software Development Kit (SDK from Affectiva. Geometric feature based approach is used for feature extraction. The distance between landmarks is used as a feature, and for selecting an optimal set of features, the brute force method is used. The proposed system uses neural network algorithm for classification. The proposed system recognizes 6 (respectively 7 facial expressions

  2. SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

    Directory of Open Access Journals (Sweden)

    Demidova Liliya

    2017-01-01

    Full Text Available The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers on the base of the modified PSO algorithm, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.

  3. Automatic brain MR image denoising based on texture feature-based artificial neural networks.

    Science.gov (United States)

    Chang, Yu-Ning; Chang, Herng-Hua

    2015-01-01

    Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

  4. A Feature Subtraction Method for Image Based Kinship Verification under Uncontrolled Environments

    DEFF Research Database (Denmark)

    Duan, Xiaodong; Tan, Zheng-Hua

    2015-01-01

    The most fundamental problem of local feature based kinship verification methods is that a local feature can capture the variations of environmental conditions and the differences between two persons having a kin relation, which can significantly decrease the performance. To address this problem...... the feature distance between face image pairs with kinship and maximize the distance between non-kinship pairs. Based on the subtracted feature, the verification is realized through a simple Gaussian based distance comparison method. Experiments on two public databases show that the feature subtraction method...

  5. Logic based feature detection on incore neutron spectra

    International Nuclear Information System (INIS)

    Bende-Farkas, S.; Kiss, S.; Racz, A.

    1992-09-01

    A methodology is proposed to investigate neutron spectra in such a way which is similar to human thinking. The goal was to save experts from tedious, mechanical tasks of browsing a large amount of signals in order to recognize changes in the underlying mechanisms. The general framework for detecting features of incore neutron spectra with a rulebased methodology is presented. As an example, the meaningful peaks in the APSDs are determined. This method is a part of a wider project to develop a noise diagnostic expert system. (R.P.) 6 refs.; 6 figs.; 1 tab

  6. SAR Image Classification Based on Its Texture Features

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  7. Document localization algorithms based on feature points and straight lines

    Science.gov (United States)

    Skoryukina, Natalya; Shemiakina, Julia; Arlazarov, Vladimir L.; Faradjev, Igor

    2018-04-01

    The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.

  8. Conditional Mutual Information Based Feature Selection for Classification Task

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana; Somol, Petr; Haindl, Michal; Pudil, Pavel

    2007-01-01

    Roč. 45, č. 4756 (2007), s. 417-426 ISSN 0302-9743 R&D Projects: GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Pattern classification * feature selection * conditional mutual information * text categorization Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.402, year: 2005

  9. Biometric identification based on feature fusion with PCA and SVM

    Science.gov (United States)

    Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

    2018-04-01

    Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

  10. A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series

    Directory of Open Access Journals (Sweden)

    Keke Zhang

    2018-01-01

    Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.

  11. Facial Transplantation Surgery Introduction

    OpenAIRE

    Eun, Seok-Chan

    2015-01-01

    Severely disfiguring facial injuries can have a devastating impact on the patient's quality of life. During the past decade, vascularized facial allotransplantation has progressed from an experimental possibility to a clinical reality in the fields of disease, trauma, and congenital malformations. This technique may now be considered a viable option for repairing complex craniofacial defects for which the results of autologous reconstruction remain suboptimal. Vascularized facial allotranspla...

  12. Marker optimization for facial motion acquisition and deformation.

    Science.gov (United States)

    Le, Binh H; Zhu, Mingyang; Deng, Zhigang

    2013-11-01

    A long-standing problem in marker-based facial motion capture is what are the optimal facial mocap marker layouts. Despite its wide range of potential applications, this problem has not yet been systematically explored to date. This paper describes an approach to compute optimized marker layouts for facial motion acquisition as optimization of characteristic control points from a set of high-resolution, ground-truth facial mesh sequences. Specifically, the thin-shell linear deformation model is imposed onto the example pose reconstruction process via optional hard constraints such as symmetry and multiresolution constraints. Through our experiments and comparisons, we validate the effectiveness, robustness, and accuracy of our approach. Besides guiding minimal yet effective placement of facial mocap markers, we also describe and demonstrate its two selected applications: marker-based facial mesh skinning and multiresolution facial performance capture.

  13. Three-Class Mammogram Classification Based on Descriptive CNN Features

    Directory of Open Access Journals (Sweden)

    M. Mohsin Jadoon

    2017-01-01

    Full Text Available In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases. In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW and convolutional neural network-curvelet transform (CNN-CT. An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE. In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT, while in the second method discrete curvelet transform (DCT is used. In both methods, dense scale invariant feature (DSIFT for all subbands is extracted. Input data matrix containing these subband features of all the mammogram patches is created that is processed as input to convolutional neural network (CNN. Softmax layer and support vector machine (SVM layer are used to train CNN for classification. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. CNN-DW and CNN-CT have achieved accuracy rate of 81.83% and 83.74%, respectively. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques.

