WorldWideScience

Sample records for face detection information

  1. An Illumination Invariant Face Detection Based on Human Shape Analysis and Skin Color Information

    Directory of Open Access Journals (Sweden)

    Dibakar Chakraborty

    2012-06-01

    Full Text Available This paper provides a novel approach towards face area localization through analyzing the shape characteristics of human body. The face region is extracted by determining the sharp increase in body pixels in the shoulder area from neck region. For ensuring face area skin color information is also analyzed. The experimental analysis shows that the proposed algorithm detects the face area effectively and it’s performance is found to be quite satisfactory

  2. Age-Dependent Face Detection and Face Categorization Performance

    OpenAIRE

    Claus-Christian Carbon; Martina Grüter; Thomas Grüter

    2013-01-01

    Empirical studies on the development of face processing skills with age show inconsistent patterns concerning qualitative vs. quantitative changes over time or the age range for peak cognitive performance. In the present study, we tested the proficiency in face detection and face categorization with a large sample of participants (N = 312; age range: 2-88 yrs). As test objects, we used so-called Mooney faces, two-tone (black and white) images of faces lacking critical information of a local, ...

  3. Age-dependent face detection and face categorization performance.

    Science.gov (United States)

    Carbon, Claus-Christian; Grüter, Martina; Grüter, Thomas

    2013-01-01

    Empirical studies on the development of face processing skills with age show inconsistent patterns concerning qualitative vs. quantitative changes over time or the age range for peak cognitive performance. In the present study, we tested the proficiency in face detection and face categorization with a large sample of participants (N = 312; age range: 2-88 yrs). As test objects, we used so-called Mooney faces, two-tone (black and white) images of faces lacking critical information of a local, featural and relational nature, reflecting difficult real world face processing conditions. We found that performance in the assessment of gender and age from Mooney faces increases up to about age 15, and decreases from 65 years on. The implications of these findings are discussed in the light of classic and recent findings from face development literature.

  4. Person-Specific Face Detection in a Scene with Optimum Composite Filtering and Colour-Shape Information

    Directory of Open Access Journals (Sweden)

    Seokwon Yeom

    2013-01-01

    Full Text Available Face detection and recognition have wide applications in robot vision and intelligent surveillance. However, face identification at a distance is very challenging because long‐distance images are often degraded by low resolution, blurring and noise. This paper introduces a person‐specific face detection method that uses a nonlinear optimum composite filter and subsequent verification stages. The filter’s optimum criterion minimizes the sum of the output energy generated by the input noise and the input image. The composite filter is trained with several training images under long‐distance modelling. The candidate facial regions are provided by the filter’s outputs of the input scene. False alarms are eliminated by subsequent testing stages, which comprise skin colour and edge mask filtering tests. In the experiments, images captured by a webcam and a CCTV camera are processed to show the effectiveness of the person‐specific face detection system at a long distance.

  5. Person-Specific Face Detection in a Scene with Optimum Composite Filtering and Colour-Shape Information

    Directory of Open Access Journals (Sweden)

    Seokwon Yeom

    2013-01-01

    Full Text Available Face detection and recognition have wide applications in robot vision and intelligent surveillance. However, face identification at a distance is very challenging because long-distance images are often degraded by low resolution, blurring and noise. This paper introduces a person-specific face detection method that uses a nonlinear optimum composite filter and subsequent verification stages. The filter's optimum criterion minimizes the sum of the output energy generated by the input noise and the input image. The composite filter is trained with several training images under long-distance modelling. The candidate facial regions are provided by the filter's outputs of the input scene. False alarms are eliminated by subsequent testing stages, which comprise skin colour and edge mask filtering tests. In the experiments, images captured by a webcam and a CCTV camera are processed to show the effectiveness of the person-specific face detection system at a long distance.

  6. Comparing Face Detection and Recognition Techniques

    OpenAIRE

    Korra, Jyothi

    2016-01-01

    This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

  7. 融合肤色信息和椭圆环模板的人脸检测%Face Detection Through Color Information and Elliptical Ring Template

    Institute of Scientific and Technical Information of China (English)

    徐艳

    2011-01-01

    Through color information and face contour information, this paper proposes a new feature extraction method based on color information and face contour. First of all, color regions are segmented by using improved color extraction algorithm, and analyzed in order to find candidate faces. Then edges of these candidate faces are detected, in accordance with edge detection points. They are matched with characteristics of face contour to identify the exact location. Finally, false faces are excluded by using mosaic template. Experimental results show that the algorithm has higher accuracy rate, high detection speed, and can detect faces of a certain point of view.%融合肤色信息和人脸轮廓信息,提出了一种新颖的基于肤色信息和人脸轮廓的人脸检测算法.首先利用改进的肤色提取算法对肤色进行分割,分析肤色区域,找出备选人脸;然后对备选人脸区域进行边缘检测,根据边缘检测点进行人脸轮廓特征的匹配,找出入脸的准确位置,并利用马赛克模板排除虚假人脸.实验结果表明,该算法具有较高的准确率,检测速度快,并能检测具有一定角度的人脸.

  8. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on‐site and on‐time. At this point, the use of smart cameras ‐ of which the popularity has been increasing ‐ is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image‐processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high‐ bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general‐purpose processors. In smart cameras ‐ which are real‐life applications of such methods ‐ the widest use is on DSPs. In the present study, the Viola‐Jones face detection method ‐ which was reported to run faster on PCs ‐ was optimized for DSPs; the face recognition method was combined with the developed sub‐region and mask‐based DCT (Discrete Cosine Transform. As the employed DSP is a fixed‐point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub‐ regions and from each sub‐region the robust coefficients against disruptive elements ‐ like face expression, illumination, etc. ‐ were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for

  9. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

  10. “Review on Human Face Detection based on Skin Color and Edge Information”

    Directory of Open Access Journals (Sweden)

    Divyesh S. Gondaliya

    2015-01-01

    Full Text Available Human face detection system is gradually used for the tracking a human face. Face detection system is mainly used in face reorganization system for detecting human face. Here in this review paper we have describe how face detection system works and where it is useful in real world environment. We have describes different technique like template matching, skin color and edge information based on face detection from skin region, symmetry based face detection and etc.

  11. FaceID: A face detection and recognition system

    Energy Technology Data Exchange (ETDEWEB)

    Shah, M.B.; Rao, N.S.V.; Olman, V.; Uberbacher, E.C.; Mann, R.C.

    1996-12-31

    A face detection system that automatically locates faces in gray-level images is described. Also described is a system which matches a given face image with faces in a database. Face detection in an Image is performed by template matching using templates derived from a selected set of normalized faces. Instead of using original gray level images, vertical gradient images were calculated and used to make the system more robust against variations in lighting conditions and skin color. Faces of different sizes are detected by processing the image at several scales. Further, a coarse-to-fine strategy is used to speed up the processing, and a combination of whole face and face component templates are used to ensure low false detection rates. The input to the face recognition system is a normalized vertical gradient image of a face, which is compared against a database using a set of pretrained feedforward neural networks with a winner-take-all fuser. The training is performed by using an adaptation of the backpropagation algorithm. This system has been developed and tested using images from the FERET database and a set of images obtained from Rowley, et al and Sung and Poggio.

  12. Face detection by aggregated Bayesian network classifiers

    NARCIS (Netherlands)

    Pham, T.V.; Worring, M.; Smeulders, A.W.M.

    2002-01-01

    A face detection system is presented. A new classification method using forest-structured Bayesian networks is used. The method is used in an aggregated classifier to discriminate face from non-face patterns. The process of generating non-face patterns is integrated with the construction of the aggr

  13. Familiar Face Detection in 180ms

    Science.gov (United States)

    Visconti di Oleggio Castello, Matteo; Gobbini, M. Ida

    2015-01-01

    The visual system is tuned for rapid detection of faces, with the fastest choice saccade to a face at 100ms. Familiar faces have a more robust representation than do unfamiliar faces, and are detected faster in the absence of awareness and with reduced attentional resources. Faces of family and close friends become familiar over a protracted period involving learning the unique visual appearance, including a view-invariant representation, as well as person knowledge. We investigated the effect of personal familiarity on the earliest stages of face processing by using a saccadic-choice task to measure how fast familiar face detection can happen. Subjects made correct and reliable saccades to familiar faces when unfamiliar faces were distractors at 180ms—very rapid saccades that are 30 to 70ms earlier than the earliest evoked potential modulated by familiarity. By contrast, accuracy of saccades to unfamiliar faces with familiar faces as distractors did not exceed chance. Saccades to faces with object distractors were even faster (110 to 120 ms) and equivalent for familiar and unfamiliar faces, indicating that familiarity does not affect ultra-rapid saccades. We propose that detectors of diagnostic facial features for familiar faces develop in visual cortices through learning and allow rapid detection that precedes explicit recognition of identity. PMID:26305788

  14. Improving Face Detection with TOE Cameras

    DEFF Research Database (Denmark)

    Hansen, Dan Witzner; Larsen, Rasmus; Lauze, F

    2007-01-01

    A face detection method based on a boosted classifier using images from a time-of-flight sensor is presented. We show that the performance of face detection can be improved when using both depth and gray scale images and that the common use of integration of hypotheses for verification can...... be relaxed. Based on the detected face we employ an active contour method on depth images for full head segmentation....

  15. Investigation of New Techniques for Face detection

    OpenAIRE

    Abdallah, Abdallah Sabry

    2007-01-01

    The task of detecting human faces within either a still image or a video frame is one of the most popular object detection problems. For the last twenty years researchers have shown great interest in this problem because it is an essential pre-processing stage for computing systems that process human faces as input data. Example applications include face recognition systems, vision systems for autonomous robots, human computer interaction systems (HCI), surveillance systems, biometric based a...

  16. Robust online face tracking-by-detection

    NARCIS (Netherlands)

    Comaschi, F.; Stuijk, S.; Basten, T.; Corporaal, H.

    2016-01-01

    The problem of online face tracking from unconstrained videos is still unresolved. Challenges range from coping with severe online appearance variations to coping with occlusion. We propose RFTD (Robust Face Tracking-by-Detection), a system which combines tracking and detection into a single framewo

  17. Strategic information security: facing the cyber impact

    CSIR Research Space (South Africa)

    Grobler, M

    2010-10-01

    Full Text Available necessitate an integrated organisational approach to information security. However, the best information security infrastructure cannot guarantee that cyber attacks and malicious intrusions will not happen. It has become necessary to face the impact...

  18. Face Detection and Face Recognition in Android Mobile Applications

    Directory of Open Access Journals (Sweden)

    Octavian DOSPINESCU

    2016-01-01

    Full Text Available The quality of the smartphone’s camera enables us to capture high quality pictures at a high resolution, so we can perform different types of recognition on these images. Face detection is one of these types of recognition that is very common in our society. We use it every day on Facebook to tag friends in our pictures. It is also used in video games alongside Kinect concept, or in security to allow the access to private places only to authorized persons. These are just some examples of using facial recognition, because in modern society, detection and facial recognition tend to surround us everywhere. The aim of this article is to create an appli-cation for smartphones that can recognize human faces. The main goal of this application is to grant access to certain areas or rooms only to certain authorized persons. For example, we can speak here of hospitals or educational institutions where there are rooms where only certain employees can enter. Of course, this type of application can cover a wide range of uses, such as helping people suffering from Alzheimer's to recognize the people they loved, to fill gaps persons who can’t remember the names of their relatives or for example to automatically capture the face of our own children when they smile.

  19. Independent component analysis of edge information for face recognition

    CERN Document Server

    Karande, Kailash Jagannath

    2013-01-01

    The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also propos

  20. Face Detection under Complex Background and Illumination

    Institute of Scientific and Technical Information of China (English)

    Shao-Dong Lv; Yong-Duan Song; Mei Xu; Cong-Ying Huang

    2015-01-01

    Abstract⎯For face detection under complex background and illumination, a detection method that combines the skin color segmentation and cost-sensitive Adaboost algorithm is proposed in this paper. First, by using the characteristic of human skin color clustering in the color space, the skin color area inYCbCr color space is extracted and a large number of irrelevant backgrounds are excluded; then for remedyingthe deficiencies of Adaboost algorithm, the cost-sensitive function is introduced into the Adaboost algorithm; finally the skin color segmentation and cost-sensitive Adaboost algorithm are combined for the face detection. Experimental results show that the proposed detection method has a higher detection rate and detection speed, which can more adapt to the actual field environment.

  1. Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy

    Directory of Open Access Journals (Sweden)

    Francisco A. Pujol

    2017-01-01

    Full Text Available Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to interpret image information. In this paper, we propose a fuzzy system for detecting skin in color images, so that each color tone is assumed to be a fuzzy set. The Red, Green, and Blue (RGB, the Hue, Saturation and Value (HSV, and the YCbCr (where Y is the luminance and Cb,Cr are the chroma components color systems are used for the development of our fuzzy design. Thus, a fuzzy three-partition entropy approach is used to calculate all of the parameters needed for the fuzzy systems, and then, a face detection method is also developed to validate the segmentation results. The results of the experiments show a correct skin detection rate between 94% and 96% for our fuzzy segmentation methods, with a false positive rate of about 0.5% in all cases. Furthermore, the average correct face detection rate is above 93%, and even when working with heterogeneous backgrounds and different light conditions, it achieves almost 88% correct detections. Thus, our method leads to accurate face detection results with low false positive and false negative rates.

  2. Varying face occlusion detection and iterative recovery for face recognition

    Science.gov (United States)

    Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

    2017-05-01

    In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

  3. Active testing for face detection and localization.

    Science.gov (United States)

    Sznitman, Raphael; Jedynak, Bruno

    2010-10-01

    We provide a novel search technique which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images. We show exponential gains in computation over traditional sliding window approaches, while keeping similar performance levels.

  4. A Novel Method for 3D Face Detection and Normalization

    Directory of Open Access Journals (Sweden)

    Robert Niese

    2007-09-01

    Full Text Available When automatically analyzing images of human faces, either for recognition in biometry applications or facial expression analysis in human machine interaction, one has to cope with challenges caused by different head pose, illumination and expression. In this article we propose a new stereo based method for effectively solving the pose problem through 3D face detection and normalization. The proposed method applies a model-based matching and is especially intended for the study of facial features and the description of their dynamic changes in image sequences under the assumption of non-cooperative persons. In our work, we are currently implementing a new application to observe and analyze single faces of post-operative patients. In the proposed method, face detection is based on color driven clustering of 3D points derived from stereo. A mesh model is matched with the post-processed face cluster using a variant of the Iterative Closest Point algorithm (ICP. Pose is derived from correspondence. Then, pose and model information is used for the synthesis of the face normalization. Results show, stereo and color are powerful cues for finding the face and its pose under a wide range of poses, illuminations and expressions (PIE. Head orientation may vary in out of plane rotations up to ±45°.

  5. Face Detection in Digital Image: A Technical Review

    Directory of Open Access Journals (Sweden)

    Devang C

    2015-01-01

    Full Text Available Face detection is the method of focusing faces in input image is an important part of any face processing system. In Face detection, segmentation plays the major role to detect the face. There are many contests for effective and efficient face detection. The aim of this paper is to present a review on several algorithms and methods used for face detection. We read the various surveys and related various techniques according to how they extract features and what learning algorithms are adopted for. Face detection system has two major phases, first to segment skin region from an image and second to decide these regions cover human face or not. There are number of algorithms used in face detection namely Genetic, Hausdorff Distance etc.

  6. The effect of texture on face identification and configural information processing

    Directory of Open Access Journals (Sweden)

    Tzschaschel Eva Alica

    2014-01-01

    Full Text Available Shape and texture are an integral part of face identity. In the present study, the importance of face texture for face identification and detection of configural manipulation (i.e., spatial relation among facial features was examined by comparing grayscale face photographs (i.e., real faces and line drawings of the same faces. Whereas real faces provide information about texture and shape of faces, line drawings are lacking texture cues. A change-detection task and a forced-choice identification task were used with both stimuli categories. Within the change detection task, participants had to decide whether the size of the eyes of two sequentially presented faces had changed or not. After having made this decision, three faces were shown to the subjects and they had to identify the previously shown face among them. Furthermore, context (full vs. cropped faces and orientation (upright vs. inverted were manipulated. The results obtained in the change detection task suggest that configural information was used in processing real faces, while part-based and featural information was used in processing line-drawings. Additionally, real faces were identified more accurately than line drawings, and identification was less context but more orientation sensitive than identification of line drawings. Taken together, the results of the present study provide new evidence stressing the importance of face texture for identity encoding and configural face processing.

  7. 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.

  8. Separated Same Rectangle Feature for Face Detection

    Institute of Scientific and Technical Information of China (English)

    Yong-hee HONG; Hwan-ik CHUNG; Hern-soo HAHN

    2010-01-01

    The paper proposes a new method of "Separated Same Rectangle Feature (SSRF)" for face detection.Generally,Haar-Like feature is used to make an Adaboost training algorithm with strong classifier.Haar-like feature is composed of two or more attached same rectangles,Inefficiency of the Haar-like feature often results from two or more attached same rectangles.But the proposed SSRF are composed of two separated same rectangles.So,it is very flexible and detailed.Therefore it creates more accuate strong classifier than Haar-Like feature.SSRF uses integral image to reduce executive time.Haar-Iike feature calculates the sum of intensities of pixels on two or more rectangles.But SSRF always calculates the sum of in-tensities of pixels on only two rectangles.The weak classifier of Ada-boost algorithm based on SSRF is faster than one based an Haar-likefeature.In the experiment,we use 1 000 face images and 1 000non-face images for Adaboost training.The proposed SSRF shows about 0,9% higher accuracy than Haar-Iike features.

  9. Impaired face detection may explain some but not all cases of developmental prosopagnosia.

    Science.gov (United States)

    Dalrymple, Kirsten A; Duchaine, Brad

    2016-05-01

    Developmental prosopagnosia (DP) is defined by severe face recognition difficulties due to the failure to develop the visual mechanisms for processing faces. The two-process theory of face recognition (Morton & Johnson, 1991) implies that DP could result from a failure of an innate face detection system; this failure could prevent an individual from then tuning higher-level processes for face recognition (Johnson, 2005). Work with adults indicates that some individuals with DP have normal face detection whereas others are impaired. However, face detection has not been addressed in children with DP, even though their results may be especially informative because they have had less opportunity to develop strategies that could mask detection deficits. We tested the face detection abilities of seven children with DP. Four were impaired at face detection to some degree (i.e. abnormally slow, or failed to find faces) while the remaining three children had normal face detection. Hence, the cases with impaired detection are consistent with the two-process account suggesting that DP could result from a failure of face detection. However, the cases with normal detection implicate a higher-level origin. The dissociation between normal face detection and impaired identity perception also indicates that these abilities depend on different neurocognitive processes.

  10. A global attentional scope setting prioritizes faces for conscious detection.

    Science.gov (United States)

    Sun, Sol Z; Cant, Jonathan S; Ferber, Susanne

    2016-01-01

    The scope of visual attention is known to affect conscious object perception, with recent studies showing that a global attentional scope boosts holistic face processing, relative to a local scope. Here we show that attentional scope settings can also modulate the availability of information for conscious visual awareness. In an initial experiment, we show that adopting a global attentional scope accelerates conscious detection of initially invisible faces, presented under continuous flash suppression (CFS). Furthermore, face detection time was not modulated by attentional scope in a nonrivalrous control condition, which emulated the experience of CFS without inducing binocular rivalry. In a follow-up experiment, we report an exact replication of the original effect, as well as data suggesting that this effect is specific to upright faces, and is abolished when using both inverted faces and images of houses in an otherwise identical task. Thus, attentional scope settings can modulate the availability of information to conscious awareness, fundamentally altering the contents of our subjective visual experience.

  11. Dominant Local Binary Pattern Based Face Feature Selection and Detection

    Directory of Open Access Journals (Sweden)

    Kavitha.T

    2010-04-01

    Full Text Available Face Detection plays a major role in Biometrics.Feature selection is a problem of formidable complexity. Thispaper proposes a novel approach to extract face features forface detection. The LBP features can be extracted faster in asingle scan through the raw image and lie in a lower dimensional space, whilst still retaining facial information efficiently. The LBP features are robust to low-resolution images. The dominant local binary pattern (DLBP is used to extract features accurately. A number of trainable methods are emerging in the empirical practice due to their effectiveness. The proposed method is a trainable system for selecting face features from over-completes dictionaries of imagemeasurements. After the feature selection procedure is completed the SVM classifier is used for face detection. The main advantage of this proposal is that it is trained on a very small training set. The classifier is used to increase the selection accuracy. This is not only advantageous to facilitate the datagathering stage, but, more importantly, to limit the training time. CBCL frontal faces dataset is used for training and validation.

  12. A causal relationship between face-patch activity and face-detection behavior

    Science.gov (United States)

    Sadagopan, Srivatsun; Zarco, Wilbert; Freiwald, Winrich A

    2017-01-01

    The primate brain contains distinct areas densely populated by face-selective neurons. One of these, face-patch ML, contains neurons selective for contrast relationships between face parts. Such contrast-relationships can serve as powerful heuristics for face detection. However, it is unknown whether neurons with such selectivity actually support face-detection behavior. Here, we devised a naturalistic face-detection task and combined it with fMRI-guided pharmacological inactivation of ML to test whether ML is of critical importance for real-world face detection. We found that inactivation of ML impairs face detection. The effect was anatomically specific, as inactivation of areas outside ML did not affect face detection, and it was categorically specific, as inactivation of ML impaired face detection while sparing body and object detection. These results establish that ML function is crucial for detection of faces in natural scenes, performing a critical first step on which other face processing operations can build. DOI: http://dx.doi.org/10.7554/eLife.18558.001 PMID:28375078

  13. Application of binocular vision system to face detection and tracking in service robot

    Science.gov (United States)

    Qian, Junfeng; Ma, Shiwei; Xu, Yulin; Li, Xin; Shen, Yujie

    2012-01-01

    A binocular vision system and its application to face detection and tracking in robot is introduced in this paper. With the vision system, the robot can do face detection, identification, recognition and tracking. The face area is detected in realtime by using AdaBoost algorithm. And a method is proposed with which a real face can be distinguished from a picture one by using skin color information and depth data. A specific face can be recognized by comparing the principal components of the current face to those of the known individuals in a face database built in advance. Finally, the robot can track a specified face according to depth of the face and position of a face rectangle in the frame. Experiment results are given and discussed.

  14. An RGB-D Database Using Microsoft’s Kinect for Windows for Face Detection

    DEFF Research Database (Denmark)

    Idskou Høg, Rasmus; Jasek, Petr; Rofidal, Clement

    2012-01-01

    of the available 3d databases have already automatically or manually detected the face images and they are therefore mostly used for face recognition not detection. This paper purposes an RGB-D database containing 1581 images (and their depth counterparts) taken from 31 persons in 17 different poses and facial......The very first step in many facial analysis systems is face detection. Though face detection has been studied for many years, there is not still a benchmark public database to be widely accepted among researchers for which both color and depth information are obtained by the same sensor. Most...... expressions using a Kinect device. The faces in the images are not extracted neither in the RGB images nor in the depth hereof, therefore they can be used for both detection and recognition. The proposed database has been used in a face detection algorithm which is based on the depth information of the images...

  15. Faces in places: humans and machines make similar face detection errors.

    Directory of Open Access Journals (Sweden)

    Bernard Marius 't Hart

    Full Text Available The human visual system seems to be particularly efficient at detecting faces. This efficiency sometimes comes at the cost of wrongfully seeing faces in arbitrary patterns, including famous examples such as a rock configuration on Mars or a toast's roast patterns. In machine vision, face detection has made considerable progress and has become a standard feature of many digital cameras. The arguably most wide-spread algorithm for such applications ("Viola-Jones" algorithm achieves high detection rates at high computational efficiency. To what extent do the patterns that the algorithm mistakenly classifies as faces also fool humans? We selected three kinds of stimuli from real-life, first-person perspective movies based on the algorithm's output: correct detections ("real faces", false positives ("illusory faces" and correctly rejected locations ("non faces". Observers were shown pairs of these for 20 ms and had to direct their gaze to the location of the face. We found that illusory faces were mistaken for faces more frequently than non faces. In addition, rotation of the real face yielded more errors, while rotation of the illusory face yielded fewer errors. Using colored stimuli increases overall performance, but does not change the pattern of results. When replacing the eye movement by a manual response, however, the preference for illusory faces over non faces disappeared. Taken together, our data show that humans make similar face-detection errors as the Viola-Jones algorithm, when directing their gaze to briefly presented stimuli. In particular, the relative spatial arrangement of oriented filters seems of relevance. This suggests that efficient face detection in humans is likely to be pre-attentive and based on rather simple features as those encoded in the early visual system.

  16. Multiple Face Location Using Motion Information

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Face location is a difficult problem for face recognition and multiple face location is more challenging. In this paper, two new methods are presented for multiple face location via motion analysis techniques. The first method is based on motion segmentation. The authors introduce a new segmentation method by computing optical flow only on the Motion Zero-Crossing Boundary (MZCB) followed by a simple clustering method to segment each person. Then an intuitive but effective location algorithm is applied to locate each face. The second method is derived from the Hough Transform (HT). After modeling a head outline as a curve consisting of circle segments, a modified HT is used to find the center of each face. Finally, the two methods are compared and the future research directions are given.

  17. Emotion recognition: the role of featural and configural face information.

    Science.gov (United States)

    Bombari, Dario; Schmid, Petra C; Schmid Mast, Marianne; Birri, Sandra; Mast, Fred W; Lobmaier, Janek S

    2013-01-01

    Several studies investigated the role of featural and configural information when processing facial identity. A lot less is known about their contribution to emotion recognition. In this study, we addressed this issue by inducing either a featural or a configural processing strategy (Experiment 1) and by investigating the attentional strategies in response to emotional expressions (Experiment 2). In Experiment 1, participants identified emotional expressions in faces that were presented in three different versions (intact, blurred, and scrambled) and in two orientations (upright and inverted). Blurred faces contain mainly configural information, and scrambled faces contain mainly featural information. Inversion is known to selectively hinder configural processing. Analyses of the discriminability measure (A') and response times (RTs) revealed that configural processing plays a more prominent role in expression recognition than featural processing, but their relative contribution varies depending on the emotion. In Experiment 2, we qualified these differences between emotions by investigating the relative importance of specific features by means of eye movements. Participants had to match intact expressions with the emotional cues that preceded the stimulus. The analysis of eye movements confirmed that the recognition of different emotions rely on different types of information. While the mouth is important for the detection of happiness and fear, the eyes are more relevant for anger, fear, and sadness.

  18. Multi-face detection based on downsampling and modified subtractive clustering for color images

    Institute of Scientific and Technical Information of China (English)

    KONG Wan-zeng; ZHU Shan-an

    2007-01-01

    This paper presents a multi-face detection method for color images. The method is based on the assumption that faces are well separated from the background by skin color detection. These faces can be located by the proposed method which modifies the subtractive clustering. The modified clustering algorithm proposes a new definition of distance for multi-face detection, and its key parameters can be predetermined adaptively by statistical information of face objects in the image. Downsampling is employed to reduce the computation of clustering and speed up the process of the proposed method. The effectiveness of the proposed method is illustrated by three experiments.

  19. Adaptive WildNet Face network for detecting face in the wild

    Science.gov (United States)

    Nguyen, Dinh-Luan; Nguyen, Vinh-Tiep; Tran, Minh-Triet; Yoshitaka, Atsuo

    2015-12-01

    Combining Convolutional Neural Network and Deformable Part Models is a new trend in object detection area. Following this trend, we propose Adaptive WildNet Face network using Deformable Part Models structure to exploit advantages of two methods in face detection area. We evaluate the merit of our method on Face Detection Data Set and Benchmark. Experimental results show that our method achieves up to 86.22% true positive images in 1000 false positive images in FDDB. Our method becomes one of state-of-the-art methods in FDDB dataset and it opens a new way to detect faces of images in the wild.

  20. Correlation based efficient face recognition and color change detection

    Science.gov (United States)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

    2013-01-01

    Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

  1. Face Detection and Modeling for Recognition

    Science.gov (United States)

    2002-01-01

    facial components show the important role of hair and face outlines in human face recognition. . . 8 1.6 Caricatures of (a) Vincent Van Gogh ; (b) Jim... Vincent Van Gogh ; (b) Jim Carrey; (c) Arnold Schwarzenegger; (d) Einstein; (e) G. W. Bush; and (f) Bill Gates. Images are down- loaded from [9], [10

  2. Robust Algorithm for Face Detection in Color Images

    Directory of Open Access Journals (Sweden)

    Hlaing Htake Khaung Tin

    2012-03-01

    Full Text Available Robust Algorithm is presented for frontal face detection in color images. Face detection is an important task in facial analysis systems in order to have a priori localized faces in a given image. Applications such as face tracking, facial expression recognition, gesture recognition, etc., for example, have a pre-requisite that a face is already located in the given image or the image sequence. Facial features such as eyes, nose and mouth are automatically detected based on properties of the associated image regions. On detecting a mouth, a nose and two eyes, a face verification step based on Eigen face theory is applied to a normalized search space in the image relative to the distance between the eye feature points. The experiments were carried out on test images taken from the internet and various other randomly selected sources. The algorithm has also been tested in practice with a webcam, giving (near real-time performance and good extraction results.

  3. The many faces of information disclosure

    NARCIS (Netherlands)

    Boot, A.W.A.; Thakor, A.V.

    1998-01-01

    In this article we ask: what kind of information and how much of it should firms voluntarily disclose? Three types of disclosures are considered. One is information that complements the information available only to informed investors (to-be-processed complementary information). The second is inform

  4. Multi-Pose Face Detection and Tracking Using Condensation

    Directory of Open Access Journals (Sweden)

    Cheng-Chieh Chiang

    2014-10-01

    Full Text Available Automatically locating face areas can advance applications either in images or videos. This paper proposes a video-based approach for face detection and tracking in an indoor environment to determine where face areas appear in video sequences. Our approach involves four main modules: an initialization module for setting all configurations, a Condensation module for face tracking, a template module for measuring the observation process in Condensation, and a correction module for correcting the tracking if the tracked face has been lost. We adapted the Condensation algorithm for dealing with the face tracking problem, and designed a checklist scheme for the template module that can record the most significant templates of the tracked face poses. We also performed experiments to demonstrate the performance and the robustness of our proposed approach for face detection and tracking.

  5. Semantic information can facilitate covert face recognition in congenital prosopagnosia.

    Science.gov (United States)

    Rivolta, Davide; Schmalzl, Laura; Coltheart, Max; Palermo, Romina

    2010-11-01

    People with congenital prosopagnosia have never developed the ability to accurately recognize faces. This single case investigation systematically investigates covert and overt face recognition in "C.," a 69 year-old woman with congenital prosopagnosia. Specifically, we: (a) describe the first assessment of covert face recognition in congenital prosopagnosia using multiple tasks; (b) show that semantic information can contribute to covert recognition; and (c) provide a theoretical explanation for the mechanisms underlying covert face recognition.

  6. A Driver Face Monitoring System for Fatigue and Distraction Detection

    Directory of Open Access Journals (Sweden)

    Mohamad-Hoseyn Sigari

    2013-01-01

    Full Text Available Driver face monitoring system is a real-time system that can detect driver fatigue and distraction using machine vision approaches. In this paper, a new approach is introduced for driver hypovigilance (fatigue and distraction detection based on the symptoms related to face and eye regions. In this method, face template matching and horizontal projection of top-half segment of face image are used to extract hypovigilance symptoms from face and eye, respectively. Head rotation is a symptom to detect distraction that is extracted from face region. The extracted symptoms from eye region are (1 percentage of eye closure, (2 eyelid distance changes with respect to the normal eyelid distance, and (3 eye closure rate. The first and second symptoms related to eye region are used for fatigue detection; the last one is used for distraction detection. In the proposed system, a fuzzy expert system combines the symptoms to estimate level of driver hypo-vigilance. There are three main contributions in the introduced method: (1 simple and efficient head rotation detection based on face template matching, (2 adaptive symptom extraction from eye region without explicit eye detection, and (3 normalizing and personalizing the extracted symptoms using a short training phase. These three contributions lead to develop an adaptive driver eye/face monitoring. Experiments show that the proposed system is relatively efficient for estimating the driver fatigue and distraction.

  7. Face liveness detection using shearlet-based feature descriptors

    Science.gov (United States)

    Feng, Litong; Po, Lai-Man; Li, Yuming; Yuan, Fang

    2016-07-01

    Face recognition is a widely used biometric technology due to its convenience but it is vulnerable to spoofing attacks made by nonreal faces such as photographs or videos of valid users. The antispoof problem must be well resolved before widely applying face recognition in our daily life. Face liveness detection is a core technology to make sure that the input face is a live person. However, this is still very challenging using conventional liveness detection approaches of texture analysis and motion detection. The aim of this paper is to propose a feature descriptor and an efficient framework that can be used to effectively deal with the face liveness detection problem. In this framework, new feature descriptors are defined using a multiscale directional transform (shearlet transform). Then, stacked autoencoders and a softmax classifier are concatenated to detect face liveness. We evaluated this approach using the CASIA Face antispoofing database and replay-attack database. The experimental results show that our approach performs better than the state-of-the-art techniques following the provided protocols of these databases, and it is possible to significantly enhance the security of the face recognition biometric system. In addition, the experimental results also demonstrate that this framework can be easily extended to classify different spoofing attacks.

  8. Face liveness detection for face recognition based on cardiac features of skin color image

    Science.gov (United States)

    Suh, Kun Ha; Lee, Eui Chul

    2016-07-01

    With the growth of biometric technology, spoofing attacks have been emerged a threat to the security of the system. Main spoofing scenarios in the face recognition system include the printing attack, replay attack, and 3D mask attack. To prevent such attacks, techniques that evaluating liveness of the biometric data can be considered as a solution. In this paper, a novel face liveness detection method based on cardiac signal extracted from face is presented. The key point of proposed method is that the cardiac characteristic is detected in live faces but not detected in non-live faces. Experimental results showed that the proposed method can be effective way for determining printing attack or 3D mask attack.

  9. Global shape information increases but color information decreases the composite face effect.

    Science.gov (United States)

    Retter, Talia L; Rossion, Bruno

    2015-01-01

    The separation of visual shape and surface information may be useful for understanding holistic face perception--that is, the perception of a face as a single unit (Jiang, Blanz, & Rossion, 2011, Visual Cognition, 19, 1003-1034). A widely used measure of holistic face perception is the composite face effect (CFE), in which identical top face halves appear different when aligned with bottom face halves from different identities. In the present study the influences of global face shape (ie contour of the face) and color information on the CFE are investigated, with the hypothesis that global face shape supports but color impairs holistic face perception as measured in this paradigm. In experiment 1 the CFE is significantly increased when face stimuli possess natural global shape information than when cropped to a generic (ie oval) global shape; this effect is not found when the stimuli are presented inverted. In experiment 2 the CFE is significantly decreased when face stimuli are presented with color information than when presented in grayscale. These findings indicate that grayscale stimuli maintaining natural global face shape information provide the most adept measure of holistic face perception in the behavioral composite face paradigm. More generally, they show that reducing different types of information diagnostic for individual face perception can have opposite effects on the CFE, illustrating the functional dissociation between shape and surface information in face perception.

  10. 3D face recognition algorithm based on detecting reliable components

    Institute of Scientific and Technical Information of China (English)

    Huang Wenjun; Zhou Xuebing; Niu Xiamu

    2007-01-01

    Fisherfaces algorithm is a popular method for face recognition. However, there exist some unstable components that degrade recognition performance. In this paper, we propose a method based on detecting reliable components to overcome the problem and introduce it to 3D face recognition. The reliable components are detected within the binary feature vector, which is generated from the Fisherfaces feature vector based on statistical properties, and is used for 3D face recognition as the final feature vector. Experimental results show that the reliable components feature vector is much more effective than the Fisherfaces feature vector for face recognition.

  11. Face detection based on multiple kernel learning algorithm

    Science.gov (United States)

    Sun, Bo; Cao, Siming; He, Jun; Yu, Lejun

    2016-09-01

    Face detection is important for face localization in face or facial expression recognition, etc. The basic idea is to determine whether there is a face in an image or not, and also its location, size. It can be seen as a binary classification problem, which can be well solved by support vector machine (SVM). Though SVM has strong model generalization ability, it has some limitations, which will be deeply analyzed in the paper. To access them, we study the principle and characteristics of the Multiple Kernel Learning (MKL) and propose a MKL-based face detection algorithm. In the paper, we describe the proposed algorithm in the interdisciplinary research perspective of machine learning and image processing. After analyzing the limitation of describing a face with a single feature, we apply several ones. To fuse them well, we try different kernel functions on different feature. By MKL method, the weight of each single function is determined. Thus, we obtain the face detection model, which is the kernel of the proposed method. Experiments on the public data set and real life face images are performed. We compare the performance of the proposed algorithm with the single kernel-single feature based algorithm and multiple kernels-single feature based algorithm. The effectiveness of the proposed algorithm is illustrated. Keywords: face detection, feature fusion, SVM, MKL

  12. Informal face-to-face interaction improves mood state reflected in prefrontal cortex activity

    Directory of Open Access Journals (Sweden)

    Jun-Ichiro eWatanabe

    2016-05-01

    Full Text Available Recent progress with wearable sensors has enabled researchers to capture face-to-face interactions quantitatively and given great insight into human dynamics. One attractive field for applying such sensors is the workplace, where the relationship between the face-to-face behaviors of employees and the productivity of the organization has been investigated. One interesting result of previous studies showed that informal face-to-face interaction among employees, captured by wearable sensors that the employees wore, significantly affects their performance. However, the mechanism behind this relationship has not yet been adequately explained, though experiences at the job scene might qualitatively support the finding. We hypothesized that informal face-to-face interaction improves mood state, which in turn affects the task performance. To test this hypothesis, we evaluated the change of mood state before and after break time for two groups of participants, one that spent their breaks alone and one that spent them with other participants, by administering questionnaires and taking brain activity measurements. Recent neuroimaging studies have suggested a significant relationship between mood state and brain activity. Here, we show that face-to-face interaction during breaks significantly improved mood state, which was measured by Profiles of Mood States (POMS.We also observed that the verbal WM task performance of participants who did not have face-to-face interaction during breaks decreased significantly. In this paper, we discuss how the change of mood state was evidenced in the prefrontal cortex (PFC activity accompanied by working memory (WM tasks measured by near-infrared spectroscopy (NIRS.

  13. Informal Face-to-Face Interaction Improves Mood State Reflected in Prefrontal Cortex Activity

    Science.gov (United States)

    Watanabe, Jun-ichiro; Atsumori, Hirokazu; Kiguchi, Masashi

    2016-01-01

    Recent progress with wearable sensors has enabled researchers to capture face-to-face interactions quantitatively and given great insight into human dynamics. One attractive field for applying such sensors is the workplace, where the relationship between the face-to-face behaviors of employees and the productivity of the organization has been investigated. One interesting result of previous studies showed that informal face-to-face interaction among employees, captured by wearable sensors that the employees wore, significantly affects their performance. However, the mechanism behind this relationship has not yet been adequately explained, though experiences at the job scene might qualitatively support the finding. We hypothesized that informal face-to-face interaction improves mood state, which in turn affects the task performance. To test this hypothesis, we evaluated the change of mood state before and after break time for two groups of participants, one that spent their breaks alone and one that spent them with other participants, by administering questionnaires and taking brain activity measurements. Recent neuroimaging studies have suggested a significant relationship between mood state and brain activity. Here, we show that face-to-face interaction during breaks significantly improved mood state, which was measured by Profiles of Mood States (POMS). We also observed that the verbal working memory (WM) task performance of participants who did not have face-to-face interaction during breaks decreased significantly. In this paper, we discuss how the change of mood state was evidenced in the prefrontal cortex (PFC) activity accompanied by WM tasks measured by near-infrared spectroscopy (NIRS). PMID:27199715

  14. Face Detection Using Discrete Gabor Jets and a Probabilistic Model of Colored Image Patches

    Science.gov (United States)

    Hoffmann, Ulrich; Naruniec, Jacek; Yazdani, Ashkan; Ebrahimi, Touradj

    Face detection allows to recognize and detect human faces and provides information about their location in a given image. Many applications such as biometrics, face recognition, and video surveillance employ face detection as one of their main modules. Therefore, improvement in the performance of existing face detection systems and new achievements in this field of research are of significant importance. In this paper a hierarchical classification approach for face detection is presented. In the first step, discrete Gabor jets (DGJ) are used for extracting features related to the brightness information of images and a preliminary classification is made. Afterwards, a skin detection algorithm, based on modeling of colored image patches, is employed as a post-processing of the results of DGJ-based classification. It is shown that the use of color efficiently reduces the number of false positives while maintaining a high true positive rate. A comparison is made with the OpenCV implementation of the Viola and Jones face detector and it is concluded that higher correct classification rates can be attained using the proposed face detector.

  15. Face Detection in Still Gray Images

    Science.gov (United States)

    2000-05-01

    statistical independence between the components. In our system we started with a manually de ned set of facial components and a simple geometrical...there was at least one detection with a higher SVM out- put value in its neighborhood. The neighborhood in the image plane was de ned as a 19 19 box...based classi er is shown in Fig. 16. A similar architecture was used for people detection [ Mohan 99]. On the rst level, component classi ers

  16. Toward automated face detection in thermal and polarimetric thermal imagery

    Science.gov (United States)

    Gordon, Christopher; Acosta, Mark; Short, Nathan; Hu, Shuowen; Chan, Alex L.

    2016-05-01

    Visible spectrum face detection algorithms perform pretty reliably under controlled lighting conditions. However, variations in illumination and application of cosmetics can distort the features used by common face detectors, thereby degrade their detection performance. Thermal and polarimetric thermal facial imaging are relatively invariant to illumination and robust to the application of makeup, due to their measurement of emitted radiation instead of reflected light signals. The objective of this work is to evaluate a government off-the-shelf wavelet based naïve-Bayes face detection algorithm and a commercial off-the-shelf Viola-Jones cascade face detection algorithm on face imagery acquired in different spectral bands. New classifiers were trained using the Viola-Jones cascade object detection framework with preprocessed facial imagery. Preprocessing using Difference of Gaussians (DoG) filtering reduces the modality gap between facial signatures across the different spectral bands, thus enabling more correlated histogram of oriented gradients (HOG) features to be extracted from the preprocessed thermal and visible face images. Since the availability of training data is much more limited in the thermal spectrum than in the visible spectrum, it is not feasible to train a robust multi-modal face detector using thermal imagery alone. A large training dataset was constituted with DoG filtered visible and thermal imagery, which was subsequently used to generate a custom trained Viola-Jones detector. A 40% increase in face detection rate was achieved on a testing dataset, as compared to the performance of a pre-trained/baseline face detector. Insights gained in this research are valuable in the development of more robust multi-modal face detectors.

  17. The changing face of informed surgical consent.

    LENUS (Irish Health Repository)

    Oosthuizen, J C

    2012-03-01

    To determine whether procedure-specific brochures improve patients\\' pre-operative knowledge, to determine the amount of information expected by patients during the consenting process, and to determine whether the recently proposed \\'Request for Treatment\\' consenting process is viable on a large scale.

  18. Face validation using 3D information from single calibrated camera

    DEFF Research Database (Denmark)

    Katsarakis, N.; Pnevmatikakis, A.

    2009-01-01

    propose a novel face validation method based on 3D position estimates from a single calibrated camera. This is done by assuming a typical face width; hence the widths of the detected image regions lead to target position estimates. Detected image regions with extreme position estimates can...... then be discarded. We apply our method on the rich dataset of the CLEAR2007 evaluation campaign, comprising 49 thousand annotated indoors images, recorded at five different sites, from four different cameras per site, depicting approximately 122 thousand faces. Our method yields very accurate 3D position estimates...

  19. The Changing Face of Serials Information Management

    OpenAIRE

    Henderson, Kitty

    2012-01-01

    The EBSCOhost is a Z39.50 compliant, multi-database client/server host featuring full-text for over 1,000 titles. Currently available in UNIX character cell and Windows formats, this presentation will preview the new WEB interface scheduled to be available during the Summer. EBSCOhost features an optional link to EBSCOdoc, a document delivery and current awareness service. EBSCOhost and EBSCOdoc are part of the EBSCO Information Services group.

  20. A Viola-Jones based hybrid face detection framework

    Science.gov (United States)

    Murphy, Thomas M.; Broussard, Randy; Schultz, Robert; Rakvic, Ryan; Ngo, Hau

    2013-12-01

    Improvements in face detection performance would benefit many applications. The OpenCV library implements a standard solution, the Viola-Jones detector, with a statistically boosted rejection cascade of binary classifiers. Empirical evidence has shown that Viola-Jones underdetects in some instances. This research shows that a truncated cascade augmented by a neural network could recover these undetected faces. A hybrid framework is constructed, with a truncated Viola-Jones cascade followed by an artificial neural network, used to refine the face decision. Optimally, a truncation stage that captured all faces and allowed the neural network to remove the false alarms is selected. A feedforward backpropagation network with one hidden layer is trained to discriminate faces based upon the thresholding (detection) values of intermediate stages of the full rejection cascade. A clustering algorithm is used as a precursor to the neural network, to group significant overlappings. Evaluated on the CMU/VASC Image Database, comparison with an unmodified OpenCV approach shows: (1) a 37% increase in detection rates if constrained by the requirement of no increase in false alarms, (2) a 48% increase in detection rates if some additional false alarms are tolerated, and (3) an 82% reduction in false alarms with no reduction in detection rates. These results demonstrate improved face detection and could address the need for such improvement in various applications.

  1. A color based face detection system using multiple templates

    Institute of Scientific and Technical Information of China (English)

    王涛; 卜佳俊; 陈纯

    2003-01-01

    A color based system using multiple templates was developed and implemented for detecting human faces in color images. The algorithm consists of three image processing steps. The first step is human skin color statistics. Then it separates skin regions from non-skin regions. After that, it locates the frontal human face(s) within the skin regions. In the first step, 250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors. This chroma chart is used to generate, from the original color image, a gray scale image whose gray value at a pixel shows its likelihood of representing the skin. The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into separate skin regions from non skin regions. Finally, multiple face templates matching is used to determine if a given skin region represents a frontal human face or not. Test of the system with more than 400 color images showed that the resulting detection rate was 83%, which is better than most color-based face detection systems. The average speed for face detection is 0.8 second/image (400×300 pixels) on a Pentium 3 (800MHz) PC.

  2. A color based face detection system using multiple templates

    Institute of Scientific and Technical Information of China (English)

    王涛; 卜佳酸; 陈纯

    2003-01-01

    A color based system using multiple templates was developed and implemented for detecting hu-man faces in color images.The algorithm comsists of three image processing steps.The first step is human skin color statistics.Then it separates skin regions from non-skin regions.After that,it locates the frontal human face(s) within the skin regions.In the first step,250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors.This chroma chart is used to generate,from the original color image,a gray scale image whose gray value at a pixel shows its likelihood of representing the shin,The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into sep-arate skin regions from non skin regions.Finally,multiple face templates matching is used to determine if a given skin region represents a frontal human face or not.Test of the system with more than 400 color images showed that the resulting detection rate was 83%,which is better than most colou-based face detection sys-tems.The average speed for face detection is 0.8 second/image(400×300pixels) on a Pentium 3(800MHz) PC.

  3. Association with emotional information alters subsequent processing of neutral faces.

    Science.gov (United States)

    Riggs, Lily; Fujioka, Takako; Chan, Jessica; McQuiggan, Douglas A; Anderson, Adam K; Ryan, Jennifer D

    2014-01-01

    The processing of emotional as compared to neutral information is associated with different patterns in eye movement and neural activity. However, the 'emotionality' of a stimulus can be conveyed not only by its physical properties, but also by the information that is presented with it. There is very limited work examining the how emotional information may influence the immediate perceptual processing of otherwise neutral information. We examined how presenting an emotion label for a neutral face may influence subsequent processing by using eye movement monitoring (EMM) and magnetoencephalography (MEG) simultaneously. Participants viewed a series of faces with neutral expressions. Each face was followed by a unique negative or neutral sentence to describe that person, and then the same face was presented in isolation again. Viewing of faces paired with a negative sentence was associated with increased early viewing of the eye region and increased neural activity between 600 and 1200 ms in emotion processing regions such as the cingulate, medial prefrontal cortex, and amygdala, as well as posterior regions such as the precuneus and occipital cortex. Viewing of faces paired with a neutral sentence was associated with increased activity in the parahippocampal gyrus during the same time window. By monitoring behavior and neural activity within the same paradigm, these findings demonstrate that emotional information alters subsequent visual scanning and the neural systems that are presumably invoked to maintain a representation of the neutral information along with its emotional details.

  4. Face Image Quality and its Improvement in a Face Detection System

    DEFF Research Database (Denmark)

    Kamal, Nasrollahi; Moeslund, Thomas B.

    2008-01-01

    When a person passes by a surveillance camera a sequence of images is obtained. Most of these images are redundant and usually keeping some of them which have better quality is sufficient. So before performing any analysis on the face of a person, the face at the first step needs to be detected....... In the second step the quality of the different face images needs to be evaluated. Finally, after choosing the best image(s) based on this quality assessment, in the third step, if this image(s) is not satisfying a predefined set of measures for good quality images, its quality should be improved. In this work...

  5. Incorporating Prior Shape into Geometric Active Contours for Face Contour Detection

    Institute of Scientific and Technical Information of China (English)

    HUANGFuzhen; SUJianbo; XIYugeng

    2004-01-01

    In this paper a new method that incorporates prior shape information into geometric active contours for face contour detection is proposed. As in general a human face can be treated as an ellipse with a little shape variation, the prior face shape is represented as an elliptical curve. By combining the prior face shape with the powerful geometric active model proposed by Chan and Vese, the improved geometric active model can retain all the advantage of the Chan-Vese model and can detect face contours in images with complex backgrounds accurately even if the image is noisy. Moreover, by implementing the new model in a variational level set framework, automatic topological changes of the model can be achieved naturally and the transformation parameters that map the face boundary to the prior shape can be roughly estimated simultaneously. The experimental results show our procedure to be eiTicient.

  6. Automatic face detection and tracking based on Adaboost with camshift algorithm

    Science.gov (United States)

    Lin, Hui; Long, JianFeng

    2011-10-01

    With the development of information technology, video surveillance is widely used in security monitoring and identity recognition. For most of pure face tracking algorithms are hard to specify the initial location and scale of face automatically, this paper proposes a fast and robust method to detect and track face by combining adaboost with camshift algorithm. At first, the location and scale of face is specified by adaboost algorithm based on Haar-like features and it will be conveyed to the initial search window automatically. Then, we apply camshift algorithm to track face. The experimental results based on OpenCV software yield good results, even in some special circumstances, such as light changing and face rapid movement. Besides, by drawing out the tracking trajectory of face movement, some abnormal behavior events can be analyzed.

  7. Borderline Personality and the Detection of Angry Faces.

    Directory of Open Access Journals (Sweden)

    Johanna Hepp

    Full Text Available Many studies have assessed emotion recognition in patients with Borderline Personality Disorder and considerable evidence has been accumulated on patients' ability to categorize emotions. In contrast, their ability to detect emotions has been investigated sparsely. The only two studies that assessed emotion detection abilities found contradictory evidence on patients' ability to detect angry faces.To clarify whether patients with Borderline Personality Disorder show enhanced detection of angry faces, we conducted three experiments: a laboratory study (n = 53 with a clinical sample and two highly powered web studies that measured Borderline features (n1 = 342, n2 = 220. Participants in all studies completed a visual search paradigm, and the reaction times for the detection of angry vs. happy faces were measured.Consistently, data spoke against enhanced detection of angry faces in the Borderline groups, indicated by non-significant group (Borderline vs. healthy control × target (angry vs. happy interactions, despite highly satisfactory statistical power to detect even small effects.In contrast to emotion categorization, emotion detection appears to be intact in patients with Borderline Personality Disorder and individuals high in Borderline features. The importance of distinguishing between these two processes in future studies is discussed.

  8. Real-time Face Detection using Skin Color Model

    Institute of Scientific and Technical Information of China (English)

    LU Yao-xin; LIU Zhi-Qiang; ZHU Xiang-hua

    2004-01-01

    This paper presents a new face detection approach to real-time applications, which is based on the skin color model and the morphological filtering. First the non-skin color pixels of the input image are removed based on the skin color model in the YCrCb chrominance space, from which we extract candidate human face regions. Then a mathematical morphological filter is used to remove noisy regions and fill the holes in the candidate skin color regions. We adopt the similarity between the human face features and the candidate face regions to locate the face regions in the original image. We have implemented the algorithm in our smart media system. The experiment results show that this system is effective in real-time applications.

  9. Individual differences in detecting rapidly presented fearful faces.

    Directory of Open Access Journals (Sweden)

    Dandan Zhang

    Full Text Available Rapid detection of evolutionarily relevant threats (e.g., fearful faces is important for human survival. The ability to rapidly detect fearful faces exhibits high variability across individuals. The present study aimed to investigate the relationship between behavioral detection ability and brain activity, using both event-related potential (ERP and event-related oscillation (ERO measurements. Faces with fearful or neutral facial expressions were presented for 17 ms or 200 ms in a backward masking paradigm. Forty-two participants were required to discriminate facial expressions of the masked faces. The behavioral sensitivity index d' showed that the detection ability to rapidly presented and masked fearful faces varied across participants. The ANOVA analyses showed that the facial expression, hemisphere, and presentation duration affected the grand-mean ERP (N1, P1, and N170 and ERO (below 20 Hz and lasted from 100 ms to 250 ms post-stimulus, mainly in theta band brain activity. More importantly, the overall detection ability of 42 subjects was significantly correlated with the emotion effect (i.e., fearful vs. neutral on ERP (r = 0.403 and ERO (r = 0.552 measurements. A higher d' value was corresponding to a larger size of the emotional effect (i.e., fearful--neutral of N170 amplitude and a larger size of the emotional effect of the specific ERO spectral power at the right hemisphere. The present results suggested a close link between behavioral detection ability and the N170 amplitude as well as the ERO spectral power below 20 Hz in individuals. The emotional effect size between fearful and neutral faces in brain activity may reflect the level of conscious awareness of fearful faces.

  10. Research on a Product Information Management System Facing Remanufacture Engineering

    Institute of Scientific and Technical Information of China (English)

    HOU Du-cheng; YU Kai-chao; JIA Jian-shi; TANG Xiu-ying

    2007-01-01

    Remanufacture Engineering is an important characteristic and development trend of a manufacturing system in the 21st Century, and product information management is very important to Remanufacture Engineering. In this paper, we first compared traditional manufacturing and remanufacturing. Then, according to the features of Remanufacture Engineering, we analyzed the request of product information management system facing Remanufacture Engineering, and designed the system module. Finally, we built a kind of system structure of product information management facing Remanufacture Engineering and gave realization methods based on Web.

  11. Efficient Approach for Face Detection in Video Surveillance

    Institute of Scientific and Technical Information of China (English)

    宋红; 石峰

    2003-01-01

    Security access control systems and automatic video surveillance systems are becoming increasingly important recently,and detecting human faces is one of the indispensable processes.In this paper,an approach is presented to detect faces in video surveillance.Firstly,both the skin-color and motion components are applied to extract skin-like regions.The skin-color segmentation algorithm is based on the BPNN (back-error-propagation neural network) and the motion component is obtained with frame difference algorithm.Secondly,the image is clustered into separated face candidates by using the region growing technique.Finally,the face candidates are further verified by the rule-based algorithm.Experiment results demonstrate that both the accuracy and processing speed are very promising and the approach can be applied for the practical use.

  12. A robust, low-cost approach to Face Detection and Face Recognition

    CERN Document Server

    Jyoti, Divya; Vaidya, Pallavi; Roja, M Mani

    2011-01-01

    In the domain of Biometrics, recognition systems based on iris, fingerprint or palm print scans etc. are often considered more dependable due to extremely low variance in the properties of these entities with respect to time. However, over the last decade data processing capability of computers has increased manifold, which has made real-time video content analysis possible. This shows that the need of the hour is a robust and highly automated Face Detection and Recognition algorithm with credible accuracy rate. The proposed Face Detection and Recognition system using Discrete Wavelet Transform (DWT) accepts face frames as input from a database containing images from low cost devices such as VGA cameras, webcams or even CCTV's, where image quality is inferior. Face region is then detected using properties of L*a*b* color space and only Frontal Face is extracted such that all additional background is eliminated. Further, this extracted image is converted to grayscale and its dimensions are resized to 128 x 128...

  13. Face detection dissociates from face recognition : evidence from ERPs and the naso-temporal asymmetry (Abstract)

    NARCIS (Netherlands)

    de Gelder, B.; Pourtois, G.R.C.

    2002-01-01

    Neuropsychological data indicate that face processing could be distributed among two functionally and anatomically distinct mechanisms, one specialised for detection and the other aimed at recognition (de Gelder & Rouw, 2000; 2001). These two mechanisms may be implemented in different interacting re

  14. Distinct information critically distinguishes judgments of face familiarity and identity.

    Science.gov (United States)

    Smith, Marie L; Volna, Blanka; Ewing, Louise

    2016-11-01

    Accurately determining the familiarity of another and correctly establishing their identity are vital social skills. A considerable body of work has explored their perceptual and neural underpinnings and debate remains regarding whether they are dissociable, that is, separable parts of a dual process, or different aspects of a common retrieval process. Less is known about the specific visual information that guides familiarity judgments and how this compares to the information used to identify a face by name. Here we sought to establish the critical information underlying participants' judgments of facial familiarity and identification. We created a new standardized stimulus set comprising 6 personally familiar and 12 unfamiliar faces and applied the Bubbles reverse-correlation methodology to establish the information driving correct performance in each task. Results revealed that markedly different information underlies familiarity and identity judgments. When categorizing familiarity, participants relied more upon lower spatial-frequency, broad facial cues (eye and face shape) than when categorizing identity, which relied on fine details in the internal features (eyes and mouth). These results provide novel evidence of qualitatively distinct information use in familiarity and identification judgments and emphasize the importance of considering the task set for participants and their processing strategy when investigating face recognition. (PsycINFO Database Record

  15. Automated face detection for occurrence and occupancy estimation in chimpanzees.

    Science.gov (United States)

    Crunchant, Anne-Sophie; Egerer, Monika; Loos, Alexander; Burghardt, Tilo; Zuberbühler, Klaus; Corogenes, Katherine; Leinert, Vera; Kulik, Lars; Kühl, Hjalmar S

    2017-03-01

    Surveying endangered species is necessary to evaluate conservation effectiveness. Camera trapping and biometric computer vision are recent technological advances. They have impacted on the methods applicable to field surveys and these methods have gained significant momentum over the last decade. Yet, most researchers inspect footage manually and few studies have used automated semantic processing of video trap data from the field. The particular aim of this study is to evaluate methods that incorporate automated face detection technology as an aid to estimate site use of two chimpanzee communities based on camera trapping. As a comparative baseline we employ traditional manual inspection of footage. Our analysis focuses specifically on the basic parameter of occurrence where we assess the performance and practical value of chimpanzee face detection software. We found that the semi-automated data processing required only 2-4% of the time compared to the purely manual analysis. This is a non-negligible increase in efficiency that is critical when assessing the feasibility of camera trap occupancy surveys. Our evaluations suggest that our methodology estimates the proportion of sites used relatively reliably. Chimpanzees are mostly detected when they are present and when videos are filmed in high-resolution: the highest recall rate was 77%, for a false alarm rate of 2.8% for videos containing only chimpanzee frontal face views. Certainly, our study is only a first step for transferring face detection software from the lab into field application. Our results are promising and indicate that the current limitation of detecting chimpanzees in camera trap footage due to lack of suitable face views can be easily overcome on the level of field data collection, that is, by the combined placement of multiple high-resolution cameras facing reverse directions. This will enable to routinely conduct chimpanzee occupancy surveys based on camera trapping and semi

  16. Emotion identification method using RGB information of human face

    Science.gov (United States)

    Kita, Shinya; Mita, Akira

    2015-03-01

    Recently, the number of single households is drastically increased due to the growth of the aging society and the diversity of lifestyle. Therefore, the evolution of building spaces is demanded. Biofied Building we propose can help to avoid this situation. It helps interaction between the building and residents' conscious and unconscious information using robots. The unconscious information includes emotion, condition, and behavior. One of the important information is thermal comfort. We assume we can estimate it from human face. There are many researchs about face color analysis, but a few of them are conducted in real situations. In other words, the existing methods were not used with disturbance such as room lumps. In this study, Kinect was used with face-tracking. Room lumps and task lumps were used to verify that our method could be applicable to real situation. In this research, two rooms at 22 and 28 degrees C were prepared. We showed that the transition of thermal comfort by changing temperature can be observed from human face. Thus, distinction between the data of 22 and 28 degrees C condition from face color was proved to be possible.

  17. Morphed emotional faces: Emotion detection and misinterpretation in social anxiety

    NARCIS (Netherlands)

    Heuer, K.; Lange, W.G.; Isaac, L.; Rinck, M.; Becker, E.S.

    2010-01-01

    The current study investigated detection and interpretation of emotional facial expressions in high socially anxious (HSA) individuals compared to non-anxious controls (NAC). A version of the morphed faces task was implemented to assess emotion onset perception, decoding accuracy and interpretation,

  18. Face inversion decreased information about facial identity and expression in face-responsive neurons in macaque area TE.

    Science.gov (United States)

    Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Ohyama, Kaoru; Kawano, Kenji

    2014-09-10

    To investigate the effect of face inversion and thatcherization (eye inversion) on temporal processing stages of facial information, single neuron activities in the temporal cortex (area TE) of two rhesus monkeys were recorded. Test stimuli were colored pictures of monkey faces (four with four different expressions), human faces (three with four different expressions), and geometric shapes. Modifications were made in each face-picture, and its four variations were used as stimuli: upright original, inverted original, upright thatcherized, and inverted thatcherized faces. A total of 119 neurons responded to at least one of the upright original facial stimuli. A majority of the neurons (71%) showed activity modulations depending on upright and inverted presentations, and a lesser number of neurons (13%) showed activity modulations depending on original and thatcherized face conditions. In the case of face inversion, information about the fine category (facial identity and expression) decreased, whereas information about the global category (monkey vs human vs shape) was retained for both the original and thatcherized faces. Principal component analysis on the neuronal population responses revealed that the global categorization occurred regardless of the face inversion and that the inverted faces were represented near the upright faces in the principal component analysis space. By contrast, the face inversion decreased the ability to represent human facial identity and monkey facial expression. Thus, the neuronal population represented inverted faces as faces but failed to represent the identity and expression of the inverted faces, indicating that the neuronal representation in area TE cause the perceptual effect of face inversion.

  19. Big Questions Facing Vocational Psychology: A Cognitive Information Processing Perspective

    Science.gov (United States)

    Reardon, Robert C.; Lenz, Janet G.; Sampson, James P., Jr.; Peterson, Gary W.

    2011-01-01

    This article draws upon the authors' experience in developing cognitive information processing theory in order to examine three important questions facing vocational psychology and assessment: (a) Where should new knowledge for vocational psychology come from? (b) How do career theories and research find their way into practice? and (c) What is…

  20. Big Questions Facing Vocational Psychology: A Cognitive Information Processing Perspective

    Science.gov (United States)

    Reardon, Robert C.; Lenz, Janet G.; Sampson, James P., Jr.; Peterson, Gary W.

    2011-01-01

    This article draws upon the authors' experience in developing cognitive information processing theory in order to examine three important questions facing vocational psychology and assessment: (a) Where should new knowledge for vocational psychology come from? (b) How do career theories and research find their way into practice? and (c) What is…

  1. ARTIFICIAL NEURAL NETWORK IN FACE DETECTION HUMAN ON DIGITAL IMAGE

    Directory of Open Access Journals (Sweden)

    Abdusamad Al-Marghilani

    2013-01-01

    Full Text Available Method itself is proposed to be formed by series of filters. Each filter is an independent method of detection and allows you to cut off quickly the regions that do not contain the face’s areas. For this purpose some of the different characteristics of the object are used in addition each subsequent part processes only promising areas of image which were obtained from the previous parts of the method. It has been tested by means of CMU/MIT test set. Analogy of speed and quality detection. There are two modifications to the classic use of neural networks in face detection. First the neural network only tests candidate regions for the face, thus dropping the search space. Secondly the window size is used in network scanning the input image is adaptive and depends on the size of the region of the candidate are implemented in Using Mat lab. The analysis of detection quality of a new method in comparison with the algorithm. The experimental results show that the proposed method the detection method, based on rectangular primitives, in quality. The proposed method, tested on a standard Test set, has surpassed all known methods in speed and quality of detection. Our approach without pre-treatment is not required because the normalization is enabled directly in the weights of the input network.

  2. Colour detection thresholds in faces and colour patches.

    Science.gov (United States)

    Tan, Kok Wei; Stephen, Ian D

    2013-01-01

    Human facial skin colour reflects individuals' underlying health (Stephen et al 2011 Evolution & Human Behavior 32 216-227); and enhanced facial skin CIELab b* (yellowness), a* (redness), and L* (lightness) are perceived as healthy (also Stephen et al 2009a International Journal of Primatology 30 845-857). Here, we examine Malaysian Chinese participants' detection thresholds for CIELab L* (lightness), a* (redness), and b* (yellowness) colour changes in Asian, African, and Caucasian faces and skin coloured patches. Twelve face photos and three skin coloured patches were transformed to produce four pairs of images of each individual face and colour patch with different amounts of red, yellow, or lightness, from very subtle (deltaE = 1.2) to quite large differences (deltaE = 9.6). Participants were asked to decide which of sequentially displayed, paired same-face images or colour patches were lighter, redder, or yellower. Changes in facial redness, followed by changes in yellowness, were more easily discriminated than changes in luminance. However, visual sensitivity was not greater for redness and yellowness in nonface stimuli, suggesting red facial skin colour special salience. Participants were also significantly better at recognizing colour differences in own-race (Asian) and Caucasian faces than in African faces, suggesting the existence of cross-race effect in discriminating facial colours. Humans' colour vision may have been selected for skin colour signalling (Changizi et al 2006 Biology Letters 2 217-221), enabling individuals to perceive subtle changes in skin colour, reflecting health and emotional status.