  14. Binary pattern analysis for 3D facial action unit detection

    NARCIS (Netherlands)

    Sandbach, Georgia; Zafeiriou, Stefanos; Pantic, Maja

    2012-01-01

    In this paper we propose new binary pattern features for use in the problem of 3D facial action unit (AU) detection. Two representations of 3D facial geometries are employed, the depth map and the Azimuthal Projection Distance Image (APDI). To these the traditional Local Binary Pattern is applied,

  15. Quantitative facial asymmetry: using three-dimensional photogrammetry to measure baseline facial surface symmetry.

    Science.gov (United States)

    Taylor, Helena O; Morrison, Clinton S; Linden, Olivia; Phillips, Benjamin; Chang, Johnny; Byrne, Margaret E; Sullivan, Stephen R; Forrest, Christopher R

    2014-01-01

    subjectively, can be easily and reproducibly measured using three-dimensional photogrammetry. The RMSD for facial asymmetry of healthy volunteers clusters at approximately 0.80 ± 0.24 mm. Patients with facial asymmetry due to a pathologic process can be differentiated from normative facial asymmetry based on their RMSDs.

  16. [Facial tics and spasms].

    Science.gov (United States)

    Potgieser, Adriaan R E; van Dijk, J Marc C; Elting, Jan Willem J; de Koning-Tijssen, Marina A J

    2014-01-01

    Facial tics and spasms are socially incapacitating, but effective treatment is often available. The clinical picture is sufficient for distinguishing between the different diseases that cause this affliction.We describe three cases of patients with facial tics or spasms: one case of tics, which are familiar to many physicians; one case of blepharospasms; and one case of hemifacial spasms. We discuss the differential diagnosis and the treatment possibilities for facial tics and spasms. Early diagnosis and treatment is important, because of the associated social incapacitation. Botulin toxin should be considered as a treatment option for facial tics and a curative neurosurgical intervention should be considered for hemifacial spasms.

  17. Part-based Pedestrian Detection and Feature-based Tracking for Driver Assistance

    DEFF Research Database (Denmark)

    Prioletti, Antonio; Møgelmose, Andreas; Grislieri, Paolo

    2013-01-01

    Detecting pedestrians is still a challenging task for automotive vision systems due to the extreme variability of targets, lighting conditions, occlusion, and high-speed vehicle motion. Much research has been focused on this problem in the last ten years and detectors based on classifiers have...... on a prototype vehicle and offers high performance in terms of several metrics, such as detection rate, false positives per hour, and frame rate. The novelty of this system relies on the combination of a HOG part-based approach, tracking based on a specific optimized feature, and porting on a real prototype....

  18. Perceived functional impact of abnormal facial appearance.

    Science.gov (United States)

    Rankin, Marlene; Borah, Gregory L

    2003-06-01

    Functional facial deformities are usually described as those that impair respiration, eating, hearing, or speech. Yet facial scars and cutaneous deformities have a significant negative effect on social functionality that has been poorly documented in the scientific literature. Insurance companies are declining payments for reconstructive surgical procedures for facial deformities caused by congenital disabilities and after cancer or trauma operations that do not affect mechanical facial activity. The purpose of this study was to establish a large, sample-based evaluation of the perceived social functioning, interpersonal characteristics, and employability indices for a range of facial appearances (normal and abnormal). Adult volunteer evaluators (n = 210) provided their subjective perceptions based on facial physical appearance, and an analysis of the consequences of facial deformity on parameters of preferential treatment was performed. A two-group comparative research design rated the differences among 10 examples of digitally altered facial photographs of actual patients among various age and ethnic groups with "normal" and "abnormal" congenital deformities or posttrauma scars. Photographs of adult patients with observable congenital and posttraumatic deformities (abnormal) were digitally retouched to eliminate the stigmatic defects (normal). The normal and abnormal photographs of identical patients were evaluated by the large sample study group on nine parameters of social functioning, such as honesty, employability, attractiveness, and effectiveness, using a visual analogue rating scale. Patients with abnormal facial characteristics were rated as significantly less honest (p = 0.007), less employable (p = 0.001), less trustworthy (p = 0.01), less optimistic (p = 0.001), less effective (p = 0.02), less capable (p = 0.002), less intelligent (p = 0.03), less popular (p = 0.001), and less attractive (p = 0.001) than were the same patients with normal facial

  19. On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis

    Directory of Open Access Journals (Sweden)

    Asriyanti Indah Pratiwi

    2018-01-01

    Full Text Available Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge. In order to handle an enormous number of features and provide better sentiment classification, an information-based feature selection and classification are proposed. The proposed method reduces more than 90% unnecessary features while the proposed classification scheme achieves 96% accuracy of sentiment classification. From the experimental results, it can be concluded that the combination of proposed feature selection and classification achieves the best performance so far.

  20. Artificially intelligent recognition of Arabic speaker using voice print-based local features

    Science.gov (United States)

    Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

    2016-11-01

    Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

  1. [Improvement of rosacea treatment based on the morphological and functional features of the skin].

    Science.gov (United States)

    Tsiskarishvili, N V; Katsitadze, A G; Tsiskarishvili, Ts I

    2013-10-01

    Rosacea - a widespread disease sometimes aleak with severe complications, mainly affecting the skin. Irrational and inadequate treatment leads to chronicity of diseases and psychosocial disadaptation of patients. Lately, a clear upward trend in the number of patients in whom in the process of complex treatment manifestations (with the varying degrees of severity) of impaired barrier function of the skin are observed and they need the protection and restoration of the damaged stratum corneum. In patients with rosacea in order to study the function of the facial skin's horny layer we used the skin analyzer BIA (bioimpedance analysis, which in duration of 6 seconds determines the moisture content, oiliness and the softness of the skin) and significant deviations from the norm (decrease in moisture content, fatness and increased roughness) was revealed. These changes were most clearly pronounced in patients with steroid rosacea. To restore the skin barrier the drug "Episofit A" (Laboratory of Evolutionary Dermatology, France) has been used (1-2 times a day for 6 weeks). Evaluation of treatment efficacy was conducted every 2 weeks by means of a scale from 0 to 5 for parameters of dryness, erythema, peeling and expression of subjective feelings. In accordance with received results, using of Episofit A emulsion, especially on the baсkground of long-term treatment with topical steroids, had a pronounced therapeutic effect. Thus, treatment of patients with consideration of morphological and functional features of facial skin, helps to improve the results traditional therapy, and the drug is highly effective means of the new direction in skin care - corneotherapy aimed to reconstruct and protect damaged stratum corneum.

  2. Learner features in a New Corpus-based Swahili dictionary ...

    African Journals Online (AJOL)

    As far as traditionally published Swahili language dictionaries are concerned, throughout the long history of Swahili lexicography, most new dictionaries were based on their predecessors. Thus far the only innovative traditionally printed corpus-based dictionary has been published by Finnish scholars (Abdulla et al. 2002).

  3. Efficient Divide-And-Conquer Classification Based on Feature-Space Decomposition

    OpenAIRE

    Guo, Qi; Chen, Bo-Wei; Jiang, Feng; Ji, Xiangyang; Kung, Sun-Yuan

    2015-01-01

    This study presents a divide-and-conquer (DC) approach based on feature space decomposition for classification. When large-scale datasets are present, typical approaches usually employed truncated kernel methods on the feature space or DC approaches on the sample space. However, this did not guarantee separability between classes, owing to overfitting. To overcome such problems, this work proposes a novel DC approach on feature spaces consisting of three steps. Firstly, we divide the feature ...

  4. Comparison of features response in texture-based iris segmentation

    CSIR Research Space (South Africa)

    Bachoo, A

    2009-03-01

    Full Text Available the Fisher linear discriminant and the iris region of interest is extracted. Four texture description methods are compared for segmenting iris texture using a region based pattern classification approach: Grey Level Co-occurrence Matrix (GLCM), Discrete...

  5. A Study of Moment Based Features on Handwritten Digit Recognition

    Directory of Open Access Journals (Sweden)

    Pawan Kumar Singh

    2016-01-01

    Full Text Available Handwritten digit recognition plays a significant role in many user authentication applications in the modern world. As the handwritten digits are not of the same size, thickness, style, and orientation, therefore, these challenges are to be faced to resolve this problem. A lot of work has been done for various non-Indic scripts particularly, in case of Roman, but, in case of Indic scripts, the research is limited. This paper presents a script invariant handwritten digit recognition system for identifying digits written in five popular scripts of Indian subcontinent, namely, Indo-Arabic, Bangla, Devanagari, Roman, and Telugu. A 130-element feature set which is basically a combination of six different types of moments, namely, geometric moment, moment invariant, affine moment invariant, Legendre moment, Zernike moment, and complex moment, has been estimated for each digit sample. Finally, the technique is evaluated on CMATER and MNIST databases using multiple classifiers and, after performing statistical significance tests, it is observed that Multilayer Perceptron (MLP classifier outperforms the others. Satisfactory recognition accuracies are attained for all the five mentioned scripts.