  3. Applying face identification to detecting hijacking of airplane

    Science.gov (United States)

    Luo, Xuanwen; Cheng, Qiang

    2004-09-01

    That terrorists hijacked the airplanes and crashed the World Trade Center is disaster to civilization. To avoid the happening of hijack is critical to homeland security. To report the hijacking in time, limit the terrorist to operate the plane if happened and land the plane to the nearest airport could be an efficient way to avoid the misery. Image processing technique in human face recognition or identification could be used for this task. Before the plane take off, the face images of pilots are input into a face identification system installed in the airplane. The camera in front of pilot seat keeps taking the pilot face image during the flight and comparing it with pre-input pilot face images. If a different face is detected, a warning signal is sent to ground automatically. At the same time, the automatic cruise system is started or the plane is controlled by the ground. The terrorists will have no control over the plane. The plane will be landed to a nearest or appropriate airport under the control of the ground or cruise system. This technique could also be used in automobile industry as an image key to avoid car stealth.

  4. Face Contour Extraction of Information%人脸轮廓信息的提取

    Institute of Scientific and Technical Information of China (English)

    原瑾

    2011-01-01

    边缘提取在模式识别、机器视觉、图像分析及图像编码等领域都有着重要的研究价值。人脸检测技术是一种人脸识别技术的前提。文章针对人脸检测中人脸定位提出了人脸轮廓信息提取技术,确定人脸检测的主要区域。首先介绍了几种边缘检测算子,然后提出了动态阈值方法来改进图像阈值,提高了边缘检测精度。%Edge extraction has important research value in the fields of pattern recognition, machine vision, image analysis and image coding. Face detection technology is prerequisite of face recognition technology. In view of person face localization in person face detection, the dissertation proposes an extraction technology of face outline information to identify the main regional of face. This article first introduced several edge detection operators, and then proposed the method of dynamic threshold value to improves the image threshold value, which increased the edge detection accuracy.

  5. Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

    Directory of Open Access Journals (Sweden)

    Iwan Setyawan

    2011-12-01

    Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.

  6. Detecting Stochastic Information of Electrocardiograms

    CERN Document Server

    Gutíerrez, R M; Guti'errez, Rafael M.; Sandoval, Luis A.

    2003-01-01

    In this work we present a method to detect, identify and characterize stochastic information contained in an electrocardiogram (ECG). We assume, as it is well known, that the ECG has information corresponding to many different processes related to the cardiac activity. We analyze scaling and Markov processes properties of the detected stochastic information using the power spectrum of the ECG and the Fokker-Planck equation respectively. The detected stochastic information is then characterized by three measures. First, the slope of the power spectrum in a particular range of frequencies as a scaling parameter. Second, an empirical estimation of the drift and diffusion coefficients of the Fokker-Planck equation through the Kramers-Moyal coefficients which define the evolution of the probability distribution of the detected stochastic information.

  7. Face to face interventions for informing or educating parents about early childhood vaccination.

    Science.gov (United States)

    Kaufman, Jessica; Synnot, Anneliese; Ryan, Rebecca; Hill, Sophie; Horey, Dell; Willis, Natalie; Lin, Vivian; Robinson, Priscilla

    2013-05-31

    Childhood vaccination (also described as immunisation) is an important and effective way to reduce childhood illness and death. However, there are many children who do not receive the recommended vaccines because their parents do not know why vaccination is important, do not understand how, where or when to get their children vaccinated, disagree with vaccination as a public health measure, or have concerns about vaccine safety.Face to face interventions to inform or educate parents about routine childhood vaccination may improve vaccination rates and parental knowledge or understanding of vaccination. Such interventions may describe or explain the practical and logistical factors associated with vaccination, and enable parents to understand the meaning and relevance of vaccination for their family or community. To assess the effects of face to face interventions for informing or educating parents about early childhood vaccination on immunisation uptake and parental knowledge. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2012, Issue 7); MEDLINE (OvidSP) (1946 to July 2012); EMBASE + Embase Classic (OvidSP) (1947 to July 2012); CINAHL (EbscoHOST) (1981 to July 2012); PsycINFO (OvidSP) (1806 to July 2012); Global Health (CAB) (1910 to July 2012); Global Health Library (WHO) (searched July 2012); Google Scholar (searched September 2012), ISI Web of Science (searched September 2012) and reference lists of relevant articles. We searched for ongoing trials in The International Clinical Trials Registry Platform (ICTRP) (searched August 2012) and for grey literature in The Grey Literature Report and OpenGrey (searched August 2012). We also contacted authors of included studies and experts in the field. There were no language or date restrictions. Randomised controlled trials (RCTs) and cluster RCTs evaluating the effects of face to face interventions delivered to individual parents or groups of parents to inform or educate

  8. Information Theory for Gabor Feature Selection for Face Recognition

    Directory of Open Access Journals (Sweden)

    Shen Linlin

    2006-01-01

    Full Text Available A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004, our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.

  9. Information Theory for Gabor Feature Selection for Face Recognition

    Science.gov (United States)

    Shen, Linlin; Bai, Li

    2006-12-01

    A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004), our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.

  10. A baseline algorithm for face detection and tracking in video

    Science.gov (United States)

    Manohar, Vasant; Soundararajan, Padmanabhan; Korzhova, Valentina; Boonstra, Matthew; Goldgof, Dmitry; Kasturi, Rangachar

    2007-10-01

    Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research significance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance metrics and establishing a substantial dataset with ground truth for object detection and tracking tasks (text and face) in two video domains -- broadcast news and meetings. In this paper, we present the results of a face detection and tracking algorithm on broadcast news videos with the objective of establishing a baseline performance for this task-domain pair. The detection algorithm uses a statistical approach that was originally developed by Viola and Jones and later extended by Lienhart. The algorithm uses a feature set that is Haar-like and a cascade of boosted decision tree classifiers as a statistical model. In this work, we used the Intel Open Source Computer Vision Library (OpenCV) implementation of the Haar face detection algorithm. The optimal values for the tunable parameters of this implementation were found through an experimental design strategy commonly used in statistical analyses of industrial processes. Tracking was accomplished as continuous detection with the detected objects in two frames mapped using a greedy algorithm based on the distances between the centroids of bounding boxes. Results on the evaluation set containing 50 sequences (~ 2.5 mins.) using the developed performance metrics show good performance of the algorithm reflecting the state-of-the-art which makes it an appropriate choice as the baseline algorithm for the problem.

  11. Face Detection Using Adaboosted SVM-Based Component Classifier

    CERN Document Server

    Valiollahzadeh, Seyyed Majid; Nazari, Mohammad

    2008-01-01

    Recently, Adaboost has been widely used to improve the accuracy of any given learning algorithm. In this paper we focus on designing an algorithm to employ combination of Adaboost with Support Vector Machine as weak component classifiers to be used in Face Detection Task. To obtain a set of effective SVM-weaklearner Classifier, this algorithm adaptively adjusts the kernel parameter in SVM instead of using a fixed one. Proposed combination outperforms in generalization in comparison with SVM on imbalanced classification problem. The proposed here method is compared, in terms of classification accuracy, to other commonly used Adaboost methods, such as Decision Trees and Neural Networks, on CMU+MIT face database. Results indicate that the performance of the proposed method is overall superior to previous Adaboost approaches.

  12. Robust Face Recognition via Occlusion Detection and Masking

    Directory of Open Access Journals (Sweden)

    Guo Tan

    2016-01-01

    Full Text Available Sparse representation-based classification (SRC method has demonstrated promising results in face recognition (FR. In this paper, we consider the problem of face recognition with occlusion. In sparse representation-based classification method, the reconstruction residual of test sample over the training set is usually heterogeneous with the training samples, highlighting the occlusion part in test sample. We detect the occlusion part by extracting a mask from the reconstruction residual through threshold operation. The mask will be applied in the representation-based classification framework to eliminate the impact of occlusion in FR. The method does not assume any prior knowledge about the occlusion, and extensive experiments on publicly available databases show the efficacy of the method.

  13. Unconstrained face detection and recognition based on RGB-D camera for the visually impaired

    Science.gov (United States)

    Zhao, Xiangdong; Wang, Kaiwei; Yang, Kailun; Hu, Weijian

    2017-02-01

    It is highly important for visually impaired people (VIP) to be aware of human beings around themselves, so correctly recognizing people in VIP assisting apparatus provide great convenience. However, in classical face recognition technology, faces used in training and prediction procedures are usually frontal, and the procedures of acquiring face images require subjects to get close to the camera so that frontal face and illumination guaranteed. Meanwhile, labels of faces are defined manually rather than automatically. Most of the time, labels belonging to different classes need to be input one by one. It prevents assisting application for VIP with these constraints in practice. In this article, a face recognition system under unconstrained environment is proposed. Specifically, it doesn't require frontal pose or uniform illumination as required by previous algorithms. The attributes of this work lie in three aspects. First, a real time frontal-face synthesizing enhancement is implemented, and frontal faces help to increase recognition rate, which is proved with experiment results. Secondly, RGB-D camera plays a significant role in our system, from which both color and depth information are utilized to achieve real time face tracking which not only raises the detection rate but also gives an access to label faces automatically. Finally, we propose to use neural networks to train a face recognition system, and Principal Component Analysis (PCA) is applied to pre-refine the input data. This system is expected to provide convenient help for VIP to get familiar with others, and make an access for them to recognize people when the system is trained enough.

  14. Informant: Detecting Sybils Using Incentives

    Science.gov (United States)

    Margolin, N. Boris; Levine, Brian N.

    We propose an economic approach to Sybil attack detection. In our Informant protocol, a detective offers a reward for Sybils to reveal themselves. The detective accepts from one identity a security deposit and the name of target peer; the deposit and a reward are given to the target. We prove the optimal strategy for the informant is to play the game if and only if she is Sybil with a low opportunity cost, and the target will cooperate if and only if she is identical to the informant. Informant uses a Dutch auction to find the minimum possible reward that will reveal a Sybil attacker. Because our approach is economic, it is not limited to a specific application and does not rely on a physical device or token.

  15. Research on Human Face Detection%人脸检测技术研究

    Institute of Scientific and Technical Information of China (English)

    盛仲飙

    2012-01-01

    Face detection has became a research hotspot in the field of artificial intelligence in recent years, which is used as a key technology in face information processing. The paper briefly introduces the theoretical basis of face detection, and then the article describes the three commonly used methods such as pretreatment, threshold detection and edge detection. Focus on the key technologies of face detection—histogram threshold segmentation and edge detection, then simulation in the MATLAB environment. The results show, that only a combination of edge detection techniques can achieve the desired results.%人脸检测作为人脸信息处理中的一项关键技术,成为近年来人工智能领域内的一项研究热点.文章简要介绍了人脸检测的理论基础,讨论了人脸检测的预处理、阈值检测和边缘检测三种常用的方法;重点研究了直方图阈值分割和边缘检测这一关键技术,并在MATLAB环境下进行了仿真.通过结果可以看出,只有将边缘检测技术和其他方法结合起来才能达到理想的检测效果.

  16. Face detection for interactive tabletop viewscreen system using olfactory display

    Science.gov (United States)

    Sakamoto, Kunio; Kanazawa, Fumihiro

    2009-10-01

    An olfactory display is a device that delivers smells to the nose. It provides us with special effects, for example to emit smell as if you were there or to give a trigger for reminding us of memories. The authors have developed a tabletop display system connected with the olfactory display. For delivering a flavor to user's nose, the system needs to recognition and measure positions of user's face and nose. In this paper, the authors describe an olfactory display which enables to detect the nose position for an effective delivery.

  17. A face detection bias for horizontal orientations develops in middle childhood

    Directory of Open Access Journals (Sweden)

    Benjamin J Balas

    2015-06-01

    Full Text Available Faces are complex stimuli that can be described via intuitive facial features like the eyes, nose, and mouth, configural features like the distances between facial landmarks, and features that correspond to computations performed in the early visual system (e.g. oriented edges. With regard to this latter category of descriptors, adult face recognition relies disproportionately on information in specific spatial frequency and orientation bands: Many recognition tasks are performed more accurately when adults have access to mid-range spatial frequencies (8-16 cycles/face and horizontal orientations (Dakin & Watt, 2009. In the current study, we examined how this information bias develops in middle childhood. We recruited children between the ages of 5-10 years old to participate in a simple categorization task that required them to label images according to whether they depicted a face or a house. Critically, children were presented with face and house images comprised either of primarily horizontal orientation energy, primarily vertical orientation energy, or both horizontal and vertical orientation energy. We predicted that any bias favoring horizontal information over vertical should be more evident in faces than in houses, and also that older children would be more likely to show such a bias than younger children. We designed our categorization task to be sufficiently easy that children would perform at near-ceiling accuracy levels, but with variation in response times that would reflect how they rely on different orientations as a function of age and object category. We found that horizontal bias for face detection (but not house detection correlated significantly with age, suggesting an emergent category-specific bias for horizontal orientation energy that develops during middle childhood. These results thus suggest that the tuning of high-level recognition to specific low-level visual features takes take place over several years of visual

  18. Analysing animal behaviour in wildlife videos using face detection and tracking

    OpenAIRE

    2006-01-01

    An algorithm that categorises animal locomotive behaviour by combining detection and tracking of animal faces in wildlife videos is presented. As an example, the algorithm is applied to lion faces. The detection algorithm is based on a human face detection method, utilising Haar-like features and AdaBoost classifiers. The face tracking is implemented by applying a specific interest model that combines low-level feature tracking with the detection algorithm. By combining the two methods in a s...

  19. Face repetition detection and social interest: An ERP study in adults with and without Williams syndrome.

    Science.gov (United States)

    Key, Alexandra P; Dykens, Elisabeth M

    2016-12-01

    The present study examined possible neural mechanisms underlying increased social interest in persons with Williams syndrome (WS). Visual event-related potentials (ERPs) during passive viewing were used to compare incidental memory traces for repeated vs. single presentations of previously unfamiliar social (faces) and nonsocial (houses) images in 26 adults with WS and 26 typical adults. Results indicated that participants with WS developed familiarity with the repeated faces and houses (frontal N400 response), but only typical adults evidenced the parietal old/new effect (previously associated with stimulus recollection) for the repeated faces. There was also no evidence of exceptional salience of social information in WS, as ERP markers of memory for repeated faces vs. houses were not significantly different. Thus, while persons with WS exhibit behavioral evidence of increased social interest, their processing of social information in the absence of specific instructions may be relatively superficial. The ERP evidence of face repetition detection in WS was independent of IQ and the earlier perceptual differentiation of social vs. nonsocial stimuli. Large individual differences in ERPs of participants with WS may provide valuable information for understanding the WS phenotype and have relevance for educational and treatment purposes.

  20. Joint Transform Correlation for face tracking: elderly fall detection application

    Science.gov (United States)

    Katz, Philippe; Aron, Michael; Alfalou, Ayman

    2013-03-01

    In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

  1. A ciosed-loop algorithm to detect human face using color and reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    吴东晖; 叶秀清; 顾伟康

    2002-01-01

    A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.

  2. A closed-loop algorithm to detect human face using color and reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color “like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the varying lighting conditions and personal conditions.

  3. Adaboost multi-view face detection based on YCgCr skin color model

    Science.gov (United States)

    Lan, Qi; Xu, Zhiyong

    2016-09-01

    Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

  4. Eye spy: the predictive value of fixation patterns in detecting subtle and extreme emotions from faces.

    Science.gov (United States)

    Vaidya, Avinash R; Jin, Chenshuo; Fellows, Lesley K

    2014-11-01

    Successful social interaction requires recognizing subtle changes in the mental states of others. Deficits in emotion recognition are found in several neurological and psychiatric illnesses, and are often marked by disturbances in gaze patterns to faces, typically interpreted as a failure to fixate on emotionally informative facial features. However, there has been very little research on how fixations inform emotion recognition in healthy people. Here, we asked whether fixations predicted detection of subtle and extreme emotions in faces. We used a simple model to predict emotion detection scores from participants' fixation patterns. The best fit of this model heavily weighted fixations to the eyes in detecting subtle fear, disgust and surprise, with less weight, or zero weight, given to mouth and nose fixations. However, this model could not successfully predict detection of subtle happiness, or extreme emotional expressions, with the exception of fear. These findings argue that detection of most subtle emotions is best served by fixations to the eyes, with some contribution from nose and mouth fixations. In contrast, detection of extreme emotions and subtle happiness appeared to be less dependent on fixation patterns. The results offer a new perspective on some puzzling dissociations in the neuropsychological literature, and a novel analytic approach for the study of eye gaze in social or emotional settings.

  5. Stereotype Priming in Face Recognition: Interactions between Semantic and Visual Information in Face Encoding

    Science.gov (United States)

    Hills, Peter J.; Lewis, Michael B.; Honey, R. C.

    2008-01-01

    The accuracy with which previously unfamiliar faces are recognised is increased by the presentation of a stereotype-congruent occupation label [Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982a). "Semantic interpretation effects on memory for faces." "Memory & Cognition," 10, 195-206; Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982b).…

  6. Impact of eye detection error on face recognition performance

    NARCIS (Netherlands)

    Dutta, A.; Günther, Manuel; El Shafey, Laurent; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2015-01-01

    The locations of the eyes are the most commonly used features to perform face normalisation (i.e. alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this study, the authors study the sensitivity of open source implementations of five face

  7. Impact of eye detection error on face recognition performance

    NARCIS (Netherlands)

    Dutta, Abhishek; Günther, Manuel; El Shafey, Laurent; Veldhuis, Raymond; Spreeuwers, Luuk

    2015-01-01

    The locations of the eyes are the most commonly used features to perform face normalisation (i.e. alignment of facial features), which is an essential preprocessing stage of many face recognition systems. In this study, the authors study the sensitivity of open source implementations of five face re

  8. The Effect of Early Visual Deprivation on the Development of Face Detection

    Science.gov (United States)

    Mondloch, Catherine J.; Segalowitz, Sidney J.; Lewis, Terri L.; Dywan, Jane; Le Grand, Richard; Maurer, Daphne

    2013-01-01

    The expertise of adults in face perception is facilitated by their ability to rapidly detect that a stimulus is a face. In two experiments, we examined the role of early visual input in the development of face detection by testing patients who had been treated as infants for bilateral congenital cataract. Experiment 1 indicated that, at age 9 to…

  9. Face Detection and the Development of Own-Species Bias in Infant Macaques.

    Science.gov (United States)

    Simpson, Elizabeth A; Jakobsen, Krisztina V; Damon, Fabrice; Suomi, Stephen J; Ferrari, Pier F; Paukner, Annika

    2017-01-01

    In visually complex environments, numerous items compete for attention. Infants may exhibit attentional efficiency-privileged detection, attention capture, and holding-for face-like stimuli. However, it remains unknown when these biases develop and what role, if any, experience plays in this emerging skill. Here, nursery-reared infant macaques' (Macaca mulatta; n = 10) attention to faces in 10-item arrays of nonfaces was measured using eye tracking. With limited face experience, 3-week-old monkeys were more likely to detect faces and looked longer at faces compared to nonfaces, suggesting a robust face detection system. By 3 months, after peer exposure, infants looked faster to conspecific faces but not heterospecific faces, suggesting an own-species bias in face attention capture, consistent with perceptual attunement. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

  10. Automatic landmark detection and face recognition for side-view face images

    NARCIS (Netherlands)

    Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N.J.; Broemme, Arslan; Busch, Christoph

    2013-01-01

    In real-life scenarios where pose variation is up to side-view positions, face recognition becomes a challenging task. In this paper we propose an automatic side-view face recognition system designed for home-safety applications. Our goal is to recognize people as they pass through doors in order to

  11. Face Tracking with Low-level and High-level Information

    Institute of Scientific and Technical Information of China (English)

    XUDong; LIStan; LIUZhengkai

    2005-01-01

    Face Tracking is an important and difficult vision task. In this paper, the high-level frontal face detector information and the low-level color information are fused iteratively. With the multi-step fusion schemes, better face tracking performance is achieved, as demonstrated by the exhaustive experiments.

  12. The Use of Neural Networks in Real-time Face Detection

    Directory of Open Access Journals (Sweden)

    Kevin Curran

    2005-01-01

    Full Text Available As continual research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is in the construction of a robust real-time face detection system. Successfully constructing a real-time face detection system not only implies a system capable of analyzing video streams, but also naturally leads onto the solution to the problems of extremely constraint testing environments. Analyzing a video sequence is the current challenge since faces are constantly in dynamic motion, presenting many different possible rotational and illumination conditions. While solutions to the task of face detection have been presented, detection performances of many systems are heavily dependent upon a strictly constrained environment. The problem of detecting faces under gross variations remains largely uncovered. This study presents a real-time face detection system which uses an image based neural network to detect images.

  13. The effect of contrast polarity reversal on face detection: evidence of perceptual asymmetry from sweep VEP.

    Science.gov (United States)

    Liu-Shuang, Joan; Ales, Justin M; Rossion, Bruno; Norcia, Anthony M

    2015-03-01

    Contrast polarity inversion (i.e., turning dark regions light and vice versa) impairs face perception. We investigated the perceptual asymmetry between positive and negative polarity faces (matched for overall luminance) using a sweep VEP approach in the context of face detection (Journal of Vision 12 (2012) 1-18). Phase-scrambled face stimuli alternated at a rate of 3 Hz (6 images/s). The phase coherence of every other stimulus was parametrically increased so that a face gradually emerged over a 20-s stimulation sequence, leading to a 3 Hz response reflecting face detection. Contrary to the 6 Hz response, reflecting low-level visual processing, this 3 Hz response was larger and emerged earlier over right occipito-temporal channels for positive than negative polarity faces. Moreover, the 3 Hz response emerged abruptly to positive polarity faces, whereas it increased linearly for negative polarity faces. In another condition, alternating between a positive and a negative polarity face also elicited a strong 3 Hz response, indicating an asymmetrical representation of positive and negative polarity faces even at supra-threshold levels (i.e., when both stimuli were perceived as faces). Overall, these findings demonstrate distinct perceptual representations of positive and negative polarity faces, independently of low-level cues, and suggest qualitatively different detection processes (template-based matching for positive polarity faces vs. linear accumulation of evidence for negative polarity faces).

  14. High and low performers differ in the use of shape information for face recognition.

    Science.gov (United States)

    Kaufmann, Jürgen M; Schulz, Claudia; Schweinberger, Stefan R

    2013-06-01

    Previous findings demonstrated that increasing facial distinctiveness by means of spatial caricaturing improves face learning and results in modulations of event-related-potential (ERP) components associated with the processing of typical shape information (P200) and with face learning and recognition (N250). The current study investigated performance-based differences in the effects of spatial caricaturing: a modified version of the Bielefelder famous faces test (BFFT) was applied to subdivide a non-clinical group of 28 participants into better and worse face recognizers. Overall, a learning benefit was seen for caricatured compared to veridical faces. In addition, for learned faces we found larger caricaturing effects in response times, inverse efficiency scores as well as in P200 and N250 amplitudes in worse face recognizers, indicating that these individuals profited disproportionately from exaggerated idiosyncratic face shape. During learning and for novel faces at test, better and worse recognizers showed similar caricaturing effects. We suggest that spatial caricaturing helps better and worse face recognizers accessing critical idiosyncratic shape information that supports identity processing and learning of unfamiliar faces. For familiarized faces, better face recognizers might depend less on exaggerated shape and make better use of texture information than worse recognizers. These results shed light on the transition from unfamiliar to familiar face processing and may also be relevant for developing training-programmes for people with difficulties in face recognition.

  15. Neural correlates of own name and own face detection in autism spectrum disorder.

    Directory of Open Access Journals (Sweden)

    Hanna B Cygan

    Full Text Available Autism spectrum disorder (ASD is a heterogeneous neurodevelopmental condition clinically characterized by social interaction and communication difficulties. To date, the majority of research efforts have focused on brain mechanisms underlying the deficits in interpersonal social cognition associated with ASD. Recent empirical and theoretical work has begun to reveal evidence for a reduced or even absent self-preference effect in patients with ASD. One may hypothesize that this is related to the impaired attentional processing of self-referential stimuli. The aim of our study was to test this hypothesis. We investigated the neural correlates of face and name detection in ASD. Four categories of face/name stimuli were used: own, close-other, famous, and unknown. Event-related potentials were recorded from 62 electrodes in 23 subjects with ASD and 23 matched control subjects. P100, N170, and P300 components were analyzed. The control group clearly showed a significant self-preference effect: higher P300 amplitude to the presentation of own face and own name than to the close-other, famous, and unknown categories, indicating preferential attentional engagement in processing of self-related information. In contrast, detection of both own and close-other's face and name in the ASD group was associated with enhanced P300, suggesting similar attention allocation for self and close-other related information. These findings suggest that attention allocation in the ASD group is modulated by the personal significance factor, and that the self-preference effect is absent if self is compared to close-other. These effects are similar for physical and non-physical aspects of the autistic self. In addition, lateralization of face and name processing is attenuated in ASD, suggesting atypical brain organization.

  16. Detecting "Infant-Directedness" in Face and Voice

    Science.gov (United States)

    Kim, Hojin I.; Johnson, Scott P.

    2014-01-01

    Five- and 3-month-old infants' perception of infant-directed (ID) faces and the role of speech in perceiving faces were examined. Infants' eye movements were recorded as they viewed a series of two side-by-side talking faces, one infant-directed and one adult-directed (AD), while listening to ID speech, AD speech, or in silence. Infants…

  17. Real Time Detection and Tracking of Human Face using Skin Color Segmentation and Region Properties

    Directory of Open Access Journals (Sweden)

    Prashanth Kumar G.

    2014-07-01

    Full Text Available Real time faces detection and face tracking is one of the challenging problems in application like computer human interaction, video surveillance, biometrics etc. In this paper we are presenting an algorithm for real time face detection and tracking using skin color segmentation and region properties. First segmentation of skin regions from an image is done by using different color models. Skin regions are separated from the image by using thresholding. Then to decide whether these regions contain human face or not we used face features. Our procedure is based on skin color segmentation and human face features (knowledge-based approach. We have used RGB, YCbCr, and HSV color models for skin color segmentation. These color models with thresholds, help to remove non skin like pixel from an image. Each segmented skin regions are tested to know whether region is human face or not, by using human face features based on knowledge of geometrical properties of human face.

  18. Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments

    Directory of Open Access Journals (Sweden)

    Mohan M. Trivedi

    2008-04-01

    Full Text Available We present a multilevel system architecture for intelligent environments equipped with omnivideo arrays. In order to gain unobtrusive human awareness, real-time 3D human tracking as well as robust video-based face detection and tracking and face recognition algorithms are needed. We first propose a multiprimitive face detection and tracking loop to crop face videos as the front end of our face recognition algorithm. Both skin-tone and elliptical detections are used for robust face searching, and view-based face classification is applied to the candidates before updating the Kalman filters for face tracking. For video-based face recognition, we propose three decision rules on the facial video segments. The majority rule and discrete HMM (DHMM rule accumulate single-frame face recognition results, while continuous density HMM (CDHMM works directly with the PCA facial features of the video segment for accumulated maximum likelihood (ML decision. The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99% accuracy of the CDHMM rule. We then experiment on the system interactions with single person and group people by the integrated layers of activity awareness. We also discuss the speech-aided incremental learning of new faces.

  19. Integrated Detection, Tracking, and Recognition of Faces with Omnivideo Array in Intelligent Environments

    Directory of Open Access Journals (Sweden)

    Huang KohsiaS

    2008-01-01

    Full Text Available Abstract We present a multilevel system architecture for intelligent environments equipped with omnivideo arrays. In order to gain unobtrusive human awareness, real-time 3D human tracking as well as robust video-based face detection and tracking and face recognition algorithms are needed. We first propose a multiprimitive face detection and tracking loop to crop face videos as the front end of our face recognition algorithm. Both skin-tone and elliptical detections are used for robust face searching, and view-based face classification is applied to the candidates before updating the Kalman filters for face tracking. For video-based face recognition, we propose three decision rules on the facial video segments. The majority rule and discrete HMM (DHMM rule accumulate single-frame face recognition results, while continuous density HMM (CDHMM works directly with the PCA facial features of the video segment for accumulated maximum likelihood (ML decision. The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99% accuracy of the CDHMM rule. We then experiment on the system interactions with single person and group people by the integrated layers of activity awareness. We also discuss the speech-aided incremental learning of new faces.

  20. Task-Specific Codes for Face Recognition: How they Shape the Neural Representation of Features for Detection and Individuation

    Science.gov (United States)

    2008-01-01

    Background The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing. Methodology/Principal Findings Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right “fusiform face area”. Conclusions/Significance Our results demonstrate: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural

  1. An Innovative Face Detection Based on YCgCr Color Space

    Science.gov (United States)

    Ghazali, Kamarul Hawari Bin; Ma, Jie; Xiao, Rui; lubis, Solly Aryza

    It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection method that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space. Firstly, we build a skin Gaussian model in Cg-Cr color space. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions.

  2. Empirical analysis of cascade deformable models for multi-view face detection

    NARCIS (Netherlands)

    Orozco, Javier; Martinez, Brais; Pantic, Maja

    2015-01-01

    We present a multi-view face detector based on Cascade Deformable Part Models (CDPM). Over the last decade, there have been several attempts to extend the well-established Viola&Jones face detector algorithm to solve the problem of multi-view face detection. Recently a tree structure model for multi

  3. Suprasegmental information affects processing of talking faces at birth.

    Science.gov (United States)

    Guellai, Bahia; Mersad, Karima; Streri, Arlette

    2015-02-01

    From birth, newborns show a preference for faces talking a native language compared to silent faces. The present study addresses two questions that remained unanswered by previous research: (a) Does the familiarity with the language play a role in this process and (b) Are all the linguistic and paralinguistic cues necessary in this case? Experiment 1 extended newborns' preference for native speakers to non-native ones. Given that fetuses and newborns are sensitive to the prosodic characteristics of speech, Experiments 2 and 3 presented faces talking native and nonnative languages with the speech stream being low-pass filtered. Results showed that newborns preferred looking at a person who talked to them even when only the prosodic cues were provided for both languages. Nonetheless, a familiarity preference for the previously talking face is observed in the "normal speech" condition (i.e., Experiment 1) and a novelty preference in the "filtered speech" condition (Experiments 2 and 3). This asymmetry reveals that newborns process these two types of stimuli differently and that they may already be sensitive to a mismatch between the articulatory movements of the face and the corresponding speech sounds.

  4. Multi-View Algorithm for Face, Eyes and Eye State Detection in Human Image- Study Paper

    Directory of Open Access Journals (Sweden)

    Latesh Kumari

    2014-07-01

    Full Text Available For fatigue detection such as in the application of driver‟s fatigue monitoring system, the eye state analysis is one of the important and deciding steps to determine the fatigue of driver‟s eyes. In this study, algorithms for face detection, eye detection and eye state analysis have been studied and presented as well as an efficient algorithm for detection of face, eyes have been proposed. Firstly the efficient algorithm for face detection method has been presented which find the face area in the human images. Then, novel algorithms for detection of eye region and eye state are introduced. In this paper we propose a multi-view based eye state detection to determine the state of the eye. With the help of skin color model, the algorithm detects the face regions in an YCbCr color model. By applying the skin segmentation which normally separates the skin and non-skin pixels of the images, it detects the face regions of the image under various lighting and noise conditions. Then from these face regions, the eye regions are extracted within those extracted face regions. Our proposed algorithms are fast and robust as there is not pattern match.

  5. An own-age bias in recognizing faces with horizontal information

    Directory of Open Access Journals (Sweden)

    Andreas Schaich

    2016-11-01

    Full Text Available Horizontal information, as a result of a selective filtering process, are essential in younger adults’ (YA ability to recognize human faces. Obermeyer, Kolling, Schaich, and Knopf (2012 recently reported impaired recognition of faces with horizontal information in older adults (OA suggesting age-variant processing. Two yet unconsidered factors (stimulus age and exposure duration that may have influenced previous results, were investigated in this study. Forty-seven YA (18-35yrs and 49 OA (62-83yrs were tested in a 2x2x2x2 mixed design with the between-subjects factors age group (YA vs OA and stimulus age (young faces vs older faces and the within-subjects factors filter (filtered (HF faces vs unfiltered faces (UF and exposure duration (0.8s vs 8s. Subjects were presented morph videos between pairs of faces: A starting face gradually merged into either the previously encoded target face or a control face. As expected, results showed an increase in recognition sensitivity (d’ with longer exposure duration in YA with both younger and older HF faces. OA however were unable to recognize filtered young faces not even with increased exposure duration. Furthermore, only elderly participants showed more accurate recognition with faces of their own age relative to other-age faces (own-age bias, OAB. For YA no OAB was observed. Filtered face recognition was significantly correlated with unfiltered recognition in YA but not in OA. It is concluded, that processing of horizontal information changes at a higher age. Presenting filtered or unfiltered faces both targets convergent face-specific processing only in YA but not in OA.

  6. MULTI-VIEW FACE DETECTION BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS AND KERNEL SUPPORT VECTOR TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2011-05-01

    Full Text Available Detecting faces across multiple views is more challenging than in a frontal view. To address this problem,an efficient approach is presented in this paper using a kernel machine based approach for learning suchnonlinear mappings to provide effective view-based representation for multi-view face detection. In thispaper Kernel Principal Component Analysis (KPCA is used to project data into the view-subspaces thencomputed as view-based features. Multi-view face detection is performed by classifying each input imageinto face or non-face class, by using a two class Kernel Support Vector Classifier (KSVC. Experimentalresults demonstrate successful face detection over a wide range of facial variation in color, illuminationconditions, position, scale, orientation, 3D pose, and expression in images from several photo collections.

  7. Mutual information, perceptual independence, and holistic face perception.

    Science.gov (United States)

    Fitousi, Daniel

    2013-07-01

    The concept of perceptual independence is ubiquitous in psychology. It addresses the question of whether two (or more) dimensions are perceived independently. Several authors have proposed perceptual independence (or its lack thereof) as a viable measure of holistic face perception (Loftus, Oberg, & Dillon, Psychological Review 111:835-863, 2004; Wenger & Ingvalson, Learning, Memory, and Cognition 28:872-892, 2002). According to this notion, the processing of facial features occurs in an interactive manner. Here, I examine this idea from the perspective of two theories of perceptual independence: the multivariate uncertainty analysis (MUA; Garner & Morton, Definitions, models, and experimental paradigms. Psychological Bulletin 72:233-259, 1969), and the general recognition theory (GRT; Ashby & Townsend, Psychological Review 93:154-179, 1986). The goals of the study were to (1) introduce the MUA, (2) examine various possible relations between MUA and GRT using numerical simulations, and (3) apply the MUA to two consensual markers of holistic face perception(-)recognition of facial features (Farah, Wilson, Drain, & Tanaka, Psychological Review 105:482-498, 1998) and the composite face effect (Young, Hellawell, & Hay, Perception 16:747-759, 1987). The results suggest that facial holism is generated by violations of several types of perceptual independence. They highlight the important theoretical role played by converging operations in the study of holistic face perception.

  8. Online multi-face detection and tracking using detector confidence and structured SVMs

    NARCIS (Netherlands)

    Comaschi, F.; Stuijk, S.; Basten, A.A.; Corporaal, H.

    2015-01-01

    Online detection and tracking of a variable number of faces in video is a crucial component in many real-world applications ranging from video-surveillance to online gaming. In this paper we propose FAST-DT, a fully automated system capable of detecting and tracking a variable number of faces online

  9. A Joint Learning Approach to Face Detection in Wavelet Compressed Domain

    Directory of Open Access Journals (Sweden)

    Szu-Hao Huang

    2014-01-01

    Full Text Available Face detection has been an important and active research topic in computer vision and image processing. In recent years, learning-based face detection algorithms have prevailed with successful applications. In this paper, we propose a new face detection algorithm that works directly in wavelet compressed domain. In order to simplify the processes of image decompression and feature extraction, we modify the AdaBoost learning algorithm to select a set of complimentary joint-coefficient classifiers and integrate them to achieve optimal face detection. Since the face detection on the wavelet compression domain is restricted by the limited discrimination power of the designated feature space, the proposed learning mechanism is developed to achieve the best discrimination from the restricted feature space. The major contributions in the proposed AdaBoost face detection learning algorithm contain the feature space warping, joint feature representation, ID3-like plane quantization, and weak probabilistic classifier, which dramatically increase the discrimination power of the face classifier. Experimental results on the CBCL benchmark and the MIT + CMU real image dataset show that the proposed algorithm can detect faces in the wavelet compressed domain accurately and efficiently.

  10. Real-Time Illumination Invariant Face Detection Using Biologically Inspired Feature Set and BP Neural Network

    Directory of Open Access Journals (Sweden)

    Reza Azad

    2014-06-01

    Full Text Available In recent years, face detection has been thoroughly studied due to its wide potential applications, including face recognition, human-computer interaction, video surveillance, etc.In this paper, a new and illumination invariant face detection method, based on features inspired by the human's visual cortexand applying BP neural network on the extracted featureset is proposed.A feature set is extracted from face and non-face images, by means of a feed-forward model, which contains a view and illumination invariant C2 features from all images in the dataset. Then, these C2 feature vector which derived from a cortex-like mechanism passed to a BP neural network. In the result part, the proposed approach is applied on FEI and Wild face detection databases and high accuracy rate is achieved. In addition, experimental results have demonstrated our proposed face detector outperforms the most of the successful face detection algorithms in the literature and gives the first best result on all tested challenging face detection databases.

  11. Face Liveness Detection Using a Light Field Camera

    Directory of Open Access Journals (Sweden)

    Sooyeon Kim

    2014-11-01

    Full Text Available A light field camera is a sensor that can record the directions as well as the colors of incident rays. This camera is widely utilized from 3D reconstruction to face and iris recognition. In this paper, we suggest a novel approach for defending spoofing face attacks, like printed 2D facial photos (hereinafter 2D photos and HD tablet images, using the light field camera. By viewing the raw light field photograph from a different standpoint, we extract two special features which cannot be obtained from the conventional camera. To verify the performance, we compose light field photograph databases and conduct experiments. Our proposed method achieves at least 94.78% accuracy or up to 99.36% accuracy under different types of spoofing attacks.

  12. Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance

    Directory of Open Access Journals (Sweden)

    Nawaf Hazim Barnouti

    2016-05-01

    Full Text Available In this paper, an automatic face recognition system is proposed based on appearance-based features that focus on the entire face image rather than local facial features. The first step in face recognition system is face detection. Viola-Jones face detection method that capable of processing images extremely while achieving high detection rates is used. This method has the most impact in the 2000’s and known as the first object detection framework to provide relevant object detection that can run in real time. Feature extraction and dimension reduction method will be applied after face detection. Principal Component Analysis (PCA method is widely used in pattern recognition. Linear Discriminant Analysis (LDA method that used to overcome drawback the PCA has been successfully applied to face recognition. It is achieved by projecting the image onto the Eigenface space by PCA after that implementing pure LDA over it. Square Euclidean Distance (SED is used. The distance between two images is a major concern in pattern recognition. The distance between the vectors of two images leads to image similarity. The proposed method is tested on three databases (MUCT, Face94, and Grimace. Different number of training and testing images are used to evaluate the system performance and it show that increasing the number of training images will increase the recognition rate.

  13. A Detection Strategy of Multi-Pose Face in Compressed Domain

    Institute of Scientific and Technical Information of China (English)

    CHEN Lei; ZHOU Guo-fu

    2004-01-01

    In this paper, we present a strategy to implement multi-pose face detection in compressed domain.The strategy extracts firstly feature vectors from DCT domain, and then uses a boosting algorithm to build classifiers to distinguish faces and non-faces.Moreover, to get more accurate results of the face detection, we present a kernel function and a linear combination to build incrementally the strong classifiers based on the weak classifiers.Through comparing and analyzing results of some experiments on the synthetic data and the natural data, we can get more satisfied results by the strong classifiers than by the weak classifies.

  14. Can women detect cues to ovulation in other women's faces?

    Science.gov (United States)

    Lobmaier, Janek S; Bobst, Cora; Probst, Fabian

    2016-01-01

    Recent research suggests that men find portraits of ovulatory women more attractive than photographs of the same women taken during the luteal phase. Only few studies have investigated whether the same is true for women. The ovulatory phase matters to men because women around ovulation are most likely to conceive, and might matter to women because fertile women might pose a reproductive threat. In an online study 160 women were shown face pairs, one of which was assimilated to the shape of a late follicular prototype and the other to a luteal prototype, and were asked to indicate which face they found more attractive. A further 60 women were tested in the laboratory using a similar procedure. In addition to choosing the more attractive face, these participants were asked which woman would be more likely to steal their own date. Because gonadal hormones influence competitive behaviour, we also examined whether oestradiol, testosterone and progesterone levels predict women's choices. The women found neither the late follicular nor the luteal version more attractive. However, naturally cycling women with higher oestradiol levels were more likely to choose the ovulatory woman as the one who would entice their date than women with lower oestradiol levels. These results imply a role of oestradiol when evaluating other women who are competing for reproduction. © 2016 The Author(s).

  15. A Scale and Pose Invariant Algorithm for Fast Detecting Human Faces in a Complex Background

    Institute of Scientific and Technical Information of China (English)

    XING Xin; SHEN Lansun; JIA Kebin

    2001-01-01

    Human face detection is an interesting and challenging task in computer vision. A scale and pose invariant algorithm is proposed in this paper.The algorithm is able to detect human faces in a complex background in about 400ms with a detection rate of 92%. The algorithm can be used in a wide range of applications such as human-computer interface, video coding, etc.

  16. Sistem Kontrol Akses Berbasis Real Time Face Recognition dan Gender Information

    Directory of Open Access Journals (Sweden)

    Putri Nurmala

    2015-06-01

    Full Text Available Face recognition and gender information is a computer application for automatically identifying or verifying a person's face from a camera to capture a person's face. It is usually used in access control systems and it can be compared to other biometrics such as finger print identification system or iris. Many of face recognition algorithms have been developed in recent years. Face recognition system and gender information in this system based on the Principal Component Analysis method (PCA. Computational method has a simple and fast compared with the use of the method requires a lot of learning, such as artificial neural network. In this access control system, relay used and Arduino controller. In this essay focuses on face recognition and gender -based information in real time using the method of Principal Component Analysis ( PCA . The result achieved from the application design is the identification of a persons face with gender using PCA. The results achieved by the application is face recognition system using PCA can obtain good results the 85 % success rate in face recognition with face images that have been tested by a few people and a fairly high degree of accuracy.

  17. Face and voice as social stimuli enhance differential physiological responding in a Concealed Information Test

    Directory of Open Access Journals (Sweden)

    Wolfgang eAmbach

    2012-11-01

    Full Text Available Attentional, intentional, and motivational factors are known to influence the physiological responses in a Concealed Information Test (CIT. Although concealing information is essentially a social action closely related to motivation, CIT studies typically rely on testing participants in an environment lacking of social stimuli: Subjects interact with a computer while sitting alone in an experimental room. To address this gap, we examined the influence of social stimuli on the physiological responses in a CIT.Seventy-one participants underwent a mock-crime experiment with a modified CIT. In a between-subjects design, subjects were either questioned acoustically by a pre-recorded male voice presented together with a virtual male experimenter’s uniform face or by a text field on the screen, which displayed the question devoid of face and voice. Electrodermal activity (EDA, respiration line length (RLL, phasic heart rate (pHR, and finger pulse waveform length (FPWL were registered. The Psychopathic Personality Inventory - Revised (PPI-R was administered in addition. The differential responses of RLL, pHR, and FPWL to probe vs. irrelevant items were greater in the condition with social stimuli than in the text condition; interestingly, the differential responses of EDA did not differ between conditions. No modulatory influence of the PPI-R sum or subscale scores was found.The results emphasize the relevance of social aspects in the process of concealing information and in its detection. Attentional demands as well as the participants’ motivation to avoid detection might be the important links between social stimuli and physiological responses in the CIT.

  18. Effect of Affective Personality Information on Face Processing: Evidence from ERPs

    OpenAIRE

    Qiuling eLuo; Hanlin eWang; Milena eDzhelyova; Lei eMo

    2016-01-01

    This study tested the extent to which there are neural correlates of the influence of affective personality information on face processing, using event-related potentials (ERPs). In the learning phase, participants viewed a target individual’s face (with a neutral expression or faint smile) paired with negative, neutral or positive sentences describing the target’s previous typical behavior. In the following EEG testing phase, participants completed gender judgments of the learned faces. Stat...

  19. Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling.

    Science.gov (United States)

    Wantz, Andrea L; Lobmaier, Janek S; Mast, Fred W; Senn, Walter

    2017-08-01

    Recent research put forward the hypothesis that eye movements are integrated in memory representations and are reactivated when later recalled. However, "looking back to nothing" during recall might be a consequence of spatial memory retrieval. Here, we aimed at distinguishing between the effect of spatial and oculomotor information on perceptual memory. Participants' task was to judge whether a morph looked rather like the first or second previously presented face. Crucially, faces and morphs were presented in a way that the morph reactivated oculomotor and/or spatial information associated with one of the previously encoded faces. Perceptual face memory was largely influenced by these manipulations. We considered a simple computational model with an excellent match (4.3% error) that expresses these biases as a linear combination of recency, saccade, and location. Surprisingly, saccades did not play a role. The results suggest that spatial and temporal rather than oculomotor information biases perceptual face memory. Copyright © 2016 Cognitive Science Society, Inc.

  20. Empirical analysis of cascade deformable models for multi-view face detection

    NARCIS (Netherlands)

    Orozco, J.; Martinez, B.; Pantic, M.

    2013-01-01

    In this paper, we present a face detector based on Cascade Deformable Part Models (CDPM) [1]. Our model is learnt from partially labelled images using Latent Support Vector Machines (LSVM). Recently Zhu et al. [2] proposed a Tree StructureModel for multi-view face detection trained with facial landm

  1. Challenges Facing Adoption of Information Communication Technology in African Universities

    Science.gov (United States)

    Murgor, Titus Kiptoo

    2015-01-01

    A significant number of the universities and higher educational institutions have adopted the latest technology and implemented it productively, for the development of skilled human resource in respective area of specialization, as part of their responsibility. Information and communication Technology (ICT) has grown tremendously around the globe…

  2. The part task of the part-spacing paradigm is not a pure measurement of part-based information of faces.

    Directory of Open Access Journals (Sweden)

    Qi Zhu

    Full Text Available BACKGROUND: Faces are arguably one of the most important object categories encountered by human observers, yet they present one of the most difficult challenges to both the human and artificial visual systems. A variety of experimental paradigms have been developed to study how faces are represented and recognized, among which is the part-spacing paradigm. This paradigm is presumed to characterize the processing of both the featural and configural information of faces, and it has become increasingly popular for testing hypotheses on face specificity and in the diagnosis of face perception in cognitive disorders. METHODOLOGY/PRINCIPAL FINDINGS: In two experiments we questioned the validity of the part task of this paradigm by showing that, in this task, measuring pure information about face parts is confounded by the effect of face configuration on the perception of those parts. First, we eliminated or reduced contributions from face configuration by either rearranging face parts into a non-face configuration or by removing the low spatial frequencies of face images. We found that face parts were no longer sensitive to inversion, suggesting that the previously reported inversion effect observed in the part task was due in fact to the presence of face configuration. Second, self-reported prosopagnosic patients who were selectively impaired in the holistic processing of faces failed to detect part changes when face configurations were presented. When face configurations were scrambled, however, their performance was as good as that of normal controls. CONCLUSIONS/SIGNIFICANCE: In sum, consistent evidence from testing both normal and prosopagnosic subjects suggests the part task of the part-spacing paradigm is not an appropriate task for either measuring how face parts alone are processed or for providing a valid contrast to the spacing task. Therefore, conclusions from previous studies using the part-spacing paradigm may need re-evaluation with

  3. A comparison of the effectiveness of a game informed online learning activity and face to face teaching in increasing knowledge about managing aggression in health settings.

    Science.gov (United States)

    McKenzie, Karen

    2013-12-01

    The present study compared the impact of face to face teaching with a short online game informed learning activity on health participants' knowledge about, and confidence in, managing aggressive situations. Both forms of teaching resulted in a significant increase in participants' knowledge and confidence. Face to face training led to significantly greater increases in knowledge but was equivalent in terms of confidence. Both forms of teaching were rated positively, but face to face teaching received significantly higher ratings than the online activity. The study suggests that short online game informed learning activities may offer an effective alternative for health professional training where face to face training is not possible. Further research is needed on the longer term impact of both types of training on practice.

  4. The design and implementation of effective face detection and recognition system

    Science.gov (United States)

    Sun, Yigui

    2011-06-01

    In the paper, a face detection and recognition system (FDRS) based on video sequences and still image is proposed. It uses the AdaBoost algorithm to detect human face in the image or frame, adopts Discrete Cosine Transforms (DCT) for feature extraction and recognition in face image. The related technologies are firstly outlined. Then, the system requirements and UML use case diagram are described. In addition, the paper mainly introduces the design solution and key procedures. The FDRS's source-code is built in VC++, Standard Template Library (STL) and Intel Open Source Computer Vision Library (OpenCV).

  5. Two faces of entropy and information in biological systems.

    Science.gov (United States)

    Mitrokhin, Yuriy

    2014-10-21

    The article attempts to overcome the well-known paradox of contradictions between the emerging biological organization and entropy production in biological systems. It is assumed that quality, speculative correlation between entropy and antientropy processes taking place both in the past and today in the metabolic and genetic cellular systems may be perfectly authorized for adequate description of the evolution of biological organization. So far as thermodynamic entropy itself cannot compensate for the high degree of organization which exists in the cell, we discuss the mode of conjunction of positive entropy events (mutations) in the genetic systems of the past generations and the formation of organized structures of current cells. We argue that only the information which is generated in the conditions of the information entropy production (mutations and other genome reorganization) in genetic systems of the past generations provides the physical conjunction of entropy and antientropy processes separated from each other in time generations. It is readily apparent from the requirements of the Second law of thermodynamics.

  6. Face mask sampling for the detection of Mycobacterium tuberculosis in expelled aerosols.

    Directory of Open Access Journals (Sweden)

    Caroline M L Williams

    Full Text Available Although tuberculosis is transmitted by the airborne route, direct information on the natural output of bacilli into air by source cases is very limited. We sought to address this through sampling of expelled aerosols in face masks that were subsequently analyzed for mycobacterial contamination.In series 1, 17 smear microscopy positive patients wore standard surgical face masks once or twice for periods between 10 minutes and 5 hours; mycobacterial contamination was detected using a bacteriophage assay. In series 2, 19 patients with suspected tuberculosis were studied in Leicester UK and 10 patients with at least one positive smear were studied in The Gambia. These subjects wore one FFP30 mask modified to contain a gelatin filter for one hour; this was subsequently analyzed by the Xpert MTB/RIF system.In series 1, the bacteriophage assay detected live mycobacteria in 11/17 patients with wearing times between 10 and 120 minutes. Variation was seen in mask positivity and the level of contamination detected in multiple samples from the same patient. Two patients had non-tuberculous mycobacterial infections. In series 2, 13/20 patients with pulmonary tuberculosis produced positive masks and 0/9 patients with extrapulmonary or non-tuberculous diagnoses were mask positive. Overall, 65% of patients with confirmed pulmonary mycobacterial infection gave positive masks and this included 3/6 patients who received diagnostic bronchoalveolar lavages.Mask sampling provides a simple means of assessing mycobacterial output in non-sputum expectorant. The approach shows potential for application to the study of airborne transmission and to diagnosis.

  7. Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees

    Science.gov (United States)

    Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.

    2017-05-01

    Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.

  8. A new method for face detection in colour images for emotional bio-robots

    Institute of Scientific and Technical Information of China (English)

    HAPESHI; Kevin

    2010-01-01

    Emotional bio-robots have become a hot research topic in last two decades. Though there have been some progress in research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Comparing with existing algorithms, this method only relies on the colour and geometrical data of human face rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.

  9. Face Detection Based on Feature Tailoring and Skin Color Space

    Directory of Open Access Journals (Sweden)

    Jiang Wenbo

    2015-01-01

    Full Text Available This paper is used to solve the time-consuming problem of training samples in Adaboost algorithm and propose an improved FTAdaboost algorithm based on feature tailoring. In the beginning, this paper is used to make all samples have the same weight, train them once and tailor the features before the first reflection point of the error rate curve which have high error rate and poor classification ability, then reduce the number of samples and save training time. According to the distribution of facial organs, the algorithm determines whether the specified area meets the characteristics of skin-color space, then eliminates the influence of wrong facial images. The experimental results show that the algorithm based on feature tailoring can shorten the training time significantly and the detection with the skin-color space can decrease the error rate to some extent.

  10. A robust face detection method%一种稳健的人脸检测算法

    Institute of Scientific and Technical Information of China (English)

    彭定辉

    2012-01-01

    人脸检测是人脸识别系统的重要组成部分,对于安全级别较高或特殊场合的门禁系统而言,高准确率的人脸识别技术尤为重要.为提高门禁系统的安全性,采用了多种特征相结合的人脸识别算法,融合了背景分离、肤色检测、人脸五官特征检测、运动物体轮廓分析、人体运动跟踪等多种技术进行人脸检测测试,有效地解决了单一特征的人脸检测方法对人脸进行漏检和误检的问题.实验结果表明,该算法在复杂背景和光照条件不足以及有遮蔽物的情况下,均能快速准确地检测出人脸,误检率低.%Face detection is a major part of face identification system. A robust and efficient algorithm for face detection is particularly important for access control system which is applied in the situation of high security level or on some special occas-sions. In order to improve the security of access control system ,a face detection algorithm combined with multi-characteristics is proposed in the paper and used to detect human face, which combines background separation, complexion detection, face features detection, profile analysis of moving objects, and moving objects tracking. And the proposed method solves the problems of missing detection and false detection of human face caused by single-feature human face detection method. The experimental results indicate that the method detects human face fast and accurately with lower false detection rate in a complex background and in different lighting conditions.

  11. Does the Method of Instruction Matter? An Experimental Examination of Information Literacy Instruction in the Online, Blended, and Face-to-Face Classrooms

    Science.gov (United States)

    Anderson, Karen; May, Frances A.

    2010-01-01

    The researchers, a librarian and a faculty member, collaborated to investigate the effectiveness of delivery methods in information literacy instruction. The authors conducted a field experiment to explore how face-to-face, online, and blended learning instructional formats influenced students' retention of information literacy skills. Results are…

  12. Improving 2D Boosted Classifiers Using Depth LDA Classifier for Robust Face Detection

    Directory of Open Access Journals (Sweden)

    Mahmood Rahat

    2012-05-01

    Full Text Available Face detection plays an important role in Human Robot Interaction. Many of services provided by robots depend on face detection. This paper presents a novel face detection algorithm which uses depth data to improve the efficiency of a boosted classifier on 2D data for reduction of false positive alarms. The proposed method uses two levels of cascade classifiers. The classifiers of the first level deal with 2D data and classifiers of the second level use depth data captured by a stereo camera. The first level employs conventional cascade of boosted classifiers which eliminates many of nonface sub windows. The remaining sub windows are used as input to the second level. After calculating the corresponding depth model of the sub windows, a heuristic classifier along with a Linear Discriminant analysis (LDA classifier is applied on the depth data to reject remaining non face sub windows. The experimental results of the proposed method using a Bumblebee-2 stereo vision system on a mobile platform for real time detection of human faces in natural cluttered environments reveal significantly reduction of false positive alarms of 2D face detector.

  13. Face, Body, and Center of Gravity Mediate Person Detection in Natural Scenes

    Science.gov (United States)

    Bindemann, Markus; Scheepers, Christoph; Ferguson, Heather J.; Burton, A. Mike

    2010-01-01

    Person detection is an important prerequisite of social interaction, but is not well understood. Following suggestions that people in the visual field can capture a viewer's attention, this study examines the role of the face and the body for person detection in natural scenes. We observed that viewers tend first to look at the center of a scene,…

  14. Automatic Detection of Frontal Face Midline by Chain-coded Merlin-Farber Hough Trasform

    Science.gov (United States)

    Okamoto, Daichi; Ohyama, Wataru; Wakabayashi, Tetsushi; Kimura, Fumitaka

    We propose a novel approach for detection of the facial midline (facial symmetry axis) from a frontal face image. The facial midline has several applications, for instance reducing computational cost required for facial feature extraction (FFE) and postoperative assessment for cosmetic or dental surgery. The proposed method detects the facial midline of a frontal face from an edge image as the symmetry axis using the Merlin-Faber Hough transformation. And a new performance improvement scheme for midline detection by MFHT is present. The main concept of the proposed scheme is suppression of redundant vote on the Hough parameter space by introducing chain code representation for the binary edge image. Experimental results on the image dataset containing 2409 images from FERET database indicate that the proposed algorithm can improve the accuracy of midline detection from 89.9% to 95.1 % for face images with different scales and rotation.

  15. The Positivity Bias Phenomenon in Face Perception Given Different Information on Ability

    Directory of Open Access Journals (Sweden)

    Lei Mo

    2017-04-01

    Full Text Available The negativity bias has been shown in many fields, including in face processing. We assume that this bias stems from the potential threat inlayed in the stimuli (e.g., negative moral behaviors in previous studies. In the present study, we conducted one behavioral and one event-related potentials (ERPs experiments to test whether the positivity bias rather than negativity bias will arise when participants process information whose negative aspect involves no threat, i.e., the ability information. In both experiments, participants first completed a valence rating (negative-to-positive of neutral facial expressions. Further, in the learning period, participants associated the neutral faces with high-ability, low-ability, or control sentences. Finally, participants rated these facial expressions again. Results of the behavioral experiment showed that compared with pre-learning, the expressions of the faces associated with high ability sentences were classified as more positive in the post-learning expression rating task, and the faces associated with low ability sentences were evaluated as more negative. Meanwhile, the change in the high-ability group was greater than that of the low-ability group. The ERP data showed that the faces associated with high-ability sentences elicited a larger early posterior negativity, an ERP component considered to reflect early sensory processing of the emotional stimuli, than the faces associated with control sentences. However, no such effect was found in faces associated with low-ability sentences. To conclude, high ability sentences exerted stronger influence on expression perception than did low ability ones. Thus, we found a positivity bias in this ability-related facial perceptual task. Our findings demonstrate an effect of valenced ability information on face perception, thereby adding to the evidence on the opinion that person-related knowledge can influence face processing. What’s more, the positivity

  16. The Positivity Bias Phenomenon in Face Perception Given Different Information on Ability.

    Science.gov (United States)

    Zhao, Sasa; Xiang, Yanhui; Xie, Jiushu; Ye, Yanyan; Li, Tianfeng; Mo, Lei

    2017-01-01

    The negativity bias has been shown in many fields, including in face processing. We assume that this bias stems from the potential threat inlayed in the stimuli (e.g., negative moral behaviors) in previous studies. In the present study, we conducted one behavioral and one event-related potentials (ERPs) experiments to test whether the positivity bias rather than negativity bias will arise when participants process information whose negative aspect involves no threat, i.e., the ability information. In both experiments, participants first completed a valence rating (negative-to-positive) of neutral facial expressions. Further, in the learning period, participants associated the neutral faces with high-ability, low-ability, or control sentences. Finally, participants rated these facial expressions again. Results of the behavioral experiment showed that compared with pre-learning, the expressions of the faces associated with high ability sentences were classified as more positive in the post-learning expression rating task, and the faces associated with low ability sentences were evaluated as more negative. Meanwhile, the change in the high-ability group was greater than that of the low-ability group. The ERP data showed that the faces associated with high-ability sentences elicited a larger early posterior negativity, an ERP component considered to reflect early sensory processing of the emotional stimuli, than the faces associated with control sentences. However, no such effect was found in faces associated with low-ability sentences. To conclude, high ability sentences exerted stronger influence on expression perception than did low ability ones. Thus, we found a positivity bias in this ability-related facial perceptual task. Our findings demonstrate an effect of valenced ability information on face perception, thereby adding to the evidence on the opinion that person-related knowledge can influence face processing. What's more, the positivity bias in non

  17. Multimodal processing of emotional information in 9-month-old infants I: emotional faces and voices.

    Science.gov (United States)

    Otte, R A; Donkers, F C L; Braeken, M A K A; Van den Bergh, B R H

    2015-04-01

    Making sense of emotions manifesting in human voice is an important social skill which is influenced by emotions in other modalities, such as that of the corresponding face. Although processing emotional information from voices and faces simultaneously has been studied in adults, little is known about the neural mechanisms underlying the development of this ability in infancy. Here we investigated multimodal processing of fearful and happy face/voice pairs using event-related potential (ERP) measures in a group of 84 9-month-olds. Infants were presented with emotional vocalisations (fearful/happy) preceded by the same or a different facial expression (fearful/happy). The ERP data revealed that the processing of emotional information appearing in human voice was modulated by the emotional expression appearing on the corresponding face: Infants responded with larger auditory ERPs after fearful compared to happy facial primes. This finding suggests that infants dedicate more processing capacities to potentially threatening than to non-threatening stimuli.

  18. Effect of Affective Personality Information on Face Processing: Evidence from ERPs

    Directory of Open Access Journals (Sweden)

    Qiuling eLuo

    2016-05-01

    Full Text Available This study tested the extent to which there are neural correlates of the influence of affective personality information on face processing, using event-related potentials (ERPs. In the learning phase, participants viewed a target individual’s face (with a neutral expression or faint smile paired with negative, neutral or positive sentences describing the target’s previous typical behavior. In the following EEG testing phase, participants completed gender judgments of the learned faces. Statistical analyses were conducted on measures of neural activity during the gender judgment task. Repeated measures ANOVA of ERP data showed that faces described as having a negative personality elicited larger N170 than did those with a neutral or positive description. The early posterior negativity (EPN showed the same pattern, with larger amplitudes for faces paired with negative personality than for others. The size of the late positive potential (LPP was larger for faces paired with positive personality than for those with neutral and negative personality. The current study indicates that affective personality information is associated with an automatic, top-down modulation of face processing.

  19. An Information-Theoretic Measure for Face Recognition: Comparison with Structural Similarity

    Directory of Open Access Journals (Sweden)

    Asmhan Flieh Hassan

    2014-11-01

    Full Text Available Automatic recognition of people faces is a challenging problem that has received significant attention from signal processing researchers in recent years. This is due to its several applications in different fields, including security and forensic analysis. Despite this attention, face recognition is still one among the most challenging problems. Up to this moment, there is no technique that provides a reliable solution to all situations. In this paper a novel technique for face recognition is presented. This technique, which is called ISSIM, is derived from our recently published information - theoretic similarity measure HSSIM, which was based on joint histogram. Face recognition with ISSIM is still based on joint histogram of a test image and a database images. Performance evaluation was performed on MATLAB using part of the well-known AT&T image database that consists of 49 face images, from which seven subjects are chosen, and for each subject seven views (poses are chosen with different facial expressions. The goal of this paper is to present a simplified approach for face recognition that may work in real-time environments. Performance of our information - theoretic face recognition method (ISSIM has been demonstrated experimentally and is shown to outperform the well-known, statistical-based method (SSIM.

  20. Distinct representations of configural and part information across multiple face- selective regions of the human brain

    Directory of Open Access Journals (Sweden)

    Golijeh eGolarai

    2015-11-01

    Full Text Available Several regions of the human brain respond more strongly to faces than to other visual stimuli, such as regions in the amygdala (AMG, superior temporal sulcus (STS, and the fusiform face area (FFA. It is unclear if these brain regions are similar in representing the configuration or natural appearance of face parts. We used functional magnetic resonance imaging of healthy adults who viewed natural or schematic faces with internal parts that were either normally configured or randomly rearranged. Response amplitudes were reduced in the AMG and STS when subjects viewed stimuli whose configuration of parts were digitally rearranged, suggesting representation of the 1st order configuration of face parts. In contrast, response amplitudes in the FFA showed little modulation whether face parts were rearranged or if the natural face parts were replaced with lines. Instead, FFA responses were reduced only when both configural and part information were reduced, revealing an interaction between these factors, suggesting distinct representation of 1st order face configuration and parts in the AMG and STS vs. the FFA.

  1. The effect of preoperative nutritional face-to-face counseling about child's fasting on parental knowledge, preoperative need-for-information, and anxiety, in pediatric ambulatory tonsillectomy.

    Science.gov (United States)

    Klemetti, Seija; Kinnunen, Ilpo; Suominen, Tarja; Antila, Heikki; Vahlberg, Tero; Grenman, Reidar; Leino-Kilpi, Helena

    2010-07-01

    The objective of this study was to define how preoperative nutritional face-to-face counseling on child's fasting affects parental knowledge, preoperative need-for-information, and anxiety, in pediatric ambulatory tonsillectomy. The participants in the prospective, randomly allocated study were parents (intervention 62/control 62) with children (4-10 years) admitted for ambulatory tonsillectomy. Data were collected by the knowledge test designed for the study and with The Amsterdam preoperative anxiety and information scale (APAIS). The intervention group was invited to a preoperative visit to receive written and verbal face-to-face counseling. They were initiated into the child's active preoperative nutrition. The parents of the control group received current information without face-to-face counseling. The parents followed the instructions. Their knowledge about the child's fast increased (p=0.003), and need-for-information and anxiety decreased (ppreoperative face-to-face counseling with written information improves parental knowledge about the child's fasting and active preoperative nutrition, and relieves their need-for-information and anxiety. The primary responsibility remains with the health care professionals when the active preoperative nutrition of the child and counseling on it are introduced into nursing practice. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  2. Covert channel detection using Information Theory

    CERN Document Server

    Hélouët, Loïc; 10.4204/EPTCS.51.3

    2011-01-01

    This paper presents an information theory based detection framework for covert channels. We first show that the usual notion of interference does not characterize the notion of deliberate information flow of covert channels. We then show that even an enhanced notion of "iterated multivalued interference" can not capture flows with capacity lower than one bit of information per channel use. We then characterize and compute the capacity of covert channels that use control flows for a class of systems.

  3. Covert channel detection using Information Theory

    Directory of Open Access Journals (Sweden)

    Loïc Hélouët

    2011-02-01

    Full Text Available This paper presents an information theory based detection framework for covert channels. We first show that the usual notion of interference does not characterize the notion of deliberate information flow of covert channels. We then show that even an enhanced notion of "iterated multivalued interference" can not capture flows with capacity lower than one bit of information per channel use. We then characterize and compute the capacity of covert channels that use control flows for a class of systems.

  4. Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition.

    Science.gov (United States)

    Galbally, Javier; Marcel, Sébastien; Fierrez, Julian

    2014-02-01

    To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.