  6. GAIN RATIO BASED FEATURE SELECTION METHOD FOR PRIVACY PRESERVATION

    Directory of Open Access Journals (Sweden)

    R. Praveena Priyadarsini

    2011-04-01

    Full Text Available Privacy-preservation is a step in data mining that tries to safeguard sensitive information from unsanctioned disclosure and hence protecting individual data records and their privacy. There are various privacy preservation techniques like k-anonymity, l-diversity and t-closeness and data perturbation. In this paper k-anonymity privacy protection technique is applied to high dimensional datasets like adult and census. since, both the data sets are high dimensional, feature subset selection method like Gain Ratio is applied and the attributes of the datasets are ranked and low ranking attributes are filtered to form new reduced data subsets. K-anonymization privacy preservation technique is then applied on reduced datasets. The accuracy of the privacy preserved reduced datasets and the original datasets are compared for their accuracy on the two functionalities of data mining namely classification and clustering using naïve Bayesian and k-means algorithm respectively. Experimental results show that classification and clustering accuracy are comparatively the same for reduced k-anonym zed datasets and the original data sets.

  7. Camouflaged target detection based on polarized spectral features

    Science.gov (United States)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  8. AREAL FEATURE MATCHING BASED ON SIMILARITY USING CRITIC METHOD

    Directory of Open Access Journals (Sweden)

    J. Kim

    2015-10-01

    Full Text Available In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

  9. Areal Feature Matching Based on Similarity Using Critic Method

    Science.gov (United States)

    Kim, J.; Yu, K.

    2015-10-01

    In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

  10. Interference among the Processing of Facial Emotion, Face Race, and Face Gender

    OpenAIRE

    Li, Yongna; Tse, Chi-Shing

    2016-01-01

    People are able to simultaneously process multiple dimensions of facial properties. Facial processing models are based on the processing of facial properties. This paper examined the processing of facial emotion, face race and face gender using categorization tasks. The same set of Chinese, White and Black faces, each posing a neutral, happy or angry expression, was used in three experiments. Facial emotion interfered with face race in all the tasks. The interaction of face race and face gend...

  11. Facial talon cusps.

    LENUS (Irish Health Repository)

    McNamara, T

    1997-12-01

    This is a report of two patients with isolated facial talon cusps. One occurred on a permanent mandibular central incisor; the other on a permanent maxillary canine. The locations of these talon cusps suggests that the definition of a talon cusp include teeth in addition to the incisor group and be extended to include the facial aspect of teeth.

  12. Textual and shape-based feature extraction and neuro-fuzzy classifier for nuclear track recognition

    Science.gov (United States)

    Khayat, Omid; Afarideh, Hossein

    2013-04-01

    Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.

  13. Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

    Science.gov (United States)

    Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

    2017-01-01

    Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

  14. Feature-Learning-Based Printed Circuit Board Inspection via Speeded-Up Robust Features and Random Forest

    Directory of Open Access Journals (Sweden)

    Eun Hye Yuk

    2018-06-01

    Full Text Available With the coming of the 4th industrial revolution era, manufacturers produce high-tech products. As the production process is refined, inspection technologies become more important. Specifically, the inspection of a printed circuit board (PCB, which is an indispensable part of electronic products, is an essential step to improve the quality of the process and yield. Image processing techniques are utilized for inspection, but there are limitations because the backgrounds of images are different and the kinds of defects increase. In order to overcome these limitations, methods based on machine learning have been used recently. These methods can inspect without a normal image by learning fault patterns. Therefore, this paper proposes a method can detect various types of defects using machine learning. The proposed method first extracts features through speeded-up robust features (SURF, then learns the fault pattern and calculates probabilities. After that, we generate a weighted kernel density estimation (WKDE map weighted by the probabilities to consider the density of the features. Because the probability of the WKDE map can detect an area where the defects are concentrated, it improves the performance of the inspection. To verify the proposed method, we apply the method to PCB images and confirm the performance of the method.

  15. A facial marker in facial wasting rehabilitation.

    Science.gov (United States)

    Rauso, Raffaele; Tartaro, Gianpaolo; Freda, Nicola; Rusciani, Antonio; Curinga, Giuseppe

    2012-02-01

    Facial lipoatrophy is one of the most distressing manifestation for HIV patients. It can be stigmatizing, severely affecting quality of life and self-esteem, and it may result in reduced antiretroviral adherence. Several filling techniques have been proposed in facial wasting restoration, with different outcomes. The aim of this study is to present a triangular area that is useful to fill in facial wasting rehabilitation. Twenty-eight HIV patients rehabilitated for facial wasting were enrolled in this study. Sixteen were rehabilitated with a non-resorbable filler and twelve with structural fat graft harvested from lipohypertrophied areas. A photographic pre-operative and post-operative evaluation was performed by the patients and by two plastic surgeons who were "blinded." The filled area, in both patients rehabilitated with structural fat grafts or non-resorbable filler, was a triangular area of depression identified between the nasolabial fold, the malar arch, and the line that connects these two anatomical landmarks. The cosmetic result was evaluated after three months after the last filling procedure in the non-resorbable filler group and after three months post-surgery in the structural fat graft group. The mean patient satisfaction score was 8.7 as assessed with a visual analogue scale. The mean score for blinded evaluators was 7.6. In this study the authors describe a triangular area of the face, between the nasolabial fold, the malar arch, and the line that connects these two anatomical landmarks, where a good aesthetic facial restoration in HIV patients with facial wasting may be achieved regardless of which filling technique is used.