  5. A Hybrid method of face detection based on Feature Extraction using PIFR and Feature Optimization using TLBO

    Directory of Open Access Journals (Sweden)

    Kapil Verma

    2016-01-01

    Full Text Available In this paper we proposed a face detection method based on feature selection and feature optimization. Now in current research trend of biometric security used the process of feature optimization for better improvement of face detection technique. Basically our face consists of three types of feature such as skin color, texture and shape and size of face. The most important feature of face is skin color and texture of face. In this detection technique used texture feature of face image. For the texture extraction of image face used partial feature extraction function, these function is most promising shape feature analysis. For the selection of feature and optimization of feature used multi-objective TLBO. TLBO algorithm is population based searching technique and defines two constraints function for the process of selection and optimization. The proposed algorithm of face detection based on feature selection and feature optimization process. Initially used face image data base and passes through partial feature extractor function and these transform function gives a texture feature of face image. For the evaluation of performance our proposed algorithm implemented in MATLAB 7.8.0 software and face image used provided by Google face image database. For numerical analysis of result used hit and miss ratio. Our empirical evaluation of result shows better prediction result in compression of PIFR method of face detection.

  6. The representation of information about faces in the temporal and frontal lobes.

    Science.gov (United States)

    Rolls, Edmund T

    2007-01-07

    Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximising the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalisation and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses, generalise to other views of the same face. A theory is described of how such invariant representations may be produced in a hierarchically organised set of visual cortical areas with convergent connectivity. The theory proposes that neurons in these visual areas use a modified Hebb synaptic modification rule with a short-term memory trace to capture whatever can be captured at each stage that is invariant about objects as the objects change in retinal view, position, size and rotation. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye gaze, face view and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found

  7. The Evaluation of Face to Face and Web-Based Information Sharing Contexts between Teachers and Academicians from the Viewpoints of the Participants

    Directory of Open Access Journals (Sweden)

    Fatih Baş

    2014-12-01

    Full Text Available The aim of this study is; evaluated the web-based and face to face information sharing context between teachers and academicians from the viewpoints of the participants. Web-based context has 13 academician - 72 teacher and face to face context has 6 academicians -17 teachers participants. The holistic case study method was adopted in the study and the data were collected via unstructured interviews  with 5 teachers and 5 academicians who participated in the information sharing processes in both contexts. The content analyses were conducted and the findings showed that coming together and sharing information were considered a positive aspect of these contexts by teachers and academicians. The participants stated that there were some factors decreasing their participation rate in the web-based context stemming from the structure of web-page, the posts in the page, views of the participants and necessary conditions. However, the participants added that teachers having similar teaching applications decreased their information sharing in the face to face context. It was recommended to use both context together based on the recommendations from the participants and the relevant literature.Key Words:    Information sharing between teacher and academician, web-based communication, face to face communication

  8. Distance Metric Learning Using Privileged Information for Face Verification and Person Re-Identification.

    Science.gov (United States)

    Xu, Xinxing; Li, Wen; Xu, Dong

    2015-12-01

    In this paper, we propose a new approach to improve face verification and person re-identification in the RGB images by leveraging a set of RGB-D data, in which we have additional depth images in the training data captured using depth cameras such as Kinect. In particular, we extract visual features and depth features from the RGB images and depth images, respectively. As the depth features are available only in the training data, we treat the depth features as privileged information, and we formulate this task as a distance metric learning with privileged information problem. Unlike the traditional face verification and person re-identification tasks that only use visual features, we further employ the extra depth features in the training data to improve the learning of distance metric in the training process. Based on the information-theoretic metric learning (ITML) method, we propose a new formulation called ITML with privileged information (ITML+) for this task. We also present an efficient algorithm based on the cyclic projection method for solving the proposed ITML+ formulation. Extensive experiments on the challenging faces data sets EUROCOM and CurtinFaces for face verification as well as the BIWI RGBD-ID data set for person re-identification demonstrate the effectiveness of our proposed approach.

  9. vMMN for schematic faces: automatic detection of change in emotional expression

    Directory of Open Access Journals (Sweden)

    Kairi eKreegipuu

    2013-10-01

    Full Text Available Our brain is able to automatically detect changes in sensory stimulation, including in vision. A large variety of changes of features in stimulation elicit a deviance-reflecting ERP component known as the mismatch negativity (MMN. The present study has three main goals: (1 to register vMMN using a rapidly presented stream of schematic faces (neutral, happy, angry; adapted from Öhman et al., 2001; (2 to compare elicited vMMNs to angry and happy schematic faces in two different paradigms, in a traditional oddball design with frequent standard and rare target and deviant stimuli (12.5% each and in an version of an optimal multi-feature paradigm with several deviant stimuli (altogether 37.5% in the stimulus block; (3 to compare vMMNs to subjective ratings of valence, arousal and attention capture for happy and angry schematic faces, i.e., to estimate the effect of affective value of stimuli on their automatic detection. Eleven observers (19-32 years, 6 women took part in both experiments, an oddball and optimum paradigm. Stimuli were rapidly presented schematic faces and an object with face-features that served as the target stimulus to be detected by a button-press. Results show that a vMMN-type response at posterior sites was equally elicited in both experiments. Post-experimental reports confirmed that the angry face attracted more automatic attention than the happy face but the difference did not emerge directly at the ERP level. Thus, when interested in studying change detection in facial expressions we encourage the use of the optimum (multi-feature design in order to save time and other experimental resources.

  10. Effect of Affective Personality Information on Face Processing: Evidence from ERPs.

    Science.gov (United States)

    Luo, Qiu L; Wang, Han L; Dzhelyova, Milena; Huang, Ping; Mo, Lei

    2016-01-01

    This study explored the extent to which there are the neural correlates of the affective personality influence on face processing using event-related potentials (ERPs). In the learning phase, participants viewed a target individual's face (expression neutral or faint smile) paired with either negative, neutral or positive sentences describing previous typical behavior of the target. In the following EEG testing phase, participants completed gender judgments of the learned faces. Statistical analyses were conducted on measures of neural activity during the gender judgment task. Repeated measures ANOVA of ERP data showed that faces described as having a negative personality elicited larger N170 than did those with a neutral or positive description. The early posterior negativity (EPN) showed the same result pattern, with larger amplitudes for faces paired with negative personality than for others. The size of the late positive potential was larger for faces paired with positive personality than for those with neutral and negative personality. The current study indicates that affective personality information is associated with an automatic, top-down modulation on face processing.

  11. P2-32: Influence of Spatial Frequency Information on Face Gender with Different Expressions

    Directory of Open Access Journals (Sweden)

    Kuei-An Li

    2012-10-01

    Full Text Available Visual image contains broadband information and is processed by different neural channels that are tuned to different spatial frequencies. Here we investigated whether or not our ability in gender identification on emotional faces was influenced by this early visual processing. Four types of emotional (happy, anger, sad, and fear faces were used, and all of the stimuli were processed by spatial frequency analysis. Spatial frequency content in the original faces was filtered by using a high-pass filter (cut-off frequency was 24 cycles/image for the HSF stimuli, and a low-pass filter (cut-off frequency was 6 cycles/image for the LSF stimuli. Participants needed to identify the gender of the faces. The results showed that the participants responded faster and had higher accuracy to LSF faces than to HSF ones. They also responded faster and had higher accuracy to male faces than to female faces. Further analysis revealed that the identification of an angry man and a happy woman had advantage among combinations of genders and emotions in LSF conditions. However, this advantage was not manifested in HSF conditions. We concluded that the identification of gender with different emotions may rely on the processing of low spatial frequency channels.

  12. Nonlinear amygdala response to face trustworthiness: contributions of high and low spatial frequency information.

    Science.gov (United States)

    Said, Christopher P; Baron, Sean G; Todorov, Alexander

    2009-03-01

    Previous neuroimaging research has shown amygdala sensitivity to the perceived trustworthiness of neutral faces, with greater responses to untrustworthy compared with trustworthy faces. This observation is consistent with the common view that the amygdala encodes fear and is preferentially responsive to negative stimuli. However, some studies have shown greater amygdala activation to positive compared with neutral stimuli. The first goal of this study was to more fully characterize the amygdala response to face trustworthiness by modeling its activation with both linear and nonlinear predictors. Using fMRI, we report a nonmonotonic response profile, such that the amygdala responds strongest to highly trustworthy and highly untrustworthy faces. This finding complicates future attempts to make inferences about mental states based on activation in the amygdala. The second goal of the study was to test for modulatory effects of image spatial frequency filtering on the amygdala response. We predicted greater amygdala sensitivity to face trustworthiness for low spatial frequency images compared with high spatial frequency images. Instead, we found that both frequency ranges provided sufficient information for the amygdala to differentiate faces on trustworthiness. This finding is consistent with behavioral results and suggests that trustworthiness information may reach the amygdala through pathways carrying both coarse and fine resolution visual signals.

  13. Automatic detection of trustworthiness of the face: a visual mismatch negativity study.

    Science.gov (United States)

    Kovács-Bálint, Z; Stefanics, G; Trunk, A; Hernádi, I

    2014-03-01

    Recognizing intentions of strangers from facial cues is crucial in everyday social interactions. Recent studies demonstrated enhanced event-related potential (ERP) responses to untrustworthy compared to trustworthy faces. The aim of the present study was to investigate the electrophysiological correlates of automatic processing of trustworthiness cues in a visual oddball paradigm in two consecutive experimental blocks. In one block, frequent trustworthy (p = 0.9) and rare untrustworthy face stimuli (p = 0.1) were briefly presented on a computer screen with each stimulus consisting of four peripherally positioned faces. In the other block stimuli were presented with reversed probabilities enabling the comparison of ERPs evoked by physically identical deviant and standard stimuli. To avoid attentional effects participants engaged in a central detection task. Analyses of deviant minus standard difference waveforms revealed that deviant untrustworthy but not trustworthy faces elicited the visual mismatch negativity (vMMN) component. The present results indicate that adaptation occurred to repeated unattended trustworthy (but not untrustworthy) faces, i.e., an automatic expectation was elicited towards trustworthiness signals, which was violated by deviant untrustworthy faces. As an evolutionary adaptive mechanism, the observed fast detection of trustworthiness-related social facial cues may serve as the basis of conscious recognition of reliable partners.

  14. Face Detection Based on Image Segmentation%基于图像分割的人脸检测

    Institute of Scientific and Technical Information of China (English)

    李艳; 陈虹洁

    2011-01-01

    人脸检测作为人脸识别中的关键问题之一,近年来受到了越来越多的关注。通常采集到人脸信息非常丰富,无法直接判断脸部信息和背景信息。因此,需要一种有效的方法来解决图像的分类问题。数据挖掘中的聚类分析方法能对大量数据进行有效划分,为人脸检测中的图像分割提供了新的研究思路。%As one of the key points in face recognition, face detection has been paid more and more attention in recent years.However, we usually can not directly distinguish the face from the background of massive image information we collected.So,we need an effective method to solve image classification problems.Cluster analysis method in data mining can effectively divide large amounts of data,and provides a new research idea for image segmentation in human face detection.

  15. Face-to-face and electronic communications in maintaining social networks : the influence of geographical and relational distance and of information content

    NARCIS (Netherlands)

    Tillema, Taede; Dijst, Martin; Schwanen, Tim

    2010-01-01

    Using data collected among 742 respondents, this article aims at gaining greater insight into (i) the interaction between face-to-face (F2F) and electronic contacts, (ii) the influence of information content and relational distance on the communication mode/service choice and (iii) the influence of

  16. GPU Implementation of Real-Time Biologically Inspired Face Detection using CUDA

    Directory of Open Access Journals (Sweden)

    Elham Askary

    2013-07-01

    Full Text Available In this paper massively parallel real-time face detection based on a visual attention and cortex-like mechanism of cognitive vision system is presented. As a first step, we use saliency map model to select salient face regions and HMAX C1 model to extract features from salient input image and then apply mixture of expert neural network to classify multi-view faces from nonface images. The saliency map model is a complex concept for bottom-up attention selection that includes many processes to find face regions in a visual science. Parallel real-time implementation on Graphics Processing Unit (GPU provides a solution for this kind of computationally intensive image processing. By implementing saliency map and HMAX C1 model on a multi-GPU platform using CUDA programming with memory bandwidth, we achieve good performance compared to recent CPU. Running on NVIDIA Geforce 8800 (GTX graphics card at resolution 640×480 detection rate of 97% is achieved. In addition, we evaluate our results using a height speed camera with other parallel methods on face detection application.

  17. A Self-Determination Perspective on Online Health Information Seeking: The Internet vs. Face-to-Face Office Visits With Physicians.

    Science.gov (United States)

    Lee, Seow Ting; Lin, Julian

    2016-06-01

    This study elucidates the experiential and motivational aspects of online health information beyond the theoretically limited instrumental perspective that dominates the extant literature. Based on a sample of 993 online health information seekers in India, the survey found that online health information seeking offers individuals greater autonomy, competence, and relatedness compared to face-to-face office visits with physicians. According to self-determination theory, individuals are motivated to act by a sense of volition and experience of willingness, validation of one's skills and competencies, and feeling of connection with others who shaped one's decisions. These 3 psychological needs, which motivate individuals to pursue what they innately seek as human beings, help explain why individuals turn online for health information. T tests showed that all 3 self-determination theory constructs -autonomy, competence, and relatedness-were higher for online health information seeking than for face-to-face office visits with physicians. A regression analysis found that 2 variables, autonomy and relatedness, explained online health information seeking. Competence was not a significant factor, likely because of competency issues faced by individuals in interpreting, understanding, and making use of online health information. The findings, which do not suggest that online health information seeking would displace physicians as many have feared, offer promise for an integrated system of care. Office visits with physicians would necessarily evolve into an expanded communicative space of health information seeking instead of an alternative channel for health information.

  18. Multi-Cue-Based Face and Facial Feature Detection on Video Segments

    Institute of Scientific and Technical Information of China (English)

    PENG ZhenYun(彭振云); AI HaiZhou(艾海舟); Hong Wei(洪微); LIANG LuHong(梁路宏); XU GuangYou(徐光祐)

    2003-01-01

    An approach is presented to detect faces and facial features on a video segmentbased on multi-cues, including gray-level distribution, color, motion, templates, algebraic featuresand so on. Faces are first detected across the frames by using color segmentation, template matchingand artificial neural network. A PCA-based (Principal Component Analysis) feature detector forstill images is then used to detect facial features on each single frame until the resulting features ofthree adjacent frames, named as base frames, are consistent with each other. The features of framesneighboring the base frames are first detected by the still-image feature detector, then verifiedand corrected according to the smoothness constraint and the planar surface motion constraint.Experiments have been performed on video segments captured under different environments, andthe presented method is proved to be robust and accurate over variable poses, ages and illuminationconditions.

  19. Enhancing community detection by local structural information

    CERN Document Server

    Xiang, Ju; Zhang, Yan; Bao, Mei-Hua; Tang, Liang; Tang, Yan-Ni; Gao, Yuan-Yuan; Li, Jian-Ming; Chen, Benyan; Hu, Jing-Bo

    2016-01-01

    Many real-world networks such as the gene networks, protein-protein interaction networks and metabolic networks exhibit community structures, meaning the existence of groups of densely connected vertices in the networks. Many local similarity measures in the networks are closely related to the concept of the community structures, and may have positive effect on community detection in the networks. Here, various local similarity measures are used to extract the local structural information and then are applied to community detection in the networks by using the edge-reweighting strategy. The effect of the local similarity measures on community detection is carefully investigated and compared in various networks. The experimental results show that the local similarity measures are crucial to the improvement for the community detection methods, while the positive effect of the local similarity measures is closely related to the networks under study and the applied community detection methods.

  20. 人脸检测实现算法研究.%A Survey on Face Detection

    Institute of Scientific and Technical Information of China (English)

    刘爽

    2011-01-01

    本文总结回顾了人脸检测的主要内容、难点、分类、检测方法,主要是基于知识、基于模板、基于特征以及基于外观的方法,最后回顾了人脸检测算法的速度发展历程,其中P.Viola提出的Adaboost算法和Cascade算法使人脸检测从真正意义上走向实用.%This paper is mainly about the dominating approach to implementing face detection, which is based on knowledge, template, feature or appearance. In addition, the paper also talks about the difficulties of face detection and how to classify it. Last but not least, summary of the time complexity development of face detection is discussed. In particular, the Adaboost algorithm and Cascade algorithm proposed by P.Viola made face detection practical.

  1. How affective information from faces and scenes interacts in the brain.

    Science.gov (United States)

    Van den Stock, Jan; Vandenbulcke, Mathieu; Sinke, Charlotte B A; Goebel, Rainer; de Gelder, Beatrice

    2014-10-01

    Facial expression perception can be influenced by the natural visual context in which the face is perceived. We performed an fMRI experiment presenting participants with fearful or neutral faces against threatening or neutral background scenes. Triangles and scrambled scenes served as control stimuli. The results showed that the valence of the background influences face selective activity in the right anterior parahippocampal place area (PPA) and subgenual anterior cingulate cortex (sgACC) with higher activation for neutral backgrounds compared to threatening backgrounds (controlled for isolated background effects) and that this effect correlated with trait empathy in the sgACC. In addition, the left fusiform gyrus (FG) responds to the affective congruence between face and background scene. The results show that valence of the background modulates face processing and support the hypothesis that empathic processing in sgACC is inhibited when affective information is present in the background. In addition, the findings reveal a pattern of complex scene perception showing a gradient of functional specialization along the posterior-anterior axis: from sensitivity to the affective content of scenes (extrastriate body area: EBA and posterior PPA), over scene emotion-face emotion interaction (left FG) via category-scene interaction (anterior PPA) to scene-category-personality interaction (sgACC). © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. Face adaptation effects: Reviewing the impact of adapting information, time, and transfer

    Directory of Open Access Journals (Sweden)

    Tilo eStrobach

    2013-06-01

    Full Text Available The ability to adapt is essential to live and survive in an ever-changing environment such as the human ecosystem. Here we review the literature on adaptation effects of face stimuli to give an overview of existing findings in this area, highlight gaps in its research literature, initiate new directions in face adaptation research and help to design future adaptation studies. Furthermore, this review should lead to better understanding of the processing characteristics as well as the mental representations of face-relevant information. The review systematises studies at a behavioral level in respect of a framework which includes 3 dimensions representing the major characteristics of studies in this field of research. These dimensions comprise (1 the specificity of adapting face information, e.g. identity, gender or age aspects of the material to be adapted to, (2 aspects of timing (e.g., the sustainability of adaptation effects, and (3 transfer relations between face images presented during adaptation and adaptation tests (e.g., images of the same or different identities. The review concludes with options for how to combine findings across different dimensions to demonstrate the relevance of our framework for future studies.

  3. Face adaptation effects: reviewing the impact of adapting information, time, and transfer.

    Science.gov (United States)

    Strobach, Tilo; Carbon, Claus-Christian

    2013-01-01

    The ability to adapt is essential to live and survive in an ever-changing environment such as the human ecosystem. Here we review the literature on adaptation effects of face stimuli to give an overview of existing findings in this area, highlight gaps in its research literature, initiate new directions in face adaptation research, and help to design future adaptation studies. Furthermore, this review should lead to better understanding of the processing characteristics as well as the mental representations of face-relevant information. The review systematizes studies at a behavioral level in respect of a framework which includes three dimensions representing the major characteristics of studies in this field of research. These dimensions comprise (1) the specificity of adapting face information, e.g., identity, gender, or age aspects of the material to be adapted to (2) aspects of timing (e.g., the sustainability of adaptation effects) and (3) transfer relations between face images presented during adaptation and adaptation tests (e.g., images of the same or different identities). The review concludes with options for how to combine findings across different dimensions to demonstrate the relevance of our framework for future studies.

  4. A Survey on Face Detection and Recognition Techniques in Different Application Domain

    Directory of Open Access Journals (Sweden)

    Subrat Kumar Rath

    2014-08-01

    Full Text Available In recent technology the popularity and demand of image processing is increasing due to its immense number of application in various fields. Most of these are related to biometric science like face recognitions, fingerprint recognition, iris scan, and speech recognition. Among them face detection is a very powerful tool for video surveillance, human computer interface, face recognition, and image database management. There are a different number of works on this subject. Face recognition is a rapidly evolving technology, which has been widely used in forensics such as criminal identification, secured access, and prison security. In this paper we had gone through different survey and technical papers of this field and list out the different techniques like Linear discriminant analysis, Viola and Jones classification and adaboost learning curvature analysis and discuss about their advantages and disadvantages also describe some of the detection and recognition algorithms, mention some application domain along with different challenges in this field. . We had proposed a classification of detection techniques and discuss all the recognition methods also.

  5. Subject independent facial expression recognition with robust face detection using a convolutional neural network.

    Science.gov (United States)

    Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

    2003-01-01

    Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

  6. DEWA: A Multiaspect Approach for Multiple Face Detection in Complex Scene Digital Image

    Directory of Open Access Journals (Sweden)

    Setiawan Hadi

    2013-09-01

    Full Text Available A new approach for detecting faces in a digital image with unconstrained background has been developed. The approach is composed of three phases: segmentation phase, filtering phase and localization phase. In the segmentation phase, we utilized both training and non-training methods, which are implemented in user selectable color space. In the filtering phase, Minkowski addition-based objects removal has been used for image cleaning. In the last phase, an image processing method and a data mining method are employed for grouping and localizing objects, combined with geometric-based image analysis. Several experiments have been conducted using our special face database that consists of simple objects and complex objects. The experiment results demonstrated that the detection accuracy is around 90% and the detection speed is less than 1 second in average.

  7. DEWA: A Multiaspect Approach for Multiple Face Detection in Complex Scene Digital Image

    Directory of Open Access Journals (Sweden)

    Setiawan Hadi

    2007-05-01

    Full Text Available A new approach for detecting faces in a digital image with unconstrained background has been developed. The approach is composed of three phases: segmentation phase, filtering phase and localization phase. In the segmentation phase, we utilized both training and non-training methods, which are implemented in user selectable color space. In the filtering phase, Minkowski addition-based objects removal has been used for image cleaning. In the last phase, an image processing method and a data mining method are employed for grouping and localizing objects, combined with geometric-based image analysis. Several experiments have been conducted using our special face database that consists of simple objects and complex objects. The experiment results demonstrated that the detection accuracy is around 90% and the detection speed is less than 1 second in average.

  8. Detection technology and application of electromagnetic method for hidden danger of water gushing at coal face

    Energy Technology Data Exchange (ETDEWEB)

    Xian-xin Shi; Shu Yan; Ming-sheng Chen; Jun-mei Fu [China Coal Research Institute, Xi' an (China). Xi' an Research Institute

    2009-06-15

    The principles, methods, technologies and application effects of several electromagnetic methods for the detection of the hidden danger of water gushing at the coal face were introduced. Also, emphasis was laid on expounding the methods, principles and effects of down-hole detections by electric transmission tomography and transient electromagnetic method. The potential of point power supplied in the underground homogeneous semi-space, as well as the response to a low-resistivity abnormal body in the homogeneous semi-space, was simulated by adopting 3-D finite element method to interpret the basic theory of the electric transmission tomography. The results of actual measurement show that the mine electromagnetic method is sensitive to water-bearing low-resistivity bodies and can play a unique role in detecting the hidden danger of water gushing at the coal face. 9 refs., 9 figs.

  9. Detection technology and application of electromagnetic method for hidden danger of water gushing at coal face

    Institute of Scientific and Technical Information of China (English)

    SHI Xian-xin; YAN Shu; CHEN Ming-sheng; FU Jun-mei

    2009-01-01

    The principles, methods, technologies and application effects of several elec-tromagnetic methods for the detection of the hidden danger of water gushing at the coal face were introduced. Also, emphasis was laid on expounding the methods, principles and effects of down-hole detections by electric transmission tomography and transient elec-tromagnetic method. The potential of point power supplied in the underground homoge-neous semi-space, as well as the response to a low-resistivity abnormal body in the ho-mogeneous semi-space, was simulated by adopting 3-D finite element method to interpret the basic theory of the electric transmission tomography. The results of actual measure-ment show that the mine electromagnetic method is sensitive to water-bearing low-resistivity bodies and can play a unique role in detecting the hidden danger of water gushing at the coal face.

  10. Foveation: an alternative method to simultaneously preserve privacy and information in face images

    Science.gov (United States)

    Alonso, Víctor E.; Enríquez-Caldera, Rogerio; Sucar, Luis Enrique

    2017-03-01

    This paper presents a real-time foveation technique proposed as an alternative method for image obfuscation while simultaneously preserving privacy in face deidentification. Relevance of the proposed technique is discussed through a comparative study of the most common distortions methods in face images and an assessment on performance and effectiveness of privacy protection. All the different techniques presented here are evaluated when they go through a face recognition software. Evaluating the data utility preservation was carried out under gender and facial expression classification. Results on quantifying the tradeoff between privacy protection and image information preservation at different obfuscation levels are presented. Comparative results using the facial expression subset of the FERET database show that the technique achieves a good tradeoff between privacy and awareness with 30% of recognition rate and a classification accuracy as high as 88% obtained from the common figures of merit using the privacy-awareness map.

  11. Improved IBD detection using incomplete haplotype information

    Directory of Open Access Journals (Sweden)

    Pollak Martin R

    2010-06-01

    Full Text Available Abstract Background The availability of high density genetic maps and genotyping platforms has transformed human genetic studies. The use of these platforms has enabled population-based genome-wide association studies. However, in inheritance-based studies, current methods do not take full advantage of the information present in such genotyping analyses. Results In this paper we describe an improved method for identifying genetic regions shared identical-by-descent (IBD from recent common ancestors. This method improves existing methods by taking advantage of phase information even if it is less than fully accurate or missing. We present an analysis of how using phase information increases the accuracy of IBD detection compared to using only genotype information. Conclusions Our algorithm should have utility in a wide range of genetic studies that rely on identification of shared genetic material in large families or small populations.

  12. Enhanced retinal modeling for face recognition and facial feature point detection under complex illumination conditions

    Science.gov (United States)

    Cheng, Yong; Li, Zuoyong; Jiao, Liangbao; Lu, Hong; Cao, Xuehong

    2016-07-01

    We improved classic retinal modeling to alleviate the adverse effect of complex illumination on face recognition and extracted robust image features. Our improvements on classic retinal modeling included three aspects. First, a combined filtering scheme was applied to simulate functions of horizontal and amacrine cells for accurate local illumination estimation. Second, we developed an optimal threshold method for illumination classification. Finally, we proposed an adaptive factor acquisition model based on the arctangent function. Experimental results on the combined Yale B; the Carnegie Mellon University poses, illumination, and expression; and the Labeled Face Parts in the Wild databases show that the proposed method can effectively alleviate illumination difference of images under complex illumination conditions, which is helpful for improving the accuracy of face recognition and that of facial feature point detection.

  13. Implementation of Robot Platform in Face Detection and Tracking Based on a New Authentication Scheme

    Directory of Open Access Journals (Sweden)

    Young-Long Chen

    2014-01-01

    Full Text Available This study proposes a method for using stereo vision and face recogonition. The method differs from the feedback detection method used in sensors in general. The method disregards unimportant environmental changes and improves the overall performance of the recognition and tracking functions. Dual-CCD cameras on the visual system are used to capture images of faces. Through image preprocessing, determination of the moving target, and the position of the target center, the image is matched with the sample image to allow the robot to recognize and track stereo objects visually. The robot can recognize and track faces. And, the system also sends the images to a remote computer by wireless. A scheme is proposed to enhance the authentication messages by hash function in wireless communications. Since the proposed scheme provides an encryption function, it improves the authentication for wireless communications.

  14. Neural processing of high and low spatial frequency information in faces changes across development: qualitative changes in face processing during adolescence.

    Science.gov (United States)

    Peters, Judith C; Vlamings, Petra; Kemner, Chantal

    2013-05-01

    Face perception in adults depends on skilled processing of interattribute distances ('configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying immaturity to use facial information in low spatial frequency (SF) ranges, which capture the coarse information needed for configural processing. We hypothesized that during adolescence a shift from use of high to low SF information takes place. Therefore, we studied the influence of SF content on neural face processing in groups of children (9-10 years), adolescents (14-15 years) and young adults (21-29 years) by measuring event-related potentials (ERPs) to upright and inverted faces which varied in SF content. Results revealed that children show a neural FIE in early processing stages (i.e. P1; generated in early visual areas), suggesting a superficial, global facial analysis. In contrast, ERPs of adults revealed an FIE at later processing stages (i.e. N170; generated in face-selective, higher visual areas). Interestingly, adolescents showed FIEs in both processing stages, suggesting a hybrid developmental stage. Furthermore, adolescents and adults showed FIEs for stimuli containing low SF information, whereas such effects were driven by both low and high SF information in children. These results indicate that face processing has a protracted maturational course into adolescence, and is dependent on changes in SF processing. During adolescence, sensitivity to configural cues is developed, which aids the fast and holistic processing that is so special for faces.

  15. 基于HCbCr的人脸检测方法%DETECTING HUMAN FACE BASED ON HCBCR

    Institute of Scientific and Technical Information of China (English)

    赵怀勋; 徐锋

    2011-01-01

    在对HSV和YCbCr子空间分析的基础上,提出了HCbCr肤色模型.通过数学形态学处理和连通性分析,实现人脸检测.实验将提出的方法与其它几种基于肤色的人脸检测方法进行比较,验证了基于HCbCr的人脸检测方法对于光照、表情等的鲁棒性高,具有较高的检测成功率.%An RCbCr complexion model is proposed based on the analysis of subspaces of HSV and YCbCr. By mathematical morphology processing and connectivity anaysis, the human face detection is achieved. We compare the presented method with other complexion-based face detection methods in experiment, and validate the presented HCbCr-based human face detection method has high robustness on light and facial expression, and has higher detection success rate as well.

  16. Design of an Active Multispectral SWIR Camera System for Skin Detection and Face Verification

    Directory of Open Access Journals (Sweden)

    Holger Steiner

    2016-01-01

    Full Text Available Biometric face recognition is becoming more frequently used in different application scenarios. However, spoofing attacks with facial disguises are still a serious problem for state of the art face recognition algorithms. This work proposes an approach to face verification based on spectral signatures of material surfaces in the short wave infrared (SWIR range. They allow distinguishing authentic human skin reliably from other materials, independent of the skin type. We present the design of an active SWIR imaging system that acquires four-band multispectral image stacks in real-time. The system uses pulsed small band illumination, which allows for fast image acquisition and high spectral resolution and renders it widely independent of ambient light. After extracting the spectral signatures from the acquired images, detected faces can be verified or rejected by classifying the material as “skin” or “no-skin.” The approach is extensively evaluated with respect to both acquisition and classification performance. In addition, we present a database containing RGB and multispectral SWIR face images, as well as spectrometer measurements of a variety of subjects, which is used to evaluate our approach and will be made available to the research community by the time this work is published.

  17. Real-time camera-based face detection using a modified LAMSTAR neural network system

    Science.gov (United States)

    Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

    2003-03-01

    This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

  18. Real-Time Multi-View Face Detection and Pose Estimation Based on Cost-Sensitive AdaBoost

    Institute of Scientific and Technical Information of China (English)

    MA Yong; DING Xiaoqing

    2005-01-01

    Locating multi-view faces in images with a complex background remains a challenging problem. In this paper, an integrated method for real-time multi-view face detection and pose estimation is presented. A simple-to-complex and coarse-to-fine view-based detector architecture has been designed to detect multi-view faces and estimate their poses efficiently. Both the pose estimators and the view-based face/nonface detectors are trained by a cost-sensitive AdaBoost algorithm to improve the generalization ability. Experimental results show that the proposed multi-view face detector, which can be constructed easily, gives more robust face detection and pose estimation and has a faster real-time detection speed compared with other conventional methods.

  19. Facing the differences between Facebook and OpenCV : A facial detection comparison between Open Library Computer Vision and Facebook

    OpenAIRE

    Blomgren, Staffan; Hertz, Marcus

    2015-01-01

    Face detection is used in many different areas and with this thesis we aim to show the difference between Facebooks face detection soft-ware compared with an open source version from OpenCV. By using the simplest implementation of OpenCV we want to find out if it is viable for use in personal applications and be of help for others wanting to implement face detection. The dataset was meticulously checked to find the exact number of faces in each image so that the optimal result is given. The c...

  20. Early detection of tooth wear by en-face optical coherence tomography

    Science.gov (United States)

    Mărcăuteanu, Corina; Negrutiu, Meda; Sinescu, Cosmin; Demjan, Eniko; Hughes, Mike; Bradu, Adrian; Dobre, George; Podoleanu, Adrian G.

    2009-02-01

    Excessive dental wear (pathological attrition and/or abfractions) is a frequent complication in bruxing patients. The parafunction causes heavy occlusal loads. The aim of this study is the early detection and monitoring of occlusal overload in bruxing patients. En-face optical coherence tomography was used for investigating and imaging of several extracted tooth, with a normal morphology, derived from patients with active bruxism and from subjects without parafunction. We found a characteristic pattern of enamel cracks in patients with first degree bruxism and with a normal tooth morphology. We conclude that the en-face optical coherence tomography is a promising non-invasive alternative technique for the early detection of occlusal overload, before it becomes clinically evident as tooth wear.

  1. 一种结合肤色及类人脸特征的人脸检测%Face detection combining skin and face-like feature

    Institute of Scientific and Technical Information of China (English)

    陈章乐; 蔡茂国; 刘凡秀

    2013-01-01

    Facial feature extraction is the key process of the face detection. Effective features make the face detection more exactitude. Although Haar-Like feature is simple and computed rapidly by integral image, as a rectangle feature, the only orientations available are vertical, horizontal and diagonal. This paper presents a face-like feature that expresses the face gray distribution model, which describes the facial feature more effective. The face detection algorithm of this paper, skin segmentation is done by using BP neura! Network to train the skin region. Face detection is done by the AdaBoost algorithm with the face-like feature. Experimental results show that this algorithm can improve the detection rate.%人脸特征提取是人脸检测的关键环节,有效的人脸特征将使得人脸检测更精确.Haar-Like特征作为一种矩形特征,虽然简单、计算迅速,但只能描述特定方向的图形结构.提出的类人脸特征是一种反映人脸灰度分布模型的矩形特征,更加有效地描述了人脸的特征.所提出的人脸检测算法,应用BP神经网络算法训练肤色区域,进行肤色分割.应用类人脸特征的AdaBoost算法进行人脸检测.实验结果表明,该算法可以提高人脸检测的检测率.

  2. Real-time Face Detection and Tracking Using Haar Classifier on SoC

    Directory of Open Access Journals (Sweden)

    Rajashree Tripathy

    2014-03-01

    Full Text Available In this paper we intend to Implement a real time Face detection and tracking the head poses position from high definition video using Haar Classifier through Raspberry Pi BCM2835 CPU processor which is a combination of SoC with GPU based Architecture. OV5647 CMOS Image sensor with 5-megapixel used for obtaining high definition video H.264 video data via GPU’s hardware video decoder to improve the playback of H.264 Video data supporting from 1080p at 30fps with complete user control over formatting and output data transfer also supporting with 720p/60HD video in full field of View(FOV. SimpleCV and OpenCV libraries are used for face detection and tracking the head poses position. The experimental result computed by using computer vision SimpleCV and OpenCV framework libraries along with above mentioned hardware results were obtained through of 30 fps under 1080p resolutions for higher accuracy and speediness for face detection and tracking the head poses position.

  3. Sentence Level Information Patterns for Novelty Detection

    Science.gov (United States)

    2006-07-01

    Information Patterns for Novelty Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER...technology transfer arm, has sold the worldwide marketing rights to the drug Daca in return for cash payments and royalties should the drug be marketed...34> Stockbroker Lehman Brothers estimates that it may eventually generate Dollars 250m in sales.</s> <s docid="FT943-9461" num=൓"> Daca is still in the early

  4. Rotation Invariant Face Detection Using Wavelet, PCA and Radial Basis Function Networks

    CERN Document Server

    Kamruzzaman, S M; Islam, Md Saiful; Haque, Md Emdadul; Alam, Mohammad Shamsul

    2010-01-01

    This paper introduces a novel method for human face detection with its orientation by using wavelet, principle component analysis (PCA) and redial basis networks. The input image is analyzed by two-dimensional wavelet and a two-dimensional stationary wavelet. The common goals concern are the image clearance and simplification, which are parts of de-noising or compression. We applied an effective procedure to reduce the dimension of the input vectors using PCA. Radial Basis Function (RBF) neural network is then used as a function approximation network to detect where either the input image is contained a face or not and if there is a face exists then tell about its orientation. We will show how RBF can perform well then back-propagation algorithm and give some solution for better regularization of the RBF (GRNN) network. Compared with traditional RBF networks, the proposed network demonstrates better capability of approximation to underlying functions, faster learning speed, better size of network, and high ro...

  5. Co-Occurrence of Local Binary Patterns Features for Frontal Face Detection in Surveillance Applications

    Directory of Open Access Journals (Sweden)

    Louis Wael

    2011-01-01

    Full Text Available Face detection in video sequence is becoming popular in surveillance applications. The tradeoff between obtaining discriminative features to achieve accurate detection versus computational overhead of extracting these features, which affects the classification speed, is a persistent problem. This paper proposes to use multiple instances of rotational Local Binary Patterns (LBP of pixels as features instead of using the histogram bins of the LBP of pixels. The multiple features are selected using the sequential forward selection algorithm we called Co-occurrence of LBP (CoLBP. CoLBP feature extraction is computationally efficient and produces a high-performance rate. CoLBP features are used to implement a frontal face detector applied on a 2D low-resolution surveillance sequence. Experiments show that the CoLBP face features outperform state-of-the-art Haar-like features and various other LBP features extensions. Also, the CoLBP features can tolerate a wide range of illumination and blurring changes.

  6. Design of a Real-Time Face Detection Parallel Architecture Using High-Level Synthesis

    Directory of Open Access Journals (Sweden)

    Yang Fan

    2008-01-01

    Full Text Available Abstract We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE, by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We then build a parallel architecture composed of a PE ring and a FIFO memory, which constitutes a generic architecture capable of processing images of different sizes. A ring of 25 PEs running at 80 MHz is able to process 127 QVGA images per second or 35 VGA images per second.

  7. Design of a Real-Time Face Detection Parallel Architecture Using High-Level Synthesis

    Directory of Open Access Journals (Sweden)

    2009-02-01

    Full Text Available We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE, by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We then build a parallel architecture composed of a PE ring and a FIFO memory, which constitutes a generic architecture capable of processing images of different sizes. A ring of 25 PEs running at 80 MHz is able to process 127 QVGA images per second or 35 VGA images per second.

  8. Face detection in thermal imagery using an Open Source Computer Vision library

    Science.gov (United States)

    Sumriddetchkajorn, Sarun; Somboonkaew, Armote

    2009-05-01

    This paper studies the use of a combination of Haar-like features and a cascade of boosted tree classifiers embedded in a widely used OpenCV for face detection in thermal images. With 2013 positive and 2020 negative 320×240-pixel thermal images for 20 training stages on three window sizes of 20×20, 24×24, and 30×30 pixels, our experiment shows that these three windows offer similar hit and false alarm rates at the end of the training section. Larger windows also spend much more time to train. During our testing, the 30×30-pixel window provides measured best hit and false rejection/acceptation rates of 93.4% and 6.6%, respectively, with a measured slowest detection speed of 19.6 ms. A 5-ms improvement in the measured detection speed with a slightly lower hit rate of 92.1% is accomplished by using the 24×24-pixel window. These results verify that the combination of Haar-like features and a cascade of boosted tree classifiers is a promising technique for face detection application in thermal images.

  9. Separable effects of inversion and contrast-reversal on face detection thresholds and response functions: a sweep VEP study.

    Science.gov (United States)

    Liu-Shuang, Joan; Ales, Justin; Rossion, Bruno; Norcia, Anthony M

    2015-02-10

    The human brain rapidly detects faces in the visual environment. We recently presented a sweep visual evoked potential approach to objectively define face detection thresholds as well as suprathreshold response functions (Ales, Farzin, Rossion, & Norcia, 2012). Here we determined these parameters are affected by orientation (upright vs. inverted) and contrast polarity (positive vs. negative), two manipulations that disproportionately disrupt the perception of faces relative to other object categories. Face stimuli parametrically increased in visibility through phase-descrambling while alternating with scrambled images at a fixed presentation rate of 3 Hz (6 images/s). The power spectrum and mean luminance of all stimuli were equalized. As a face gradually emerged during a stimulation sequence, EEG responses at 3 Hz appeared at ≈35% phase coherence over right occipito-temporal channels, replicating previous observations. With inversion and contrast-reversal, the 3-Hz amplitude decreased by ≈20%-50% and the face detection threshold increased by ≈30%-60% coherence. Furthermore, while the 3-Hz response emerged abruptly and saturated quickly for normal faces, suggesting a categorical neural response, the response profile for inverted and negative polarity faces was shallower and more linear, indicating gradual and continuously increasing activation of the underlying neural population. These findings demonstrate that inversion and contrast-reversal increase the threshold and modulate the suprathreshold response function of face detection.

  10. Shot detection combining Bayesian and structural information

    Science.gov (United States)

    Han, Seung H.; Kweon, In-So

    2000-12-01

    There are a number of shots in a video, each of which has boundary types, such as cut, fade, dissolve and wipe. Many previous approaches can find the cut boundary without difficulty. However, most of them often produce false alarms for the videos with large motions of camera and objects. We propose a shot boundary detection method combining Bayesian and structural information. In the Bayesian approach, a probability distribution function models each transition type, e.g., normal, abrupt, gradual transition, and also models shot length. But inseparability between those distributions causes unwanted results and degrades the precision. In this paper, we demonstrate that the shape of the filtered frame difference, called the structural information, provides an important cue to distinguish fade and dissolve effects form cut effects and gradual changes caused by motion of camera and objects. The proposed method has been tested for a few golf video segments and shown good performances in detecting fade and dissolve effects as well as cut.

  11. Split-Second Trustworthiness Detection From Faces in an Economic Game.

    Science.gov (United States)

    De Neys, Wim; Hopfensitz, Astrid; Bonnefon, Jean-François

    2017-07-01

    Economic interactions often imply to gauge the trustworthiness of others. Recent studies showed that when making trust decisions in economic games, people have some accuracy in detecting trustworthiness from the facial features of unknown partners. Here we provide evidence that this face-based trustworthiness detection is a fast and intuitive process by testing its performance at split-second levels of exposure. Participants played a Trust game, in which they made decisions whether to trust another player based on their picture. In two studies, we manipulated the exposure time of the picture. We observed that trustworthiness detection remained better than chance for exposure times as short as 100 ms, although it disappeared with an exposure time of 33 ms. We discuss implications for ongoing debates on the use of facial inferences for social and economic decisions.

  12. Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination

    CERN Document Server

    Godil, Afzal; Grother, Patrick

    2011-01-01

    In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information. The 3D surface and color map data are from the CAESAR anthropometric database. We find that the recognition performance is not very different between 3D surface and color map information using a principal component analysis algorithm. We also discuss the different techniques for the combination of the 3D surface and color map information for multi-modal recognition by using different fusion approaches and show that there is significant improvement in results. The effectiveness of various techniques is compared and evaluated on a dataset with 200 subjects in two different positions.

  13. The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

    Directory of Open Access Journals (Sweden)

    Xiaohui Li

    2016-01-01

    Full Text Available Monitoring the contact state of seal end faces would help the early warning of the seal failure. In the acoustic emission (AE detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. To solve these problems and achieve higher detection rates, a new approach based on genetic particle filter with autoregression (AR-GPF and hypersphere support vector machine (HSSVM is presented. First, AR model is used to build the dynamic state space (DSS of the AE signal, and GPF is used for signal filtering. Then, multiple features are extracted, and a classification model based on HSSVM is constructed for state recognition. In this approach, AR-GPF is an excellent time-domain method for noise reduction, and HSSVM has advantage on those dispersed features. Finally experimental data shows that the proposed method can effectively detect the contact state of the seal end faces and has higher accuracy rates than some other existing methods.

  14. Detection of orange juice frauds using front-face fluorescence spectroscopy and Independent Components Analysis.

    Science.gov (United States)

    Ammari, Faten; Redjdal, Lamia; Rutledge, Douglas N

    2015-02-01

    The aim of this study was to find simple objective analytical methods to assess the adulteration of orange juice by grapefruit juice. The adulterations by addition of grapefruit juice were studied by 3D-front-face fluorescence spectroscopy followed by Independent Components Analysis (ICA) and by classical methods such as free radical scavenging activity and total flavonoid content. The results of this study clearly indicate that frauds by adding grapefruit juice to orange juice can be detected at percentages as low as 1%.

  15. Real-time Face Detection and Tracking Using Haar Classifier on SoC

    OpenAIRE

    Rajashree Tripathy; R N Daschoudhury

    2014-01-01

    In this paper we intend to Implement a real time Face detection and tracking the head poses position from high definition video using Haar Classifier through Raspberry Pi BCM2835 CPU processor which is a combination of SoC with GPU based Architecture. OV5647 CMOS Image sensor with 5-megapixel used for obtaining high definition video H.264 video data via GPU’s hardware video decoder to improve the playback of H.264 Video data supporting from 1080p at 30fps with complete user control over fo...

  16. Non-rigid, but not rigid, motion interferes with the processing of structural face information in developmental prosopagnosia.

    Science.gov (United States)

    Maguinness, Corrina; Newell, Fiona N

    2015-04-01

    There is growing evidence to suggest that facial motion is an important cue for face recognition. However, it is poorly understood whether motion is integrated with facial form information or whether it provides an independent cue to identity. To provide further insight into this issue, we compared the effect of motion on face perception in two developmental prosopagnosics and age-matched controls. Participants first learned faces presented dynamically (video), or in a sequence of static images, in which rigid (viewpoint) or non-rigid (expression) changes occurred. Immediately following learning, participants were required to match a static face image to the learned face. Test face images varied by viewpoint (Experiment 1) or expression (Experiment 2) and were learned or novel face images. We found similar performance across prosopagnosics and controls in matching facial identity across changes in viewpoint when the learned face was shown moving in a rigid manner. However, non-rigid motion interfered with face matching across changes in expression in both individuals with prosopagnosia compared to the performance of control participants. In contrast, non-rigid motion did not differentially affect the matching of facial expressions across changes in identity for either prosopagnosics (Experiment 3). Our results suggest that whilst the processing of rigid motion information of a face may be preserved in developmental prosopagnosia, non-rigid motion can specifically interfere with the representation of structural face information. Taken together, these results suggest that both form and motion cues are important in face perception and that these cues are likely integrated in the representation of facial identity.

  17. Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

    Science.gov (United States)

    Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

    2014-11-01

    A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

  18. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Iwano Koji

    2007-01-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  19. Audio-Visual Speech Recognition Using Lip Information Extracted from Side-Face Images

    Directory of Open Access Journals (Sweden)

    Koji Iwano

    2007-03-01

    Full Text Available This paper proposes an audio-visual speech recognition method using lip information extracted from side-face images as an attempt to increase noise robustness in mobile environments. Our proposed method assumes that lip images can be captured using a small camera installed in a handset. Two different kinds of lip features, lip-contour geometric features and lip-motion velocity features, are used individually or jointly, in combination with audio features. Phoneme HMMs modeling the audio and visual features are built based on the multistream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions. These visual features were confirmed to be effective even when the audio HMM was adapted to noise by the MLLR method.

  20. Improved cyberbullying detection using gender information

    NARCIS (Netherlands)

    Dadvar, M.; de Jong, F.M.G.; Ordelman, R.; Trieschnigg, D.

    2012-01-01

    As a result of the invention of social networks, friendships, relationships and social communication are all undergoing changes and new definitions seem to be applicable. One may have hundreds of ‘friends’ without even seeing their faces. Meanwhile, alongside this transition there is increasing evid

  1. Improved cyberbullying detection using gender information

    NARCIS (Netherlands)

    Dadvar, M.; de Jong, Franciska M.G.; Ordelman, Roeland J.F.; Trieschnigg, Rudolf Berend

    2012-01-01

    As a result of the invention of social networks, friendships, relationships and social communication are all undergoing changes and new definitions seem to be applicable. One may have hundreds of ‘friends’ without even seeing their faces. Meanwhile, alongside this transition there is increasing evid

  2. Improved cyberbullying detection using gender information

    NARCIS (Netherlands)

    Dadvar, M.; de Jong, Franciska M.G.; Ordelman, Roeland J.F.; Trieschnigg, Rudolf Berend

    2012-01-01

    As a result of the invention of social networks, friendships, relationships and social communication are all undergoing changes and new definitions seem to be applicable. One may have hundreds of ‘friends’ without even seeing their faces. Meanwhile, alongside this transition there is increasing

  3. Automatic Brain Tumour Detection Using Symmetry Information

    Directory of Open Access Journals (Sweden)

    Mr.Mubarak Jamadar

    2015-07-01

    Full Text Available Image segmentation is used to separate an image into several “meaningful” parts. Image segmentation is identification of homogeneous regions in the image. Many algorithms have been elaborated for gray scale images. However, the problem of segmentation for color images, which convey much more information about objects in scenes, has received much less attention of scientific community. While several surveys of monochrome image segmentation techniques were published, similar surveys for color images did not emerge. Image segmentation is a process of pixel classification. An image is segmented into subsets by assigning individual pixels to classes. It is an important step towards pattern detection and recognition. Segmentation is one of the first steps in image analysis. It refers to the process of partitioning a digital image into multiple regions (sets of pixels. Each of the pixels in a region is similar with respect to some characteristic or computed property, such as color, intensity, or texture. The level of segmentation is decided by the particular characteristics of the problem being considered. Image segmentation could be further used for object matching between two images. An object of interest is specified in the first image by using the segmentation result of that image; then the specified object is matched in the second image by using the segmentation result of that image

  4. Mediamorphosis and misinformation in the infosphere: media, digital and information literacy face of changes in information consumption habits

    Directory of Open Access Journals (Sweden)

    Juan Ignacio AGUADED

    2015-04-01

    Full Text Available From a theoretical reflection, this work is evidence that the current communicational and digital ecosystem is endogenous and systemically misinformative, as it has gradually become an information overload and infoxicative scenario, traversed by a dynamic of mediamorphosis, in which traditional media are looking to compete for the preference of the audience facing the multiplicity of digital platforms in the way of their economic subsistence, usually spreading pseudo-contents with limbic great value, but lacking useful in the process of decision making. Consequently, this paper analyzes the above problems by reviewing various multidisciplinary academic contributions to later refer those from within the theories of media, digital and information literacy contribute recommendations and pragmatic schemes to cope with the situation. The work focuses on media-digital society in the context of media convergence and multiple screens, outlining the social changes that are currently embedded audiences. Obtained results showed the need to adapt an “infodiet” or media ecology from the user’s perspective, alternating moments of disconnection, without deserting the efforts that Educommunication and communication policy could contribute in social transformation, in order promote educational, cultural and informative content from the perspective of pluralism, citizen participation and pragmatic reconstruction towards public service media.

  5. Controlled fabrication of nanopores using a direct focused ion beam approach with back face particle detection.

    Science.gov (United States)

    Patterson, N; Adams, D P; Hodges, V C; Vasile, M J; Michael, J R; Kotula, P G

    2008-06-11

    We report a direct, ion drilling technique that enables the reproducible fabrication and placement of nanopores in membranes of different thickness. Using a 30 keV focused Ga ion beam column combined with an in situ, back face, multi-channelplate particle detector, nanopores are sputtered in Si(3)N(4) and W/Si(3)N(4) to have diameters as small as 12 nm. Transmission electron microscopy shows that focused ion beam-drilled holes are near-conical with the diameter decreasing from entry to exit side. By monitoring the detector signal during ion exposure, the drilled hole width can be minimized such that the exit-side diameter is smaller than the full width at half-maximum of the nominally Gaussian-shaped incident beam. Judicious choice of the beam defining aperture combined with back face particle detection allows for reproducible exit-side hole diameters between 18 and 100 nm. The nanopore direct drilling technique does not require potentially damaging broad area exposure to tailor hole sizes. Moreover, this technique successfully achieves breakthrough despite the effects of varying membrane thickness, redeposition, polycrystalline grain structure, and slight ion beam current fluctuations.

  6. An FPGA-based design of a modular approach for integral images in a real-time face detection system

    Science.gov (United States)

    Ngo, Hau T.; Rakvic, Ryan N.; Broussard, Randy P.; Ives, Robert W.

    2009-05-01

    The first step in a facial recognition system is to find and extract human faces in a static image or video frame. Most face detection methods are based on statistical models that can be trained and then used to classify faces. These methods are effective but the main drawback is speed because a massive number of sub-windows at different image scales are considered in the detection procedure. A robust face detection technique based on an encoded image known as an "integral image" has been proposed by Viola and Jones. The use of an integral image helps to reduce the number of operations to access a sub-image to a relatively small and fixed number. Additional speedup is achieved by incorporating a cascade of simple classifiers to quickly eliminate non-face sub-windows. Even with the reduced number of accesses to image data to extract features in Viola-Jones algorithm, the number of memory accesses is still too high to support realtime operations for high resolution images or video frames. The proposed hardware design in this research work employs a modular approach to represent the "integral image" for this memory-intensive application. An efficient memory manage strategy is also proposed to aggressively utilize embedded memory modules to reduce interaction with external memory chips. The proposed design is targeted for a low-cost FPGA prototype board for a cost-effective face detection/recognition system.

  7. Brain Responses Reveal That Infants' Face Discrimination Is Guided by Statistical Learning from Distributional Information

    Science.gov (United States)

    Altvater-Mackensen, Nicole; Jessen, Sarah; Grossmann, Tobias

    2017-01-01

    Infants' perception of faces becomes attuned to the environment during the first year of life. However, the mechanisms that underpin perceptual narrowing for faces are only poorly understood. Considering the developmental similarities seen in perceptual narrowing for faces and speech and the role that statistical learning has been shown to play…

  8. Zeolite thin film-coated spherical end-face fiber sensors for detection of trace organic vapors

    Science.gov (United States)

    Ning, Xiangping; Zhao, Chun Liu; Yang, Jingyi; Chan, Chi Chiu

    2016-04-01

    A novel zeolite thin film-coated spherical end face fiber sensor for detection of trace organic vapors was experimentally demonstrated. The spherical end-face was fabricated by electrical arc discharge on the end face of a standard single-mode fiber. The proposed sensor comprise of the fiber's spherical end-face covered with a layer of zeolite thin film. The zeolite film and spherical end face constituted an arc-shaped inline Fabry-Perot (F-P) cavity, which improves the interference performance. The trace chemical vapor concentration was measured by monitoring the shift of F-P interference wavelength which induced by the organic vapor molecular adsorption of the zeolite film. The proposed trace organic vapors sensor performed with the enhanced sensitivity 0.91 nm/ppm with the range from 0 to 70 ppm.

  9. Distinct representations of configural and part information across multiple face-selective regions of the human brain.

    Science.gov (United States)

    Golarai, Golijeh; Ghahremani, Dara G; Eberhardt, Jennifer L; Gabrieli, John D E

    2015-01-01

    Several regions of the human brain respond more strongly to faces than to other visual stimuli, such as regions in the amygdala (AMG), superior temporal sulcus (STS), and the fusiform face area (FFA). It is unclear if these brain regions are similar in representing the configuration or natural appearance of face parts. We used functional magnetic resonance imaging of healthy adults who viewed natural or schematic faces with internal parts that were either normally configured or randomly rearranged. Response amplitudes were reduced in the AMG and STS when subjects viewed stimuli whose configuration of parts were digitally rearranged, suggesting that these regions represent the 1st order configuration of face parts. In contrast, response amplitudes in the FFA showed little modulation whether face parts were rearranged or if the natural face parts were replaced with lines. Instead, FFA responses were reduced only when both configural and part information were reduced, revealing an interaction between these factors, suggesting distinct representation of 1st order face configuration and parts in the AMG and STS vs. the FFA.

  10. 基于肤色的人脸检测研究%Researh of Face Detection Based on Skin Color

    Institute of Scientific and Technical Information of China (English)

    王莹

    2012-01-01

    对于有背景的彩色图像,肤色是人体表面最显著的特征之一,所以肤色特征是人脸检测中一个重要的特征[1~2].肤色特征主要由肤色模型描述,检测方法可以分为颜色选择,肤色区域分割和人脸检测三个步骤.文章提出的肤色模型可以较好的适应光照变化,采用肤色分割的方法,可以快速检测不同大小,不同平面以及一定侧面旋转角度的人脸.对简单背景下的人脸检测的检测率达到95.65%,复杂背景下的人脸检测的检测率达到85.22%.%For color images with certain background, color of skin is the most important character of the body surface, so skin color is an important character in face detection. Skin character can be described by skin color model. The detection method can be divided into color selection, skin color segmentation and face detection. The skin color model was presented can well adapt to different light condition. Using the skin color based face detection, different sizes, different plane and a certain rotation angle of the face could be quickly detected. In the simple context picture, the face detection rate reach to 95. 65%, in the complex context picture, the face detection rate can reach to 85. 22%.

  11. Moving human full body and body parts detection, tracking, and applications on human activity estimation, walking pattern and face recognition

    Science.gov (United States)

    Chen, Hai-Wen; McGurr, Mike

    2016-05-01

    We have developed a new way for detection and tracking of human full-body and body-parts with color (intensity) patch morphological segmentation and adaptive thresholding for security surveillance cameras. An adaptive threshold scheme has been developed for dealing with body size changes, illumination condition changes, and cross camera parameter changes. Tests with the PETS 2009 and 2014 datasets show that we can obtain high probability of detection and low probability of false alarm for full-body. Test results indicate that our human full-body detection method can considerably outperform the current state-of-the-art methods in both detection performance and computational complexity. Furthermore, in this paper, we have developed several methods using color features for detection and tracking of human body-parts (arms, legs, torso, and head, etc.). For example, we have developed a human skin color sub-patch segmentation algorithm by first conducting a RGB to YIQ transformation and then applying a Subtractive I/Q image Fusion with morphological operations. With this method, we can reliably detect and track human skin color related body-parts such as face, neck, arms, and legs. Reliable body-parts (e.g. head) detection allows us to continuously track the individual person even in the case that multiple closely spaced persons are merged. Accordingly, we have developed a new algorithm to split a merged detection blob back to individual detections based on the detected head positions. Detected body-parts also allow us to extract important local constellation features of the body-parts positions and angles related to the full-body. These features are useful for human walking gait pattern recognition and human pose (e.g. standing or falling down) estimation for potential abnormal behavior and accidental event detection, as evidenced with our experimental tests. Furthermore, based on the reliable head (face) tacking, we have applied a super-resolution algorithm to enhance

  12. Effect of Affective Personality Information on Face Processing: Evidence from ERPs

    OpenAIRE

    Luo, Qiu L.; Wang, Han L.; Dzhelyova, Milena; Huang, Ping; Mo, Lei

    2016-01-01

    This study explored the extent to which there are the neural correlates of the affective personality influence on face processing using event-related potentials (ERPs). In the learning phase, participants viewed a target individual’s face (expression neutral or faint smile) paired with either negative, neutral or positive sentences describing previous typical behavior of the target. In the following EEG testing phase, participants completed gender judgments of the learned faces. Statistical a...

  13. An Information-Theoretic Measure for Face Recognition: Comparison with Structural Similarity

    OpenAIRE

    Asmhan Flieh Hassan; Zahir M. Hussain; Dong Cai-lin

    2014-01-01

    Automatic recognition of people faces is a challenging problem that has received significant attention from signal processing researchers in recent years. This is due to its several applications in different fields, including security and forensic analysis. Despite this attention, face recognition is still one among the most challenging problems. Up to this moment, there is no technique that provides a reliable solution to all situations. In this paper a novel technique for face recognition i...

  14. Face Detection Based on Adaboost and Clifford Algebra%基于Adaboost与Clifford代数的人脸检测

    Institute of Scientific and Technical Information of China (English)

    杨晋吉; 李荣兵

    2013-01-01

    In the conditions of complicated backgrounds and different illumination, as face detection based on Adaboost algorithm usually has higher false alarm rate, a new method based on the Adaboost algorithm and the Clifford vector product is proposed in this paper. Most of the non-face region is quickly excluded by the Adaboost classifier. The candidate region is verified basing on the face prior knowledge. If verification failure, according to Clifford vector product properties, searching for the region which has higher similarity with the region that need to be verified again, when their vector product is higher than threshold, this paper can judge that it is a face region. The comparison of this method with Viola-Jones method, experimental result shows that this method can detect face with high detection rate, suppresses the error detection rate, and is highly robust to face detection.%Adaboost算法在光照不均、背景复杂的条件下进行人脸检测时误检率较高。为解决该问题,提出一种基于Adaboost算法与Clifford代数矢量积性质的人脸检测方法。利用Adaboost算法初步定位人脸可能存在的区域,对该区域进行基于知识的校验,如果校验失败,根据Clifford矢量积性质,寻找与待验证区域相似度较高的人脸,当相似度大于阈值时,判断其为人脸。实验结果表明,与Viola-Jones方法相比,该方法在保持较高检测率的同时,降低了误检率,且鲁棒性较好。

  15. Gaussian Weak Classifiers Based on Haar-Like Features with Four Rectangles for Real-time Face Detection

    Science.gov (United States)

    Pavani, Sri-Kaushik; Delgado Gomez, David; Frangi, Alejandro F.

    This paper proposes Gaussian weak classifiers (GWCs) for use in real-time face detection systems. GWCs are based on Haar-like features (HFs) with four rectangles (HF4s), which constitute the majority of the HFs used to train a face detector. To label an image as face or clutter (non-face), GWC uses the responses of the two HF2s in a HF4 to compute a Mahalanobis distance which is later compared to a threshold to make decisions. For a fixed accuracy on the face class, GWCs can classify clutter images with more accuracy than the existing weak classifier types. Our experiments compare the accuracy and speed of the face detectors built with four different weak classifier types: GWCs, Viola & Jones’s, Rasolzadeh et al.’s and Mita et al.’s. On the standard MIT+CMU image database, the GWC-based face detector provided 40% less false positives and required 32% less time for the scanning process when compared to the detector that used Viola & Jones’s weak classifiers. When compared to detectors that used Rasolzadeh et al.’s and Mita et al.’s weak classifiers, the GWC-based detector produced 11% and 9% fewer false positives. Simultaneously, it required 37% and 42% less time for the scanning process.

  16. Newborns' Mooney-Face Perception

    Science.gov (United States)

    Leo, Irene; Simion, Francesca

    2009-01-01

    The aim of this study is to investigate whether newborns detect a face on the basis of a Gestalt representation based on first-order relational information (i.e., the basic arrangement of face features) by using Mooney stimuli. The incomplete 2-tone Mooney stimuli were used because they preclude focusing both on the local features (i.e., the fine…

  17. How affective information from faces and scenes interacts in the brain

    NARCIS (Netherlands)

    van den Stock, J.B.; Vandenbulcke, Mathieu; Sinke, C.B.A.; Goebel, Rainer; de Gelder, B.

    2014-01-01

    Facial expression perception can be influenced by the natural visual context in which the face is perceived. We performed an fMRI experiment presenting participants with fearful or neutral faces against threatening or neutral background scenes. Triangles and scrambled scenes served as control

  18. Handbook of Face Recognition

    CERN Document Server

    Li, Stan Z

    2011-01-01

    This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems

  19. Face feature processor on mobile service robot

    Science.gov (United States)

    Ahn, Ho Seok; Park, Myoung Soo; Na, Jin Hee; Choi, Jin Young

    2005-12-01

    In recent years, many mobile service robots have been developed. These robots are different from industrial robots. Service robots were confronted to unexpected changes in the human environment. So many capabilities were needed to service mobile robot, for example, the capability to recognize people's face and voice, the capability to understand people's conversation, and the capability to express the robot's thinking etc. This research considered face detection, face tracking and face recognition from continuous camera image. For face detection module, it used CBCH algorithm using openCV library from Intel Corporation. For face tracking module, it used the fuzzy controller to control the pan-tilt camera movement smoothly with face detection result. A PCA-FX, which adds class information to PCA, was used for face recognition module. These three procedures were called face feature processor, which were implemented on mobile service robot OMR to verify.

  20. Detecting novel metaphor using selectional preference information

    NARCIS (Netherlands)

    Haagsma, Hessel; Bjerva, Johannes

    2016-01-01

    Recent work on metaphor processing often employs selectional preference information. We present a comparison of different approaches to the modelling of selectional preferences, based on various ways of generalizing over corpus frequencies. We evaluate on the VU Amsterdam Metaphor corpus, a broad co

  1. Face verification for mobile personal devices

    NARCIS (Netherlands)

    Tao, Qian

    2009-01-01

    In this thesis, we presented a detailed study of the face verification problem on the mobile device, covering every component of the system. The study includes face detection, registration, normalization, and verification. Furthermore, the information fusion problem is studied to verify face sequenc

  2. Auditor Detected Misstatements and the Effect of Information Technology

    OpenAIRE

    Austen, Lizabeth A.; Eilifsen, Aasmund; Messier, William F.

    2004-01-01

    This paper presents information on the causes and detection of misstatements by auditors and the relationship of those misstatements with information technology (IT). The last major study of misstatements and IT used data that was gathered in 1988. In the intervening period, there have been significant changes in IT, possibly altering the error generation and detection process. Two research questions related to detected misstatements and the effect of IT are examined. The six largest public a...

  3. Visual scanning and recognition of Chinese, Caucasian, and racially ambiguous faces: contributions from bottom-up facial physiognomic information and top-down knowledge of racial categories.

    Science.gov (United States)

    Wang, Qiandong; Xiao, Naiqi G; Quinn, Paul C; Hu, Chao S; Qian, Miao; Fu, Genyue; Lee, Kang

    2015-02-01

    Recent studies have shown that participants use different eye movement strategies when scanning own- and other-race faces. However, it is unclear (1) whether this effect is related to face recognition performance, and (2) to what extent this effect is influenced by top-down or bottom-up facial information. In the present study, Chinese participants performed a face recognition task with Chinese, Caucasian, and racially ambiguous faces. For the racially ambiguous faces, we led participants to believe that they were viewing either own-race Chinese faces or other-race Caucasian faces. Results showed that (1) Chinese participants scanned the nose of the true Chinese faces more than that of the true Caucasian faces, whereas they scanned the eyes of the Caucasian faces more than those of the Chinese faces; (2) they scanned the eyes, nose, and mouth equally for the ambiguous faces in the Chinese condition compared with those in the Caucasian condition; (3) when recognizing the true Chinese target faces, but not the true target Caucasian faces, the greater the fixation proportion on the nose, the faster the participants correctly recognized these faces. The same was true when racially ambiguous face stimuli were thought to be Chinese faces. These results provide the first evidence to show that (1) visual scanning patterns of faces are related to own-race face recognition response time, and (2) it is bottom-up facial physiognomic information that mainly contributes to face scanning. However, top-down knowledge of racial categories can influence the relationship between face scanning patterns and recognition response time.