  16. Advances in facial reanimation.

    Science.gov (United States)

    Tate, James R; Tollefson, Travis T

    2006-08-01

    Facial paralysis often has a significant emotional impact on patients. Along with the myriad of new surgical techniques in managing facial paralysis comes the challenge of selecting the most effective procedure for the patient. This review delineates common surgical techniques and reviews state-of-the-art techniques. The options for dynamic reanimation of the paralyzed face must be examined in the context of several patient factors, including age, overall health, and patient desires. The best functional results are obtained with direct facial nerve anastomosis and interpositional nerve grafts. In long-standing facial paralysis, temporalis muscle transfer gives a dependable and quick result. Microvascular free tissue transfer is a reliable technique with reanimation potential whose results continue to improve as microsurgical expertise increases. Postoperative results can be improved with ancillary soft tissue procedures, as well as botulinum toxin. The paper provides an overview of recent advances in facial reanimation, including preoperative assessment, surgical reconstruction options, and postoperative management.

  17. A Mean-Shift-Based Feature Descriptor for Wide Baseline Stereo Matching

    Directory of Open Access Journals (Sweden)

    Yiwen Dou

    2015-01-01

    Full Text Available We propose a novel Mean-Shift-based building approach in wide baseline. Initially, scale-invariance feature transform (SIFT approach is used to extract relatively stable feature points. As to each matching SIFT feature point, it needs a reasonable neighborhood range so as to choose feature points set. Subsequently, in view of selecting repeatable and high robust feature points, Mean-Shift controls corresponding feature scale. At last, our approach is employed to depth image acquirement in wide baseline and Graph Cut algorithm optimizes disparity information. Compared with the existing methods such as SIFT, speeded up robust feature (SURF, and normalized cross-correlation (NCC, the presented approach has the advantages of higher robustness and accuracy rate. Experimental results on low resolution image and weak feature description in wide baseline confirm the validity of our approach.

  18. A feature-based approach to modeling protein-protein interaction hot spots.

    Science.gov (United States)

    Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

    2009-05-01

    Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

  19. Development and validation of a facial expression database based on the dimensional and categorical model of emotions.

    Science.gov (United States)

    Fujimura, Tomomi; Umemura, Hiroyuki

    2018-01-15

    The present study describes the development and validation of a facial expression database comprising five different horizontal face angles in dynamic and static presentations. The database includes twelve expression types portrayed by eight Japanese models. This database was inspired by the dimensional and categorical model of emotions: surprise, fear, sadness, anger with open mouth, anger with closed mouth, disgust with open mouth, disgust with closed mouth, excitement, happiness, relaxation, sleepiness, and neutral (static only). The expressions were validated using emotion classification and Affect Grid rating tasks [Russell, Weiss, & Mendelsohn, 1989. Affect Grid: A single-item scale of pleasure and arousal. Journal of Personality and Social Psychology, 57(3), 493-502]. The results indicate that most of the expressions were recognised as the intended emotions and could systematically represent affective valence and arousal. Furthermore, face angle and facial motion information influenced emotion classification and valence and arousal ratings. Our database will be available online at the following URL. https://www.dh.aist.go.jp/database/face2017/ .

  20. Facial emotion recognition in Parkinson's disease: A review and new hypotheses

    Science.gov (United States)

    Vérin, Marc; Sauleau, Paul; Grandjean, Didier

    2018-01-01

    Abstract Parkinson's disease is a neurodegenerative disorder classically characterized by motor symptoms. Among them, hypomimia affects facial expressiveness and social communication and has a highly negative impact on patients' and relatives' quality of life. Patients also frequently experience nonmotor symptoms, including emotional‐processing impairments, leading to difficulty in recognizing emotions from faces. Aside from its theoretical importance, understanding the disruption of facial emotion recognition in PD is crucial for improving quality of life for both patients and caregivers, as this impairment is associated with heightened interpersonal difficulties. However, studies assessing abilities in recognizing facial emotions in PD still report contradictory outcomes. The origins of this inconsistency are unclear, and several questions (regarding the role of dopamine replacement therapy or the possible consequences of hypomimia) remain unanswered. We therefore undertook a fresh review of relevant articles focusing on facial emotion recognition in PD to deepen current understanding of this nonmotor feature, exploring multiple significant potential confounding factors, both clinical and methodological, and discussing probable pathophysiological mechanisms. This led us to examine recent proposals about the role of basal ganglia‐based circuits in emotion and to consider the involvement of facial mimicry in this deficit from the perspective of embodied simulation theory. We believe our findings will inform clinical practice and increase fundamental knowledge, particularly in relation to potential embodied emotion impairment in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. PMID:29473661