  4. Using the WMS-III faces subtest to detect malingered memory impairment.

    Science.gov (United States)

    Glassmire, David M; Bierley, Rex A; Wisniewski, Amy M; Greene, Roger L; Kennedy, Jan E; Date, Elaine

    2003-06-01

    The current study evaluated the utility of the WMS-III Faces I subtest (Faces) for the assessment of malingering. Thirty nonlitigating traumatic brain injury patients and 30 control participants were administered Faces under standard administration and instructed malingering conditions. Although the two groups obtained similar scores when taking the test under standard instructions, both groups produced significantly lower performances when instructed to malinger, indicating that Faces is sensitive to malingering, but less sensitive to traumatic brain injury. The total raw score provided stronger classification accuracy than an empirically weighted combination of the five easiest items (i.e., floor effect items). A raw score cutoff of 31 yielded the maximum classification accuracy with 93.3% sensitivity and 80.0% specificity.

  5. Face Detection Based on 3×3 Block Gradient Image Partition and Face Geometric Model%基于3×3块梯度图像划分和人脸几何模型的人脸检测

    Institute of Scientific and Technical Information of China (English)

    盛光磊; 张腾; 裴铮

    2013-01-01

      提出一个人脸检测算法,该算法使用3×3块划分的梯度图像和几何人脸模型来进行人脸检测.3×3块划分用来初步检测特定区域中是否有人脸,接下来利用几何人脸模型把人脸检测出来.实验结果表明所提出的人脸检测算法检测结果比较好,并且对于光照并不敏感.%This paper presents a face detection algorithm, the algorithm uses a gradient image of 3 Í3 block partition and geometric human face model for face detection. 3 Í 3 block partition is used to and preliminary detect whether someone in the specific area of the face, followed by the use of geometric face model face detection. The experimental results show that the proposed face detection algorithms to detect better results,and is not sensitive to light.

  6. [A review on polarization information in the remote sensing detection].

    Science.gov (United States)

    Gong, Jie-Qiong; Zhan, Hai-Gang; Liu, Da-Zhao

    2010-04-01

    Polarization is one of the inherent characteristics. Because the surface of the target structure, internal structure, and the angle of incident light are different, the earth's surface and any target in atmosphere under optical interaction process will have their own characteristic nature of polarization. Polarimetric characteristics of radiation energy from the targets are used in polarization remote sensing detection as detective information. Polarization remote sensing detection can get the seven-dimensional information of targets in complicated backgrounds, detect well-resolved outline of targets and low-reflectance region of objectives, and resolve the problems of atmospheric detection and identification camouflage detection which the traditional remote sensing detection can not solve, having good foreground in applications. This paper introduces the development of polarization information in the remote sensing detection from the following four aspects. The rationale of polarization remote sensing detection is the base of polarization remote sensing detection, so it is firstly introduced. Secondly, the present researches on equipments that are used in polarization remote sensing detection are particularly and completely expatiated. Thirdly, the present exploration of theoretical simulation of polarization remote sensing detection is well detailed. Finally, the authors present the applications research home and abroad of the polarization remote sensing detection technique in the fields of remote sensing, atmospheric sounding, sea surface and underwater detection, biology and medical diagnosis, astronomical observation and military, summing up the current problems in polarization remote sensing detection. The development trend of polarization remote sensing detection technology in the future is pointed out in order to provide a reference for similar studies.

  7. Learning weighted sparse representation of encoded facial normal information for expression-robust 3D face recognition

    KAUST Repository

    Li, Huibin

    2011-10-01

    This paper proposes a novel approach for 3D face recognition by learning weighted sparse representation of encoded facial normal information. To comprehensively describe 3D facial surface, three components, in X, Y, and Z-plane respectively, of normal vector are encoded locally to their corresponding normal pattern histograms. They are finally fed to a sparse representation classifier enhanced by learning based spatial weights. Experimental results achieved on the FRGC v2.0 database prove that the proposed encoded normal information is much more discriminative than original normal information. Moreover, the patch based weights learned using the FRGC v1.0 and Bosphorus datasets also demonstrate the importance of each facial physical component for 3D face recognition. © 2011 IEEE.

  8. An Approach to Face Recognition of 2-D Images Using Eigen Faces and PCA

    Directory of Open Access Journals (Sweden)

    Annapurna Mishra

    2012-04-01

    Full Text Available Face detection is to find any face in a given image. Face recognition is a two-dimension problem used for detecting faces. The information contained in a face can be analysed automatically by this system like identity, gender, expression, age, race and pose. Normally face detection is done for a single image but it can also be extended for video stream. As the face images are normally upright, they can be described by a small set of 2-D characteristics views. Here the face images are projected to a feature space or face space to encode the variation between the known face images. The projected feature space or the face space can be defined as ‘eigenfaces’ and can be formed by eigenvectors of the face image set. The above process can be used to recognize a new face in unsupervised manner. This paper introduces an algorithm which is used for effective face recognition. It takes into consideration not only the face extraction but also the mathematical calculations which enable us to bring the image into a simple and technical form. It can also be implemented in real-time using data acquisition hardware and software interface with the face recognition systems. Face recognition can be applied to various domains including security systems, personal identification, image and film processing and human computer interaction.

  9. Neural processing of high and low spatial frequency information in faces changes across development : qualitative changes in face processing during adolescence

    NARCIS (Netherlands)

    Peters, Judith C.; Vlamings, Petra; Kemner, Chantal

    2013-01-01

    Face perception in adults depends on skilled processing of interattribute distances (configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying im

  10. Neural processing of high and low spatial frequency information in faces changes across development : qualitative changes in face processing during adolescence

    NARCIS (Netherlands)

    Peters, Judith C.; Vlamings, Petra; Kemner, Chantal

    2013-01-01

    Face perception in adults depends on skilled processing of interattribute distances (configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying im

  11. Filtering, control and fault detection with randomly occurring incomplete information

    CERN Document Server

    Dong, Hongli; Gao, Huijun

    2013-01-01

    This book investigates the filtering, control and fault detection problems for several classes of nonlinear systems with randomly occurring incomplete information. It proposes new concepts, including RVNs, ROMDs, ROMTCDs, and ROQEs. The incomplete information under consideration primarily includes missing measurements, time-delays, sensor and actuator saturations, quantization effects and time-varying nonlinearities. The first part of this book focuses on the filtering, control and fault detection problems for several classes of nonlinear stochastic discrete-time systems and

  12. Differential brain activation to angry faces by elite warfighters: neural processing evidence for enhanced threat detection.

    Directory of Open Access Journals (Sweden)

    Martin P Paulus

    Full Text Available BACKGROUND: Little is known about the neural basis of elite performers and their optimal performance in extreme environments. The purpose of this study was to examine brain processing differences between elite warfighters and comparison subjects in brain structures that are important for emotion processing and interoception. METHODOLOGY/PRINCIPAL FINDINGS: Navy Sea, Air, and Land Forces (SEALs while off duty (n = 11 were compared with n = 23 healthy male volunteers while performing a simple emotion face-processing task during functional magnetic resonance imaging. Irrespective of the target emotion, elite warfighters relative to comparison subjects showed relatively greater right-sided insula, but attenuated left-sided insula, activation. Navy SEALs showed selectively greater activation to angry target faces relative to fearful or happy target faces bilaterally in the insula. This was not accounted for by contrasting positive versus negative emotions. Finally, these individuals also showed slower response latencies to fearful and happy target faces than did comparison subjects. CONCLUSIONS/SIGNIFICANCE: These findings support the hypothesis that elite warfighters deploy greater processing resources toward potential threat-related facial expressions and reduced processing resources to non-threat-related facial expressions. Moreover, rather than expending more effort in general, elite warfighters show more focused neural and performance tuning. In other words, greater neural processing resources are directed toward threat stimuli and processing resources are conserved when facing a nonthreat stimulus situation.

  13. Detecting Early Signatures of Persuasion in Information Cascades

    Science.gov (United States)

    2014-01-01

    ADDRESS. Indiana University at Bloomington Trustees of Indiana University 509 E 3RD ST Bloomington, IN 47401 -3654 Detecting Early Signatures of Persuasion ...SMISC  Project:   DESPIC:  Detecting  Early  Signatures  of   Persuasion  in  Information  Cascades     Teams:   Indiana

  14. Surface Electromyographic Onset Detection Based On Statistics and Information Content

    Science.gov (United States)

    López, Natalia M.; Orosco, Eugenio; di Sciascio, Fernando

    2011-12-01

    The correct detection of the onset of muscular contraction is a diagnostic tool to neuromuscular diseases and an action trigger to control myoelectric devices. In this work, entropy and information content concepts were applied in algorithmic methods to automatic detection in surface electromyographic signals.

  15. 静态灰度图像中的人脸检测方法综述%Survey on Face Detection Methods in Gray-level Still Images

    Institute of Scientific and Technical Information of China (English)

    唐伟; 陈兆乾; 吴建鑫; 周志华

    2002-01-01

    In recent twenty years,the technique of face detection and face recognition,as one of the important research area of computer vision and image understanding,attracts more and more attenion.In general,face detection in graylevel still images is more difficualt than that in color images.Therefore this paper briefly surveys this raes and indicates some issues for exploration.

  16. Face Detection for Augmented Reality Application Using Boosting-based Techniques

    Directory of Open Access Journals (Sweden)

    Youssef Hbali

    2016-12-01

    Full Text Available Augmented reality has gained an increasing research interest over the few last years. Customers requirements have become more intense and more demanding, the need of the different industries to re-adapt their products and enhance them by recent advances in the computer vision and more intelligence has become a necessary. In this work we present a marker-less augmented reality application that can be used and expanded in the e-commerce industry. We take benefit of the well known boosting techniques to train and evaluate different face detectors using the multi-block local binary features. The work purpose is to select the more relevant training parameters in order to maximize the classification accuracy. Using the resulted face detector, the position of the face will serve as a marker in the proposed augmented reality.

  17. Multi-pose face detection based on color model and face feature%基于肤色模型与人脸特征的多姿态人脸检测

    Institute of Scientific and Technical Information of China (English)

    孙亚新; 战荫伟

    2011-01-01

    传统AdaBooat人脸检测算法使用正面人脸训练分类器,不能检测有任意偏转角度的多姿态人脸.本研究利用各种多姿态人脸中人眼结构变化比较小的性质,使用人眼训练AdaBoost算法的分类器,设计出一种快速的复杂场景下的多人多姿态人脸检测算法.先将图像映射到一种色彩空间,运用皮肤颜色分布特性检测皮肤区域;再运用AdaBoost算法从肤色区域检测出人眼区域;最后根据人眼在人脸中的位置计算出人脸的位置.实验结果表明:该算法对多姿态人脸有很好的检测效果.%Traditionally, AdaBoost based face detection algorithms use frontal faces to train classifiers, which cannot detect multi-pose faces with arbitrary rotations.Noticing that the eye structures vary less than face structures in multipose faces, eyes were used to train the classifier in AdaBoost algorithm, and present a fast algorithm to detect multipose faces in complex scenes.An image is first mapped to a YCrCb color space and the skin region is detected with the skin color distribution.The eye region is then detected from the skin region via the AdaBoost algorithm.The face is located according to the eye positions relative to faces.Experimental results show that this algorithm performs well for the detection of multi-pose faces.

  18. Head Pose Estimation on Top of Haar-Like Face Detection: A Study Using the Kinect Sensor

    Directory of Open Access Journals (Sweden)

    Anwar Saeed

    2015-08-01

    Full Text Available Head pose estimation is a crucial initial task for human face analysis, which is employed in several computer vision systems, such as: facial expression recognition, head gesture recognition, yawn detection, etc. In this work, we propose a frame-based approach to estimate the head pose on top of the Viola and Jones (VJ Haar-like face detector. Several appearance and depth-based feature types are employed for the pose estimation, where comparisons between them in terms of accuracy and speed are presented. It is clearly shown through this work that using the depth data, we improve the accuracy of the head pose estimation. Additionally, we can spot positive detections, faces in profile views detected by the frontal model, that are wrongly cropped due to background disturbances. We introduce a new depth-based feature descriptor that provides competitive estimation results with a lower computation time. Evaluation on a benchmark Kinect database shows that the histogram of oriented gradients and the developed depth-based features are more distinctive for the head pose estimation, where they compare favorably to the current state-of-the-art approaches. Using a concatenation of the aforementioned feature types, we achieved a head pose estimation with average errors not exceeding 5:1; 4:6; 4:2 for pitch, yaw and roll angles, respectively.

  19. Face recognition from a moving platform via sparse representation

    Science.gov (United States)

    Hsu, Ming Kai; Hsu, Charles; Lee, Ting N.; Szu, Harold

    2012-06-01

    A video-based surveillance system for passengers includes face detection, face tracking and face recognition. In general, the final recognition result of the video-based surveillance system is usually determined by the cumulative recognition results. Under this strategy, the correctness of face tracking plays an important role for the system recognition rate. For face tracking, the challenges of face tracking on a moving platform are that the space and time information used for conventional face tracking algorithms may be lost. Consequently, conventional face tracking algorithms can barely handle the face tracking on a moving platform. In this paper, we have verified the state-of-the-art technologies for face detection, face tracking and face recognition on a moving platform. In the mean time, we also proposed a new strategy for face tracking on a moving platform or face tracking under very low frame rate. The steps of the new strategy for face detection are: (1) classification the detected faces over a certain period instead of every frame (2) Tracking of each passenger is equivalent to reconstruct the time order of certain period for each passenger. If the cumulative recognition results are the only part needed for the surveillance system, step 2 can be skipped. In addition, if the additional information from the passengers is required, such as path tracking, lip read, gesture recognition, etc, time order reconstruction in step 2 can offer the information required.

  20. A Method of Image Symmetry Detection Based on Phase Information

    Institute of Scientific and Technical Information of China (English)

    WU Jun; YANG Zhaoxuan; FENG Dengchao

    2005-01-01

    Traditional methods for detecting symmetry in image suffer greatly from the contrast of image and noise, and they all require some preprocessing. This paper presents a new method of image symmetry detection. This method detects symmetry with phase information utilizing logGabor wavelets, because phase information is stable and significant, while symmetric points produce patterns easy to be recognised and confirmable in local phase. Phase method does not require any preprocessing, and its result is accurate or invariant to contrast, rotation and illumination conditions. This method can detect mirror symmetry, rotating symmetry and curve symmetry at one time. Results of experiment show that, compared with pivotal element algorithm based on intensity information, phase method is more accurate and robust.

  1. Sampling and coverage issues of telephone surveys used for collecting health information in Australia: results from a face-to-face survey from 1999 to 2008

    Science.gov (United States)

    2010-01-01

    Background To examine the trend of "mobile only" households, and households that have a mobile phone or landline telephone listed in the telephone directory, and to describe these groups by various socio-demographic and health indicators. Method Representative face-to-face population health surveys of South Australians, aged 15 years and over, were conducted in 1999, 2004, 2006, 2007 and 2008 (n = 14285, response rates = 51.9% to 70.6%). Self-reported information on mobile phone ownership and usage (1999 to 2008) and listings in White Pages telephone directory (2006 to 2008), and landline telephone connection and listings in the White Pages (1999 to 2008), was provided by participants. Additional information was collected on self-reported health conditions and health-related risk behaviours. Results Mobile only households have been steadily increasing from 1.4% in 1999 to 8.7% in 2008. In terms of sampling frame for telephone surveys, 68.7% of South Australian households in 2008 had at least a mobile phone or landline telephone listed in the White Pages (73.8% in 2006; 71.5% in 2007). The proportion of mobile only households was highest among young people, unemployed, people who were separated, divorced or never married, low income households, low SES areas, rural areas, current smokers, current asthma or people in the normal weight range. The proportion with landlines or mobiles telephone numbers listed in the White Pages telephone directory was highest among older people, married or in a defacto relationship or widowed, low SES areas, rural areas, people classified as overweight, or those diagnosed with arthritis or osteoporosis. Conclusion The rate of mobile only households has been increasing in Australia and is following worldwide trends, but has not reached the high levels seen internationally (12% to 52%). In general, the impact of mobile telephones on current sampling frames (exclusion or non-listing of mobile only households or not listed in the White

  2. Incorporating privileged genetic information for fundus image based glaucoma detection.

    Science.gov (United States)

    Duan, Lixin; Xu, Yanwu; Li, Wen; Chen, Lin; Wing, Damon Wing Kee; Wong, Tien Yin; Liu, Jiang

    2014-01-01

    Visual features extracted from retinal fundus images have been increasingly used for glaucoma detection, as those images are generally easy to acquire. In recent years, genetic researchers have found that some single nucleic polymorphisms (SNPs) play important roles in the manifestation of glaucoma and also show superiority over fundus images for glaucoma detection. In this work, we propose to use the SNPs to form the so-called privileged information and deal with a practical problem where both fundus images and privileged genetic information exist for the training subjects, while the test objects only have fundus images. To solve this problem, we present an effective approach based on the learning using privileged information (LUPI) paradigm to train a predictive model for the image visual features. Extensive experiments demonstrate the usefulness of our approach in incorporating genetic information for fundus image based glaucoma detection.

  3. Fast obstacle detection based on multi-sensor information fusion

    Science.gov (United States)

    Lu, Linli; Ying, Jie

    2014-11-01

    Obstacle detection is one of the key problems in areas such as driving assistance and mobile robot navigation, which cannot meet the actual demand by using a single sensor. A method is proposed to realize the real-time access to the information of the obstacle in front of the robot and calculating the real size of the obstacle area according to the mechanism of the triangle similarity in process of imaging by fusing datum from a camera and an ultrasonic sensor, which supports the local path planning decision. In the part of image analyzing, the obstacle detection region is limited according to complementary principle. We chose ultrasonic detection range as the region for obstacle detection when the obstacle is relatively near the robot, and the travelling road area in front of the robot is the region for a relatively-long-distance detection. The obstacle detection algorithm is adapted from a powerful background subtraction algorithm ViBe: Visual Background Extractor. We extracted an obstacle free region in front of the robot in the initial frame, this region provided a reference sample set of gray scale value for obstacle detection. Experiments of detecting different obstacles at different distances respectively, give the accuracy of the obstacle detection and the error percentage between the calculated size and the actual size of the detected obstacle. Experimental results show that the detection scheme can effectively detect obstacles in front of the robot and provide size of the obstacle with relatively high dimensional accuracy.

  4. Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

    CERN Document Server

    Greensmith, Julie; Tedesco, Gianni

    2010-01-01

    Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is sucessful at detecting port scans.

  5. Information-theoretical noninvasive damage detection in bridge structures

    Science.gov (United States)

    Sudu Ambegedara, Amila; Sun, Jie; Janoyan, Kerop; Bollt, Erik

    2016-11-01

    Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.

  6. Rock face stability analysis and potential rockfall source detection in Yosemite Valley

    Science.gov (United States)

    Matasci, B.; Stock, G. M.; Jaboyedoff, M.; Oppikofer, T.; Pedrazzini, A.; Carrea, D.

    2012-04-01

    Rockfall hazard in Yosemite Valley is especially high owing to the great cliff heights (~1 km), the fracturing of the steep granitic cliffs, and the widespread occurrence of surface parallel sheeting or exfoliation joints. Between 1857 and 2011, 890 documented rockfalls and other slope movements caused 15 fatalities and at least 82 injuries. The first part of this study focused on realizing a structural study for Yosemite Valley at both regional (valley-wide) and local (rockfall source area) scales. The dominant joint sets were completely characterized by their orientation, persistence, spacing, roughness and opening. Spacing and trace length for each joint set were accurately measured on terrestrial laser scanning (TLS) point clouds with the software PolyWorks (InnovMetric). Based on this fundamental information the second part of the study aimed to detect the most important failure mechanisms leading to rockfalls. With the software Matterocking and the 1m cell size DEM, we calculated the number of possible failure mechanisms (wedge sliding, planar sliding, toppling) per cell, for several cliffs of the valley. Orientation, spacing and persistence measurements directly issued from field and TLS data were inserted in the Matterocking calculations. TLS point clouds are much more accurate than the 1m DEM and show the overhangs of the cliffs. Accordingly, with the software Coltop 3D we developed a methodology similar to the one used with Matterocking to identify on the TLS point clouds the areas of a cliff with the highest number of failure mechanisms. Exfoliation joints are included in this stability analysis in the same way as the other joint sets, with the only difference that their orientation is parallel to the local cliff orientation and thus variable. This means that, in two separate areas of a cliff, the exfoliation joint set is taken into account with different dip direction and dip, but its effect on the stability assessment is the same. Areas with a high

  7. A Face Detection Method for Illumination Compensation Based on Adaboost%基于A daboos t的人脸光照补偿方法

    Institute of Scientific and Technical Information of China (English)

    李雪源; 袁晨; 姜代红

    2014-01-01

    Traditional Adaboost face detection algorithm uneven illumination image detection rate decreased problem ,we propose a face detection method based on Adaboost algorithm for illumination compensation .Details of the Adaboost face detection algorithm processing and histogram equalization principle and Adaboost algorithm and histogram equalization combined to achieve face detection .Test results show that this method compared with conventional Adaboost face detec-tion method to detect the speed difference is not big ,but uneven illumination image face detection accuracy and false detec-tion rate has very good results .%针对传统Adaboost人脸检测算法中光照不均匀、图像检测正确率低的问题,提出一种基于Adaboost算法的人脸光照补偿检测方法。介绍Adaboost人脸检测算法的处理流程以及直方图均衡化原理,并将Adaboost算法和直方图均衡化相结合,实现人脸检测。检测结果表明,与传统的Adaboost人脸检测方法相比,新方法对于光照不均匀图像的人脸检测有很好的效果。

  8. Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing.

    Science.gov (United States)

    Khadem, Ali; Hossein-Zadeh, Gholam-Ali; Khorrami, Anahita

    2016-03-01

    The majority of previous functional/effective connectivity studies conducted on the autistic patients converged to the underconnectivity theory of ASD: "long-range underconnectivity and sometimes short-rang overconnectivity". However, to the best of our knowledge the total (linear and nonlinear) predictive information transfers (PITs) of autistic patients have not been investigated yet. Also, EEG data have rarely been used for exploring the information processing deficits in autistic subjects. This study is aimed at comparing the total (linear and nonlinear) PITs of autistic and typically developing healthy youths during human face processing by using EEG data. The ERPs of 12 autistic youths and 19 age-matched healthy control (HC) subjects were recorded while they were watching upright and inverted human face images. The PITs among EEG channels were quantified using two measures separately: transfer entropy with self-prediction optimality (TESPO), and modified transfer entropy with self-prediction optimality (MTESPO). Afterwards, the directed differential connectivity graphs (dDCGs) were constructed to characterize the significant changes in the estimated PITs of autistic subjects compared with HC ones. By using both TESPO and MTESPO, long-range reduction of PITs of ASD group during face processing was revealed (particularly from frontal channels to right temporal channels). Also, it seemed the orientation of face images (upright or upside down) did not modulate the binary pattern of PIT-based dDCGs, significantly. Moreover, compared with TESPO, the results of MTESPO were more compatible with the underconnectivity theory of ASD in the sense that MTESPO showed no long-range increase in PIT. It is also noteworthy that to the best of our knowledge it is the first time that a version of MTE is applied for patients (here ASD) and it is also its first use for EEG data analysis.

  9. 基于SVM和HOG的人脸检测算法%Face Detection Based on SVM and HOG

    Institute of Scientific and Technical Information of China (English)

    赵峰

    2013-01-01

    In this paper, we propose a frontal face detection method based on Support Vector Machine (SVM) and Histogram of Oriented Gradients (HOG).Support Vector Machine selects support vectors according to the HOG feature and uses these support vectors to build the classiifer.The training and testing positive samples are all selected from the CMU PIE multi-pose and multi-illumination face database,the negative samples are selected from the Internet, the sample size is normalized to 20 × 20 pixels. The classifier of the detection system is a support vector machine, whose kernel function is linear. The feature we choose is ifrstly raised by Navneet Dalal and Bill Triggs in pedestrian detection issues,by selecting the appropriate parameters, we obtain a 384-dimensional feature, the cell size of the feature(Histogram of Oriented Gradients) is 4×4 pixels, each block contains four cells, and each cell contains six bins. The classiifer we trained has the detection rate of 92%on the test set and the false alarm rate is also low .By comparing the result of our method with the result of the face detection method based on adaboost of opencv, the result shows that our face detection system is quite good. In the CMU+MIT frontal face test set this method also achieved good results. Experimental results show that the proposed method in face detection problem is relatively effective.%本文提出了一种基于支持向量机和方向梯度直方图的正面人脸检测方法。支持向量机通过学习方向梯度直方图特征来选取支持向量,然后根据这些支持向量构建最优分类面。实验使用的训练样本和测试样本从CMU的PIE多姿态和多光照人脸数据库中选取,样本大小被标准化为20×20像素。检测系统选用的分类器是支持向量机,其核函数是线性的。选用的特征是Navneet Dalal和Bill Triggs在行人检测问题上提出的方向梯度直方图。训练好的分类器在测试集合上的检出率为92%。

  10. Application of DBNs for concerned internet information detecting

    Science.gov (United States)

    Wang, Yanfang; Gao, Song

    2017-03-01

    In recent years, deep learning has achieved great success in many fields, ranging from voice recognition and image classification to computer vision. In this study we apply DBNs to concerned internet information in Chinese detecting problem, since there are inherent differences between English and Chinese. Contrastive divergence (CD) is employed in the DBNs to learn a multi-layer generative model from numerous unlabeled data. The features obtained by this model are used to initialize the feed-forward neural network, which can be fine-tuned with backpropagation. Experiment results indicate that, the model and training method we proposed can be used to detect the concerned internet information effectively and accurately.

  11. Extraction of hidden information by efficient community detection in networks

    CERN Document Server

    Lee, Juyong; Lee, Jooyoung

    2012-01-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas.

  12. 基于肤色特征的人脸检测算法的研究%Face Detection Study Based on Skin Color Feature

    Institute of Scientific and Technical Information of China (English)

    边晶; 董迎红; 杜威

    2011-01-01

    通过对比面部识别技术的各种算法,本文重点研究了基于肤色特征的人脸检测算法。首先通过两种方法实现人脸的区域分割:基于相似度的方法和基于皮肤区域、头发区域的方法。前者通过相似度计算、二值化之后标记出人脸区域,后者利用颜色来检测人脸区域。人脸区域检测完毕之后再对其进行人脸特征的标注,最终实现面部检测。%By contrasting many algorithms of face detection technology, the algorithm of face detection based on skin-tone feature is mainly researched in this paper.Firstly realize the face region segmentation by two methods,the method based on similarity and the method based on skin region and hair region.The former method marks face region after similarity calculation and binaryzation,and the latter detect face region with different colors.When the face region detection is completed,we mark the face features,and then realize the final face detection.

  13. The Many Faces of Information Management. AIR 1998 Annual Forum Paper.

    Science.gov (United States)

    Krotseng, Marsha V.; McLaughlin, Gerald W.

    This paper examines the many facets of administrative information management on the college or university campus. It is argued that, depending on the situation, an effective information manager can adopt the outlook of an architect/designer, data administrator, editor, analyst, reporter, planner, broker, collaborator, interpreter, or marketer.…

  14. 3D Face Model Dataset: Automatic Detection of Facial Expressions and Emotions for Educational Environments

    Science.gov (United States)

    Chickerur, Satyadhyan; Joshi, Kartik

    2015-01-01

    Emotion detection using facial images is a technique that researchers have been using for the last two decades to try to analyze a person's emotional state given his/her image. Detection of various kinds of emotion using facial expressions of students in educational environment is useful in providing insight into the effectiveness of tutoring…

  15. An Approach to Face Recognition of 2-D Images Using Eigen Faces and PCA

    Directory of Open Access Journals (Sweden)

    Annapurna Mishra

    2012-05-01

    Full Text Available Face detection is to find any face in a given image. Face recognition is a two-dimension problem used fordetecting faces. The information contained in a face can be analysed automatically by this system likeidentity, gender, expression, age, race and pose. Normally face detection is done for a single image but itcan also be extended for video stream. As the face images are normally upright, they can be described by asmall set of 2-D characteristics views. Here the face images are projected to a feature space or face spaceto encode the variation between the known face images. The projected feature space or the face space canbe defined as ‘eigenfaces’ and can be formed by eigenvectors of the face image set. The above process canbe used to recognize a new face in unsupervised manner. This paper introduces an algorithm which is usedfor effective face recognition. It takes into consideration not only the face extraction but also themathematical calculations which enable us to bring the image into a simple and technical form. It can alsobe implemented in real-time using data acquisition hardware and software interface with the facerecognition systems. Face recognition can be applied to various domains including security systems,personal identification, image and film processing and human computer interaction.

  16. Enhancing community detection by using local structural information

    Science.gov (United States)

    Xiang, Ju; Hu, Ke; Zhang, Yan; Bao, Mei-Hua; Tang, Liang; Tang, Yan-Ni; Gao, Yuan-Yuan; Li, Jian-Ming; Chen, Benyan; Hu, Jing-Bo

    2016-03-01

    Many real-world networks, such as gene networks, protein-protein interaction networks and metabolic networks, exhibit community structures, meaning the existence of groups of densely connected vertices in the networks. Many local similarity measures in the networks are closely related to the concept of the community structures, and may have a positive effect on community detection in the networks. Here, various local similarity measures are used to extract local structural information, which is then applied to community detection in the networks by using the edge-reweighting strategy. The effect of the local similarity measures on community detection is carefully investigated and compared in various networks. The experimental results show that the local similarity measures are crucial for the improvement of community detection methods, while the positive effect of the local similarity measures is closely related to the networks under study and applied community detection methods.

  17. 医院信息化面临的安全挑战%The Information Security Challenges Faced by Hospitals

    Institute of Scientific and Technical Information of China (English)

    沈韬

    2012-01-01

    This article provides an overview of the information security challenges faced by hospitals in the process of healthcare reform. The solutions and implementation approaches for financial security, business continuity management, internet security and leakage of sensitive information were proposed. A brief analysis about significant barriers to promoting hospital information security governance was also in this article.%概述了医改形势下医院信息化所面临的安全挑战,针对财务安全、业务连续性管理、互联网安全和敏感信息泄漏问题提出了应对方案和实施策略,并对推进医院信息安全治理的主要障碍进行了简要分析.

  18. 基于openCV的人脸检测系统的设计%Face detection system design based on openCV

    Institute of Scientific and Technical Information of China (English)

    陈志恒; 姜明新

    2012-01-01

    According to the research of Adaboost algorithm of Face Detection,people made use of the algorithms and computer vision class library openCV for the design of face detection system and achieved the target of detecting faces showing up in videos and pictures.What's more,in the environment of VC++6.0,it achieved the development of simple Face Detection.The speed of Face Detection is very fast and the test results are accurate.It can be used as the development foundation of other face detection or face pattern recognition system.%通过对基于Adaboost人脸检测算法的研究,利用该算法与计算机视觉类库openCV进行人脸检测系统的设计,实现了对出现在视频或图像中的人脸检测。此外,在VC++6.0环境下实现了对一个简单的人脸检测系统软件的界面开发,该系统对人脸检测的速度较快,检测结果较为准确,可以作为其他人脸检测或人脸模式识别的系统的开发基础。

  19. New Problems Faced by Information Organizing in the Network Environment%网络环境下信息组织面临的新问题

    Institute of Scientific and Technical Information of China (English)

    倪莉

    2001-01-01

    In the network environment, information organizing faces many new problems, such as information filtration, bibliographic control, systematic indexing, etc. The key point of solving such problems is to extend the function of the traditional methods of information organizing so as to classify and catalog the network information resources mom effectively.

  20. Improving geo-information reliability by centralized change detection management

    NARCIS (Netherlands)

    Gorte, B.; Nardinocchi, C.; Thonon, I.; Addink, E.; Beck, R.; Persie, van M.; Kramer, H.

    2006-01-01

    A consortium called Mutatis Mutandis (MutMut), consisting of three Universities and eight producers and users of geo-information, was established in the Netherlands to streamline change detection on a national level. After preliminary investigations concerning market feasibility, three actions are

  1. Facing possible illness detected through screening--experiences of healthy women with pathological cervical smears

    DEFF Research Database (Denmark)

    Hounsgaard, Lise; Petersen, Lone Kjeld; Pedersen, Birthe D

    2007-01-01

    The aim of this study is to gain knowledge about women's perceptions of illness based on their abnormal PAP smears, following screening for cervical cancer. The study uses a phenomenological, hermeneutic approach inspired by Ricoeur's theory of interpretation. Twelve women, aged between 23 and 59...... of a face-value review of participant experiences (naive reading), structural analysis and, critical interpretation of what it means to be potentially ill. The women were unprepared to find that their screening results showed abnormal cells, indicative of incipient genital cancer. They were frustrated...... by the results as they had not experienced any symptoms and felt well, despite being diagnosed with a potential disease. Being diagnosed with abnormal cells caused the participants to feel anxious. Their anxiety had subsided 6 months after the cells had been removed. For those who did not require treatment...