  1. Sad Facial Expressions Increase Choice Blindness

    Directory of Open Access Journals (Sweden)

    Yajie Wang

    2018-01-01

    Full Text Available Previous studies have discovered a fascinating phenomenon known as choice blindness—individuals fail to detect mismatches between the face they choose and the face replaced by the experimenter. Although previous studies have reported a couple of factors that can modulate the magnitude of choice blindness, the potential effect of facial expression on choice blindness has not yet been explored. Using faces with sad and neutral expressions (Experiment 1 and faces with happy and neutral expressions (Experiment 2 in the classic choice blindness paradigm, the present study investigated the effects of facial expressions on choice blindness. The results showed that the detection rate was significantly lower on sad faces than neutral faces, whereas no significant difference was observed between happy faces and neutral faces. The exploratory analysis of verbal reports found that participants who reported less facial features for sad (as compared to neutral expressions also tended to show a lower detection rate of sad (as compared to neutral faces. These findings indicated that sad facial expressions increased choice blindness, which might have resulted from inhibition of further processing of the detailed facial features by the less attractive sad expressions (as compared to neutral expressions.

  2. Sad Facial Expressions Increase Choice Blindness.

    Science.gov (United States)

    Wang, Yajie; Zhao, Song; Zhang, Zhijie; Feng, Wenfeng

    2017-01-01

    Previous studies have discovered a fascinating phenomenon known as choice blindness-individuals fail to detect mismatches between the face they choose and the face replaced by the experimenter. Although previous studies have reported a couple of factors that can modulate the magnitude of choice blindness, the potential effect of facial expression on choice blindness has not yet been explored. Using faces with sad and neutral expressions (Experiment 1) and faces with happy and neutral expressions (Experiment 2) in the classic choice blindness paradigm, the present study investigated the effects of facial expressions on choice blindness. The results showed that the detection rate was significantly lower on sad faces than neutral faces, whereas no significant difference was observed between happy faces and neutral faces. The exploratory analysis of verbal reports found that participants who reported less facial features for sad (as compared to neutral) expressions also tended to show a lower detection rate of sad (as compared to neutral) faces. These findings indicated that sad facial expressions increased choice blindness, which might have resulted from inhibition of further processing of the detailed facial features by the less attractive sad expressions (as compared to neutral expressions).

  3. [Facial nerve neurinomas].

    Science.gov (United States)

    Sokołowski, Jacek; Bartoszewicz, Robert; Morawski, Krzysztof; Jamróz, Barbara; Niemczyk, Kazimierz

    2013-01-01

    Evaluation of diagnostic, surgical technique, treatment results facial nerve neurinomas and its comparison with literature was the main purpose of this study. Seven cases of patients (2005-2011) with facial nerve schwannomas were included to retrospective analysis in the Department of Otolaryngology, Medical University of Warsaw. All patients were assessed with history of the disease, physical examination, hearing tests, computed tomography and/or magnetic resonance imaging, electronystagmography. Cases were observed in the direction of potential complications and recurrences. Neurinoma of the facial nerve occurred in the vertical segment (n=2), facial nerve geniculum (n=1) and the internal auditory canal (n=4). The symptoms observed in patients were analyzed: facial nerve paresis (n=3), hearing loss (n=2), dizziness (n=1). Magnetic resonance imaging and computed tomography allowed to confirm the presence of the tumor and to assess its staging. Schwannoma of the facial nerve has been surgically removed using the middle fossa approach (n=5) and by antromastoidectomy (n=2). Anatomical continuity of the facial nerve was achieved in 3 cases. In the twelve months after surgery, facial nerve paresis was rated at level II-III° HB. There was no recurrence of the tumor in radiological observation. Facial nerve neurinoma is a rare tumor. Currently surgical techniques allow in most cases, the radical removing of the lesion and reconstruction of the VII nerve function. The rate of recurrence is low. A tumor of the facial nerve should be considered in the differential diagnosis of nerve VII paresis. Copyright © 2013 Polish Otorhinolaryngology - Head and Neck Surgery Society. Published by Elsevier Urban & Partner Sp. z.o.o. All rights reserved.

  4. A Study of Various Feature Extraction Methods on a Motor Imagery Based Brain Computer Interface System

    Directory of Open Access Journals (Sweden)

    Seyed Navid Resalat

    2016-01-01

    Discussion: These features were selected for the designed real-time navigation. The corresponding results revealed the subject-specific nature of the MI-based BCI system however, the Power Spectral Density (PSD based &alpha-BP feature had the highest averaged accuracy.

  5. The fate of task-irrelevant visual motion: perceptual load versus feature-based attention.

    Science.gov (United States)

    Taya, Shuichiro; Adams, Wendy J; Graf, Erich W; Lavie, Nilli

    2009-11-18

    We tested contrasting predictions derived from perceptual load theory and from recent feature-based selection accounts. Observers viewed moving, colored stimuli and performed low or high load tasks associated with one stimulus feature, either color or motion. The resultant motion aftereffect (MAE) was used to evaluate attentional allocation. We found that task-irrelevant visual features received less attention than co-localized task-relevant features of the same objects. Moreover, when color and motion features were co-localized yet perceived to belong to two distinct surfaces, feature-based selection was further increased at the expense of object-based co-selection. Load theory predicts that the MAE for task-irrelevant motion would be reduced with a higher load color task. However, this was not seen for co-localized features; perceptual load only modulated the MAE for task-irrelevant motion when this was spatially separated from the attended color location. Our results suggest that perceptual load effects are mediated by spatial selection and do not generalize to the feature domain. Feature-based selection operates to suppress processing of task-irrelevant, co-localized features, irrespective of perceptual load.

  6. Chinese wine classification system based on micrograph using combination of shape and structure features

    Science.gov (United States)

    Wan, Yi

    2011-06-01

    Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

  7. Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

    Science.gov (United States)

    Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

    2015-01-01

    Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

  8. Outcome of a graduated minimally invasive facial reanimation in patients with facial paralysis.

    Science.gov (United States)

    Holtmann, Laura C; Eckstein, Anja; Stähr, Kerstin; Xing, Minzhi; Lang, Stephan; Mattheis, Stefan

    2017-08-01

    Peripheral paralysis of the facial nerve is the most frequent of all cranial nerve disorders. Despite advances in facial surgery, the functional and aesthetic reconstruction of a paralyzed face remains a challenge. Graduated minimally invasive facial reanimation is based on a modular principle. According to the patients' needs, precondition, and expectations, the following modules can be performed: temporalis muscle transposition and facelift, nasal valve suspension, endoscopic brow lift, and eyelid reconstruction. Applying a concept of a graduated minimally invasive facial reanimation may help minimize surgical trauma and reduce morbidity. Twenty patients underwent a graduated minimally invasive facial reanimation. A retrospective chart review was performed with a follow-up examination between 1 and 8 months after surgery. The FACEgram software was used to calculate pre- and postoperative eyelid closure, the level of brows, nasal, and philtral symmetry as well as oral commissure position at rest and oral commissure excursion with smile. As a patient-oriented outcome parameter, the Glasgow Benefit Inventory questionnaire was applied. There was a statistically significant improvement in the postoperative score of eyelid closure, brow asymmetry, nasal asymmetry, philtral asymmetry as well as oral commissure symmetry at rest (p facial nerve repair or microneurovascular tissue transfer cannot be applied, graduated minimally invasive facial reanimation is a promising option to restore facial function and symmetry at rest.

  9. Technical Evaluation Report 51: Text-based Conferencing: Features vs. functionality

    Directory of Open Access Journals (Sweden)

    Lynn Anderson

    2005-11-01

    Full Text Available This report examines three text-based conferencing products: WowBB, Invision Power Board, and vBulletin. Their selection was prompted by a feature-by-feature comparison of the same products on the WowBB website. The comparison chart painted a misleading impression of WowBB’s features in relation to the other two products; so the evaluation team undertook a more comprehensive and impartial comparison using the categories and criteria for online software evaluation developed by the American Society for Training and Development (ASTD. The findings are summarised in terms of the softwares’ pricing, common features/ functions, and differentiating features.

  10. Facial skin follllicular hyperkeratosis of patients with basal cell carcinoma

    Directory of Open Access Journals (Sweden)

    M. V. Zhuchkov

    2016-01-01

    Full Text Available This article provides a clinical observation of paraneoplastic syndrome of a patient with basal cell carcinoma of skin. Authors present clinical features of the described for the first time, paraneoplastic retentional follicular hyperkeratosis of facial area.

  11. Sound-induced facial synkinesis following facial nerve paralysis

    NARCIS (Netherlands)

    Ma, Ming-San; van der Hoeven, Johannes H.; Nicolai, Jean-Philippe A.; Meek, Marcel F.

    Facial synkinesis (or synkinesia) (FS) occurs frequently after paresis or paralysis of the facial nerve and is in most cases due to aberrant regeneration of (branches of) the facial nerve. Patients suffer from inappropriate and involuntary synchronous facial muscle contractions. Here we describe two

  12. Single channel blind source separation based on ICA feature extraction

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new technique is proposed to solve the blind source separation (BSS) given only a single channel observation. The basis functions and the density of the coefficients of source signals learned by ICA are used as the prior knowledge. Based on the learned prior information the learning rules of single channel BSS are presented by maximizing the joint log likelihood of the mixed sources to obtain source signals from single observation,in which the posterior density of the given measurements is maximized. The experimental results exhibit a successful separation performance for mixtures of speech and music signals.

  13. Image segmentation-based robust feature extraction for color image watermarking

    Science.gov (United States)

    Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

    2018-04-01

    This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

  14. Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

    Science.gov (United States)

    Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

    2018-03-01

    The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

  15. A Polymer Optical Fiber Temperature Sensor Based on Material Features.

    Science.gov (United States)

    Leal-Junior, Arnaldo; Frizera-Netoc, Anselmo; Marques, Carlos; Pontes, Maria José

    2018-01-19

    This paper presents a polymer optical fiber (POF)-based temperature sensor. The operation principle of the sensor is the variation in the POF mechanical properties with the temperature variation. Such mechanical property variation leads to a variation in the POF output power when a constant stress is applied to the fiber due to the stress-optical effect. The fiber mechanical properties are characterized through a dynamic mechanical analysis, and the output power variation with different temperatures is measured. The stress is applied to the fiber by means of a 180° curvature, and supports are positioned on the fiber to inhibit the variation in its curvature with the temperature variation. Results show that the sensor proposed has a sensitivity of 1.04 × 10 -3 °C -1 , a linearity of 0.994, and a root mean squared error of 1.48 °C, which indicates a relative error of below 2%, which is lower than the ones obtained for intensity-variation-based temperature sensors. Furthermore, the sensor is able to operate at temperatures up to 110 °C, which is higher than the ones obtained for similar POF sensors in the literature.

  16. Feature discrimination/identification based upon SAR return variations

    Science.gov (United States)

    Rasco, W. A., Sr.; Pietsch, R.

    1978-01-01

    A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.

  17. Spectral features based tea garden extraction from digital orthophoto maps

    Science.gov (United States)

    Jamil, Akhtar; Bayram, Bulent; Kucuk, Turgay; Zafer Seker, Dursun

    2018-05-01

    The advancements in the photogrammetry and remote sensing technologies has made it possible to extract useful tangible information from data which plays a pivotal role in various application such as management and monitoring of forests and agricultural lands etc. This study aimed to evaluate the effectiveness of spectral signatures for extraction of tea gardens from 1 : 5000 scaled digital orthophoto maps obtained from Rize city in Turkey. First, the normalized difference vegetation index (NDVI) was derived from the input images to suppress the non-vegetation areas. NDVI values less than zero were discarded and the output images was normalized in the range 0-255. Individual pixels were then mapped into meaningful objects using global region growing technique. The resulting image was filtered and smoothed to reduce the impact of noise. Furthermore, geometrical constraints were applied to remove small objects (less than 500 pixels) followed by morphological opening operator to enhance the results. These objects served as building blocks for further image analysis. Finally, for the classification stage, a range of spectral values were empirically calculated for each band and applied on candidate objects to extract tea gardens. For accuracy assessment, we employed an area based similarity metric by overlapping obtained tea garden boundaries with the manually digitized tea garden boundaries created by experts of photogrammetry. The overall accuracy of the proposed method scored 89 % for tea gardens from 10 sample orthophoto maps. We concluded that exploiting the spectral signatures using object based analysis is an effective technique for extraction of dominant tree species from digital orthophoto maps.

  18. A feature based comparison of pen and swipe based signature characteristics.

    Science.gov (United States)

    Robertson, Joshua; Guest, Richard

    2015-10-01

    Dynamic Signature Verification (DSV) is a biometric modality that identifies anatomical and behavioral characteristics when an individual signs their name. Conventionally signature data has been captured using pen/tablet apparatus. However, the use of other devices such as the touch-screen tablets has expanded in recent years affording the possibility of assessing biometric interaction on this new technology. To explore the potential of employing DSV techniques when a user signs or swipes with their finger, we report a study to correlate pen and finger generated features. Investigating the stability and correlation between a set of characteristic features recorded in participant's signatures and touch-based swipe gestures, a statistical analysis was conducted to assess consistency between capture scenarios. The results indicate that there is a range of static and dynamic features such as the rate of jerk, size, duration and the distance the pen traveled that can lead to interoperability between these two systems for input methods for use within a potential biometric context. It can be concluded that this data indicates that a general principle is that the same underlying constructional mechanisms are evident. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

    Science.gov (United States)

    Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

    2017-01-01

    We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

  20. Uniform competency-based local feature extraction for remote sensing images

    Science.gov (United States)

    Sedaghat, Amin; Mohammadi, Nazila

    2018-01-01

    Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.