  2. Incorporating profile information in community detection for online social networks

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2014-07-01

    Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

  3. In the Face of Cybersecurity How the Common Information Model can be used

    Energy Technology Data Exchange (ETDEWEB)

    Skare, Paul M.; Falk, Herbert; Rice, Mark J.; Winkel, Jens

    2016-01-01

    Efforts are underway to combine smart grid information, devices, networking, and emergency response information to create messages that are not dependent on specific standards development organizations (SDOs). This supports a future-proof approach of allowing changes in the canonical data models (CDMs) going forward without having to perform forklift replacements of solutions that use the messages. This also allows end users (electric utilities) to upgrade individual components of a larger system while keeping the message payload definitions intact. The goal is to enable public and private information sharing securely in a standards-based approach that can be integrated into existing operations. We provide an example architecture that could benefit from this multi-SDO, secure message approach. This article also describes how to improve message security

  4. Information visualization, physicality and intuitive use for tangible user inter- faces

    Institute of Scientific and Technical Information of China (English)

    HO U Shijiang; LIU Guohua

    2012-01-01

    In the last two decades, tangible user interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. TUIs show a potential to enhance the way in which people interact with digital information. First, this paper exam- ines the existing body of work on tangible user interfaces and discusses their application domains, especially information visualiza- tion. Then it provides a definition of intuitive use and reviews formerly separated ideas on physicality. As interaction has an impact on the overall product experience, we also discuss whether intuitive use influences the users' aesthetic judgements of such products.

  5. Robust Unstructured Road Detection: The Importance of Contextual Information

    Directory of Open Access Journals (Sweden)

    Erke Shang

    2013-03-01

    Full Text Available Unstructured road detection is a key step in an unmanned guided vehicle (UGV system for road following. However, current vision‐based unstructured road detection algorithms are usually affected by continuously changing backgrounds, different road types (shape, colour, variable lighting conditions and weather conditions. Therefore, a confidence map of road distribution, one of contextual information cues, is theoretically analysed and experimentally generated to help detect unstructured roads. Two traditional algorithms, support vector machine (SVM and k‐nearest neighbour (KNN, are carried out to verify the helpfulness of the proposed confidence map. Following this, a novel algorithm, which combines SVM, KNN and the confidence map under a Bayesian framework, is proposed to improve the overall performance of the unstructured road detections. The proposed algorithm has been evaluated using different types of unstructured roads and the experimental results show its effectiveness.

  6. Information dynamics algorithm for detecting communities in networks

    CERN Document Server

    Massaro, E; Bagnoli, F; Liò, P

    2011-01-01

    The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network - inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark ...

  7. Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle

    Science.gov (United States)

    Thurner, Stefan; Corominas-Murtra, Bernat; Hanel, Rudolf

    2017-09-01

    There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a means for statistical inference on multinomial processes (Jaynes maximum entropy principle). Even though these notions represent fundamentally different concepts, the functional form of the entropy for thermodynamic systems in equilibrium, for ergodic sources in information theory, and for independent sampling processes in statistical systems, is degenerate, H (p ) =-∑ipilogpi . For many complex systems, which are typically history-dependent, nonergodic, and nonmultinomial, this is no longer the case. Here we show that for such processes, the three entropy concepts lead to different functional forms of entropy, which we will refer to as SEXT for extensive entropy, SIT for the source information rate in information theory, and SMEP for the entropy functional that appears in the so-called maximum entropy principle, which characterizes the most likely observable distribution functions of a system. We explicitly compute these three entropy functionals for three concrete examples: for Pólya urn processes, which are simple self-reinforcing processes, for sample-space-reducing (SSR) processes, which are simple history dependent processes that are associated with power-law statistics, and finally for multinomial mixture processes.

  8. GlobePort Faces Global Business Challenges--Assessing the Organizational Side of Information Systems Projects

    Science.gov (United States)

    Ghosh, Biswadip

    2011-01-01

    Published studies have reported that Information System (IS) projects succeed or fail based on how effectively the organizational issues were understood and addressed in the specification, development and implementation stages of the project. This is particularly true in the design and delivery of Inter-Organizational Systems (IOS) that can affect…

  9. Facial Electromyographic Responses to Emotional Information from Faces and Voices in Individuals with Pervasive Developmental Disorder

    Science.gov (United States)

    Magnee, Maurice J. C. M.; de Gelder, Beatrice; van Engeland, Herman; Kemner, Chantal

    2007-01-01

    Background: Despite extensive research, it is still debated whether impairments in social skills of individuals with pervasive developmental disorder (PDD) are related to specific deficits in the early processing of emotional information. We aimed to test both automatic processing of facial affect as well as the integration of auditory and visual…

  10. Examining the Hemispheric Distribution of Semantic Information Using Lateralised Priming of Familiar Faces

    Science.gov (United States)

    Vladeanu, Matei; Bourne, Victoria J.

    2009-01-01

    The way in which the semantic information associated with people is organised in the brain is still unclear. Most evidence suggests either bilateral or left hemisphere lateralisation. In this paper we use a lateralised semantic priming paradigm to further examine this neuropsychological organisation. A clear semantic priming effect was found with…

  11. Baseline Face Detection, Head Pose Estimation, and Coarse Direction Detection for Facial Data in the SHRP2 Naturalistic Driving Study

    Energy Technology Data Exchange (ETDEWEB)

    Paone, Jeffrey R [ORNL; Bolme, David S [ORNL; Ferrell, Regina Kay [ORNL; Aykac, Deniz [ORNL; Karnowski, Thomas Paul [ORNL

    2015-01-01

    Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume, and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.

  12. A Reconfigurable Architecture for Rotation Invariant Multi-View Face Detection Based on a Novel Two-Stage Boosting Method

    Directory of Open Access Journals (Sweden)

    Zhengbin Pang

    2009-01-01

    Full Text Available We present a reconfigurable architecture model for rotation invariant multi-view face detection based on a novel two-stage boosting method. A tree-structured detector hierarchy is designed to organize multiple detector nodes identifying pose ranges of faces. We propose a boosting algorithm for training the detector nodes. The strong classifier in each detector node is composed of multiple novelly designed two-stage weak classifiers. With a shared output space of multicomponents vector, each detector node deals with the multidimensional binary classification problems. The design of the hardware architecture which fully exploits the spatial and temporal parallelism is introduced in detail. We also study the reconfiguration of the architecture for finding an appropriate tradeoff among the hardware implementation cost, the detection accuracy, and speed. Experiments on FPGA show that high accuracy and marvelous speed are achieved compared with previous related works. The execution time speedups range from 14.68 to 20.86 for images with size of 160×120 up to 800×600 when our FPGA design (98 MHz is compared with software solution on PC (Pentium 4 2.8 GHz.

  13. Redox cycling with facing interdigitated array electrodes as a method for selective detection of redox species

    NARCIS (Netherlands)

    Dam, V.A.T.; Olthuis, W.; Berg, van den A.

    2007-01-01

    A pair of interdigitated ultramicroelectrodes (UMEs) is used to electrochemically detect a weak reductor ( dopamine) in the presence of a stronger one (K-4[ Fe(CN)(6)]). In the mixture of both reductors, one of the two interdigitated electrodes ( the generator electrode) is used to oxidize both spec

  14. Pesticide Health and Safety Challenges Facing Informal Sector Workers: A Case of Small-scale Agricultural Workers in Tanzania.

    Science.gov (United States)

    Ngowi, Aiwerasia; Mrema, Ezra; Kishinhi, Stephen

    2016-08-01

    The Tanzania informal sector is growing fast, with precarious working conditions and particular hazards for women and children in agriculture. Hazardous agricultural chemicals including pesticides are mostly imported and have been used for many years. Despite the role played by pesticides in food security and vector control, these chemicals are responsible for acute and chronic illnesses among communities. The availability of obsolete persistent organic pesticides on the open market indicates existence of an inadequate regulatory system. People who get injured or ill in the agriculture sector in Tanzania receive health services in primary health care facilities where professionals have little or no knowledge of pesticides. We are presenting the pesticide health and safety challenges faced by small-scale farmers who fall in the informal sector. Achievements that have been made by the government and other players to reduce and prevent pesticide exposures and poisoning are also outlined.

  15. The compassionate brain: humans detect intensity of pain from another's face.

    Science.gov (United States)

    Saarela, Miiamaaria V; Hlushchuk, Yevhen; Williams, Amanda C de C; Schürmann, Martin; Kalso, Eija; Hari, Riitta

    2007-01-01

    Understanding another person's experience draws on "mirroring systems," brain circuitries shared by the subject's own actions/feelings and by similar states observed in others. Lately, also the experience of pain has been shown to activate partly the same brain areas in the subjects' own and in the observer's brain. Recent studies show remarkable overlap between brain areas activated when a subject undergoes painful sensory stimulation and when he/she observes others suffering from pain. Using functional magnetic resonance imaging, we show that not only the presence of pain but also the intensity of the observed pain is encoded in the observer's brain-as occurs during the observer's own pain experience. When subjects observed pain from the faces of chronic pain patients, activations in bilateral anterior insula (AI), left anterior cingulate cortex, and left inferior parietal lobe in the observer's brain correlated with their estimates of the intensity of observed pain. Furthermore, the strengths of activation in the left AI and left inferior frontal gyrus during observation of intensified pain correlated with subjects' self-rated empathy. These findings imply that the intersubjective representation of pain in the human brain is more detailed than has been previously thought.

  16. Community detection using global and local structural information

    Indian Academy of Sciences (India)

    Hai-Long Yan; Ju Xiang; Xiao-Yu Zhang; Jun-Feng Fan; Fang Chane; Gen-Yi Fu; Er-Min Guo; Xin-Guang Hu; Ke Hu; Ru-Min Wang

    2013-01-01

    Community detection is of considerable importance for understanding both the structure and function of complex networks. In this paper, we introduced the general procedure of the community detection algorithms using global and local structural information, where the edge betweenness and the local similarity measures respectively based on local random walk dynamics and local cyclic structures were used. The algorithms were tested on artificial and real-world networks. The results clearly show that all the algorithms have excellent performance in the tests and the local similarity measure based on local random walk dynamics is superior to that based on local cyclic structures.

  17. Psychopathy and Physiological Detection of Concealed Information: A review

    Directory of Open Access Journals (Sweden)

    Bruno Verschuere

    2006-03-01

    Full Text Available The Concealed Information Test has been advocated as the preferred method for deception detection using the polygraph ("lie detector". The Concealed Information Test is argued to be a standardised, highly accurate psychophysiological test founded on the orienting reflex. The validity of polygraph tests for the assessment of psychopathic individuals has, however, been questioned. Two dimensions are said to underlie psychopathy: emotional detachment and antisocial behaviour. Distinct psychophysiological correlates are hypothesised in these facets of psychopathy. Emotional detachment is associated with deficient fear-potentiated startle, and antisocial behaviour with reduced orienting. Few studies have examined the effect of psychopathy on the validity of the Concealed Information Test. This review suggests that reduced orienting in high antisocial individuals is also found in the Concealed Information Test, thereby threatening its validity. Implications for criminal investigations, possible solutions and directions for future research will be discussed.

  18. Information dynamics algorithm for detecting communities in networks

    Science.gov (United States)

    Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

    2012-11-01

    The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

  19. Detecting Marionette Microblog Users for Improved Information Credibility

    Institute of Scientific and Technical Information of China (English)

    吴贤; 范••伟; 高晶; 冯子明; 俞勇

    2015-01-01

    In this paper, we propose to detect a special group of microblog users: the “marionette” users, who are created or employed by backstage “puppeteers”, either through programs or manually. Unlike normal users that access microblog for information sharing or social communication, the marionette users perform specific tasks to earn financial profits. For example, they follow certain users to increase their “statistical popularity”, or retweet some tweets to amplify their “statistical impact”. The fabricated follower or retweet counts not only mislead normal users to wrong information, but also seriously impair microblog-based applications, such as hot tweets selection and expert finding. In this paper, we study the important problem of detecting marionette users on microblog platforms. This problem is challenging because puppeteers are employing complicated strategies to generate marionette users that present similar behaviors as normal users. To tackle this challenge, we propose to take into account two types of discriminative information: 1) individual user tweeting behavior and 2) the social interactions among users. By integrating both information into a semi-supervised probabilistic model, we can e昇ectively distinguish marionette users from normal ones. By applying the proposed model to one of the most popular microblog platforms (Sina Weibo) in China, we find that the model can detect marionette users with F-measure close to 0.9. In addition, we apply the proposed model to calculate the marionette ratio of the top 200 most followed microbloggers and the top 50 most retweeted posts in Sina Weibo. To accelerate the detecting speed and reduce feature generation cost, we further propose a light-weight model which utilizes fewer features to identify marionettes from retweeters.

  20. Face-to-face: Perceived personal relevance amplifies face processing.

    Science.gov (United States)

    Bublatzky, Florian; Pittig, Andre; Schupp, Harald T; Alpers, Georg W

    2017-05-01

    The human face conveys emotional and social information, but it is not well understood how these two aspects influence face perception. In order to model a group situation, two faces displaying happy, neutral or angry expressions were presented. Importantly, faces were either facing the observer, or they were presented in profile view directed towards, or looking away from each other. In Experiment 1 (n = 64), face pairs were rated regarding perceived relevance, wish-to-interact, and displayed interactivity, as well as valence and arousal. All variables revealed main effects of facial expression (emotional > neutral), face orientation (facing observer > towards > away) and interactions showed that evaluation of emotional faces strongly varies with their orientation. Experiment 2 (n = 33) examined the temporal dynamics of perceptual-attentional processing of these face constellations with event-related potentials. Processing of emotional and neutral faces differed significantly in N170 amplitudes, early posterior negativity (EPN), and sustained positive potentials. Importantly, selective emotional face processing varied as a function of face orientation, indicating early emotion-specific (N170, EPN) and late threat-specific effects (LPP, sustained positivity). Taken together, perceived personal relevance to the observer-conveyed by facial expression and face direction-amplifies emotional face processing within triadic group situations. © The Author (2017). Published by Oxford University Press.

  1. UiO-66 MOF end-face-coated optical fiber in aqueous contaminant detection.

    Science.gov (United States)

    Nazari, Marziyeh; Forouzandeh, Mohammad Ali; Divarathne, Chamath M; Sidiroglou, Fotios; Martinez, Marta Rubio; Konstas, Kristina; Muir, Benjamin W; Hill, Anita J; Duke, Mikel C; Hill, Matthew R; Collins, Stephen F

    2016-04-15

    Optical quality metal organic framework (MOF) thin films were integrated, for the first time, to the best of our knowledge, with structured optical fiber substrates to develop MOF-fiber sensors. The MOF-fiber structure, UiO-66 (Zr-based MOF is well known for its water stability), is a thin film that acts as an effective analyte collector. This provided a Fabry-Perot sensor in which concentrations of up to 15 mM Rhodamine-B were detected via wavelength shifts in the interference spectrum.

  2. Low spatial frequency bias in schizophrenia is not face specific: When the integration of coarse and fine information fails

    Directory of Open Access Journals (Sweden)

    Vincent eLaprevote

    2013-05-01

    Full Text Available Studies have shown that patients with schizophrenia exhibit visual processing impairments, particularly regarding the processing of spatial frequencies. In a previous work, we found that, compared to healthy volunteers, patients were biased towards low spatial frequencies (LSF to identify facial expression at a glance. Given the ubiquity of faces in visual perception, it remains an open question whether the LSF bias is face specific or also occurs with other visual objects. Here, fifteen patients with schizophrenia and eleven healthy control adults performed a categorization task with hybrid stimuli. These stimuli were single images consisting of two different objects, a fruit and an animal, each in a specific spatial frequency range, either low (LSF or high (HSF. Observers were asked to report if they saw an animal or a fruit. The reported category demonstrated which spatial scale was preferentially perceived in each trial. In a control experiment, participants performed the same task but with images of only a single object, either a LSF or HSF filtered animal or fruit, to verify that participants could perceive both HSF or LSF when presented in isolation. The results on the categorization task showed that patients chose more frequently LSF with hybrid stimuli compared to healthy controls. However, both populations performed equally well with HSF and LSF filtered pictures in the control experiment, demonstrating that the LSF preference found with hybrid stimuli in patients was not due to an inability to perceive HSF.The LSF preference found in schizophrenia confirms our previous study conducted with faces, and shows that this LSF bias generalizes to other categories of objects. When a broad range of spatial frequencies are present in the image, as in normal conditions of viewing, patients preferentially rely on coarse visual information contained in LSF. This result may be interpreted as a dysfunction of the guidance of HSF processing by LSF

  3. Extraction of hidden information by efficient community detection in networks

    Science.gov (United States)

    Lee, Jooyoung; Lee, Juyong; Gross, Steven

    2013-03-01

    Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 20120001222).

  4. Multirobot autonomous landmine detection using distributed multisensor information aggregation

    Science.gov (United States)

    Jumadinova, Janyl; Dasgupta, Prithviraj

    2012-06-01

    We consider the problem of distributed sensor information fusion by multiple autonomous robots within the context of landmine detection. We assume that different landmines can be composed of different types of material and robots are equipped with different types of sensors, while each robot has only one type of landmine detection sensor on it. We introduce a novel technique that uses a market-based information aggregation mechanism called a prediction market. Each robot is provided with a software agent that uses sensory input of the robot and performs calculations of the prediction market technique. The result of the agent's calculations is a 'belief' representing the confidence of the agent in identifying the object as a landmine. The beliefs from different robots are aggregated by the market mechanism and passed on to a decision maker agent. The decision maker agent uses this aggregate belief information about a potential landmine and makes decisions about which other robots should be deployed to its location, so that the landmine can be confirmed rapidly and accurately. Our experimental results show that, for identical data distributions and settings, using our prediction market-based information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques.

  5. Estimation of the limit of detection using information theory measures.

    Science.gov (United States)

    Fonollosa, Jordi; Vergara, Alexander; Huerta, Ramón; Marco, Santiago

    2014-01-31

    Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.

  6. A New Face Detection Algorithm Based on Template Match in Compress Domain%一种基于压缩域模板匹配的快速人脸检测算法

    Institute of Scientific and Technical Information of China (English)

    王剑峰

    2011-01-01

    The face detection and tracking is the key technology in the field of face information processing,it widely applied in the fields of automated face recognition system,content based image retrieval, video monitoring,shortcut detection and human-machine alternative technology. Firstly,detect the skin area of one image with the statistics theory, next, convert these area into compress domain through discrete Walsh transform, lastly,propose the new eight directions chain code template and angle template to judge whether the face region or not. The experimental results show the superiority of the proposed algorithm in terms of human face retrieval precision and speed, it also very suitable for face detection system that requires the timeliness highly.%人脸的检测是人脸信息处理领域中的一项关键技术,在自动人脸识别系统、基于内容的图像检索、视觉监测、场景检测、新一代人机交互技术等领域具有广阔的应用前景.通过在压缩域利用DC系数重构图像,提出了改进的链码模板和通过训练产生角度模板来对候选区域进行搜索匹配和检测.实验结果显示,本方法在检测人脸的过程中速度快,漏检率较低,非常适合实时性要求高的人脸检测系统.

  7. Coastal Hazards Maps: Actionable Information for Communities Facing Sea-Level Rise (Invited)

    Science.gov (United States)

    Gibeaut, J. C.; Barraza, E.

    2010-12-01

    Barrier islands along the U.S. Gulf coast remain under increasing pressure from development. This development and redevelopment is occurring despite recent hurricanes, ongoing erosion, and sea-level rise. To lessen the impacts of these hazards, local governments need information in a form that is useful for informing the public, making policy, and enforcing development rules. We recently completed the Galveston Island Geohazards Map for the city of Galveston, Texas and are currently developing maps for the Mustang and South Padre Island communities. The maps show areas that vary in their susceptibility to, and function for, mitigating the effects of geological processes, including sea-level rise, land subsidence, erosion and storm-surge flooding and washover. The current wetlands, beaches and dunes are mapped as having the highest geohazard potential both in terms of their exposure to hazardous conditions and their mitigating effects of those hazards for the rest of the island. These existing “critical environments” are generally protected under existing regulations. Importantly, however, the mapping recognizes that sea-level rise and shoreline retreat are changing the island; therefore, 60-year model projections of the effects of these changes are incorporated into the map. The areas that we project will become wetlands, beaches and dunes in the next 60 years are not protected. These areas are the most difficult to deal with from a policy point of view, yet we must address what happens there if real progress is to be made in how we live with sea-level rise. The geohazards maps draw on decades of geological knowledge of how barrier islands behave and put it in a form that is intuitive to the public and directly useful to planners. Some of the “messages” in the map include: leave salt marshes alone and give them room to migrate inland as sea level rises; set back and move development away from the shoreline to provide space for beaches and protective dunes

  8. Research Based on Digital Image Irocessing of Face Detection Algorithm%基于数字图像处理的人脸检测算法研究

    Institute of Scientific and Technical Information of China (English)

    刘笃晋; 邓小亚; 蒲国林

    2012-01-01

      Face detection is premise and the foundation of face recognition, at the same time ,it has very important application val⁃ue in the digital video processing, authentication, content based retrieval, visual detection, this paper makes a study based on digi⁃tal image processing, color face detection steps at the present situation, that include human face image denoising, human face im⁃age edge detection, human face image segmentation, image the illumination effect removal, and points out the future develop⁃ment direction of each step.%  人脸检测是人脸识别的前提和基础,同时在数字视频处理、身份验证、基于内容的检索、视觉检测等方面都有着非常重要的应用价值,该文对基于数字图像处理的彩色人脸检测的各个步骤包括图像去噪、图像边缘检测、图像分割、图像光照影响的去除等的发展现状进行了研究,并指出了各个步骤以后的发展方向。

  9. 利用SVM改进Adaboost算法的人脸检测精度%IMPROVING FACE DETECTION ACCURACY IN ADABOOST ALGORITHM WITH SVM

    Institute of Scientific and Technical Information of China (English)

    王志伟; 张晓龙; 梁文豪

    2011-01-01

    提出利用SVM分类方法改进Adaboost算法的人脸检测精度.该方法先通过Adaboost算法找出图像中的候选人脸区域,根据训练样本集中的人脸和非人脸样本训练出分类器支持向量机(SVM),然后通过SVM分类器从候选人脸区域中最终确定人脸区域.实验结果证明,SVM分类算法可以提高检测精度,使检测算法具有更好的检测效果.%This paper presents an approach to improve the face detection accuracy in Adaboost algorithm with SVM. Firstly, the method finds out candidate regions of the human face in the image, and trains the classifier of support vector machine (SVM) according to human face samples and non-face samples in the training sample set, then eventually determine the region of human face from candidate face regions by SVM classifier. Experimental results show that the SVM classifying algorithm can improve the detection accuracy and makes the detection algorithm better in detection efficiency.

  10. Females excel at basic face perception.

    Science.gov (United States)

    McBain, Ryan; Norton, Dan; Chen, Yue

    2009-02-01

    Females are generally better than males at recognizing facial emotions. However, it is not entirely clear whether and in what way females may also excel at non-affective face recognition. Here, we tested males and females on two perceptual face recognition tasks that involved only neutral expressions: detection and identity discrimination. On face detection (Experiment 1), females were significantly more accurate than males in detecting upright faces. This gender difference was reduced during inverted face detection, and not present during tree detection, suggesting that the magnitude of the gender difference for performance co-varies with the extent to which face processing mechanisms are involved. On facial identity discrimination (Experiment 2), females again outperformed males, particularly when face images were masked by visual noise, or the delay between comparison face images was extended from 0.5 to 3s. These results reveal a female advantage in processing face-specific information and underscore the role of perceptual factors in socially relevant gender differences.

  11. Pro-active data breach detection: examining accuracy and applicability on personal information detected

    CSIR Research Space (South Africa)

    Botha, J

    2016-03-01

    Full Text Available breaches but does not provide a clear indication of the level of personal information available on the internet since only reported incidents are taken into account. The possibility of pro-active automated breach detection has previously been discussed as a...

  12. Distinct representations of configural and part information across multiple face-selective regions of the human brain

    OpenAIRE

    Golijeh eGolarai; Dara eGhahremani; Eberhardt, Jennifer L.; John D E Gabrieli

    2015-01-01

    Several regions of the human brain respond more strongly to faces than to other visual stimuli, such as regions in the amygdala (AMG), superior temporal sulcus (STS), and the fusiform face area (FFA). It is unclear if these brain regions are similar in representing the configuration or natural appearance of face parts. We used functional magnetic resonance imaging of healthy adults who viewed natural or schematic faces with internal parts that were either normally configured or randomly rearr...

  13. ENSEMBLE DESIGN OF MASQUERADER DETECTION SYSTEMS FOR INFORMATION SECURITY

    Directory of Open Access Journals (Sweden)

    T. Subbulakshmi

    2011-01-01

    Full Text Available Masqueraders are a category of intruders who impersonate other people on a computer system and use this entry point to use the information stored in the systems or throw other attacks into the network. This paper focuses on Ensemble Design of a Masquerader Detection System using Decision trees and Support Vector Machines for classification with two kernel functions linear and linear BSpline. The key idea is to find out specific patterns of command sequence that tells about user behaviour on a system, and use them to build classifiers that can perfectly recognize anomalous and normal behaviour. Real time truncated command line data set collected from a debian Linux server is used for performance comparison of the developed classifiers with the standard truncated command line data set of Schonlau[4]. The results show that Ensemble Design of Masquerader Detection Systems is much faster than individual Decision trees or Support Vector Machines.

  14. Fast Face Detection Algorithm Based on CUDA%基于CUDA的快速人脸检测算法

    Institute of Scientific and Technical Information of China (English)

    孙立超; 张盛兵; 程训焘; 张萌

    2013-01-01

    For the traditional CPU facial detection program is difficult to meet the requirements of real-time detection over high definition images,this paper proposes a fast face detection algorithm based on the Viola-Jones cascade classifier in the CUDA platform.It implements and improves novel parallel methodologies of image integral calculation,scan window processing and the amplification and correction of classifiers.The load imbalance problem of irregular tree structure applications could be effectively solved by the window re-mapping technology used in the scan window processing.The experimental results show that the CUDA program could respectively achieve 17.04,3.22 times speedup compared with the CPU and OpenCV programs for the 1080p image,while maintaining a similar detection quality.%针对传统的CPU人脸检测程序难以满足高清图像实时检测要求的问题,本文提出一种在CUDA平台下基于Viola-Jones级联分类器的快速人脸检测算法,其中积分图计算、扫描窗口检测和分类器放大修正部分均进行了并行加速.扫描窗口检测采用的窗口重映射技术可有效解决非规则树结构应用的负载不均衡问题.实验结果表明,对于1080p图像,CUDA程序与CPU和OpenCV程序相比可分别实现17.04、3.22倍的加速比,同时具有相近的检测精度.

  15. Rapid prototyping of SoC-based real-time vision system: application to image preprocessing and face detection

    Science.gov (United States)

    Jridi, Maher; Alfalou, Ayman

    2017-05-01

    By this paper, the major goal is to investigate the Multi-CPU/FPGA SoC (System on Chip) design flow and to transfer a know-how and skills to rapidly design embedded real-time vision system. Our aim is to show how the use of these devices can be benefit for system level integration since they make possible simultaneous hardware and software development. We take the facial detection and pretreatments as case study since they have a great potential to be used in several applications such as video surveillance, building access control and criminal identification. The designed system use the Xilinx Zedboard platform. The last is the central element of the developed vision system. The video acquisition is performed using either standard webcam connected to the Zedboard via USB interface or several camera IP devices. The visualization of video content and intermediate results are possible with HDMI interface connected to HD display. The treatments embedded in the system are as follow: (i) pre-processing such as edge detection implemented in the ARM and in the reconfigurable logic, (ii) software implementation of motion detection and face detection using either ViolaJones or LBP (Local Binary Pattern), and (iii) application layer to select processing application and to display results in a web page. One uniquely interesting feature of the proposed system is that two functions have been developed to transmit data from and to the VDMA port. With the proposed optimization, the hardware implementation of the Sobel filter takes 27 ms and 76 ms for 640x480, and 720p resolutions, respectively. Hence, with the FPGA implementation, an acceleration of 5 times is obtained which allow the processing of 37 fps and 13 fps for 640x480, and 720p resolutions, respectively.

  16. 基于Adaboost算法的人脸检测技术的研究与实现%Research and Realization of Face Detection Technology Based on Adaboost Algorithm

    Institute of Scientific and Technical Information of China (English)

    张宁; 李娜

    2011-01-01

    人脸检测是人脸识别技术的基础,首先提出人脸检测系统的构成,分析Adaboost算法对图像进行人脸检测的基本原理.根据Adaboost算法形成了简单的矩形特征作为人脸特征,即Haarlike特征,然后由多个Haarlike特征相当于一个弱分类器,由多个弱分类器级联成为一个强的分类器,并将级联分类器用于动态人脸检测中,从截取的每一帧图像中进行检浏.经过实验验证,采用这种方法和步骤进行人脸检测达到了比较好的精度和速度,为接下来的人脸识别提供了前提条件.%Face detection is the basis of face recognition. The structure of the face detection system is introduced and the basic principles of Adaboost algorithm is analyzed inthis paper. Based on Adaboost algorithm, a simple rectangular feature is formed as a facial feature, whch is Haar-like features. A weak classifier is formed by a number of Haar-Iike features, and multiple weak classifiers are cascaded into a strong classifier. The cascade classifier is used in dynamic face detection to detect faces captured from each frame image. Experimental results show that this method and process of face detection can achieve a relarively good accuracy and high speed, and provide preconditions for the next face recognition.

  17. 2-D contact detection and localization using proprioceptive information

    Energy Technology Data Exchange (ETDEWEB)

    Huber, M.; Grupen, R.A. (Univ. of Massachusetts, Amherst, MA (United States). Dept. of Computer Science)

    1994-02-01

    This paper employs proprioceptive information (joint angles and torques) to estimate properties of the contact between a planar robot and an unknown object without specifically requiring strategic manipulator motions. The algorithm presented tackles this task in two stages; a contact localization analysis is followed by a force domain contact detection analysis. In the former, the Cartesian endpoint velocities are used for each link to obtain an estimate of the location of a hypothetical contact point on the link surface. A second observer, based on the displacement between two consecutive postures of the manipulator, provides an estimate of the error associated with this location. This data is fused over time by tracking the contact location using a linear observer and results in a hypothetical contact location, an associated uncertainty region, and a surface normal estimate. The detection phase uses torque domain evidence and the location estimates to verify the existence of each of the contacts. This process allows the detection of one contact per link and provides estimates of contact location, velocity, surface normal, and contact force.

  18. Child vocalization composition as discriminant information for automatic autism detection.

    Science.gov (United States)

    Xu, Dongxin; Gilkerson, Jill; Richards, Jeffrey; Yapanel, Umit; Gray, Sharmi

    2009-01-01

    Early identification is crucial for young children with autism to access early intervention. The existing screens require either a parent-report questionnaire and/or direct observation by a trained practitioner. Although an automatic tool would benefit parents, clinicians and children, there is no automatic screening tool in clinical use. This study reports a fully automatic mechanism for autism detection/screening for young children. This is a direct extension of the LENA (Language ENvironment Analysis) system, which utilizes speech signal processing technology to analyze and monitor a child's natural language environment and the vocalizations/speech of the child. It is discovered that child vocalization composition contains rich discriminant information for autism detection. By applying pattern recognition and machine learning approaches to child vocalization composition data, accuracy rates of 85% to 90% in cross-validation tests for autism detection have been achieved at the equal-error-rate (EER) point on a data set with 34 children with autism, 30 language delayed children and 76 typically developing children. Due to its easy and automatic procedure, it is believed that this new tool can serve a significant role in childhood autism screening, especially in regards to population-based or universal screening.

  19. Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol.

    Science.gov (United States)

    Kasturi, Rangachar; Goldgof, Dmitry; Soundararajan, Padmanabhan; Manohar, Vasant; Garofolo, John; Bowers, Rachel; Boonstra, Matthew; Korzhova, Valentina; Zhang, Jing

    2009-02-01

    Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic improvements. In this paper, we present such a framework for evaluating object detection and tracking in video: specifically for face, text, and vehicle objects. This framework includes the source video data, ground-truth annotations (along with guidelines for annotation), performance metrics, evaluation protocols, and tools including scoring software and baseline algorithms. For each detection and tracking task and supported domain, we developed a 50-clip training set and a 50-clip test set. Each data clip is approximately 2.5 minutes long and has been completely spatially/temporally annotated at the I-frame level. Each task/domain, therefore, has an associated annotated corpus of approximately 450,000 frames. The scope of such annotation is unprecedented and was designed to begin to support the necessary quantities of data for robust machine learning approaches, as well as a statistically significant comparison of the performance of algorithms. The goal of this work was to systematically address the challenges of object detection and tracking through a common evaluation framework that permits a meaningful objective comparison of techniques, provides the research community with sufficient data for the exploration of automatic modeling techniques, encourages the incorporation of objective evaluation into the development process, and contributes useful lasting resources of a scale and magnitude that will prove to be extremely useful to the computer vision research community for years to come.

  20. This person is saying bad things about you: The influence of physically and socially threatening context information on the processing of inherently neutral faces.

    Science.gov (United States)

    Klein, Fabian; Iffland, Benjamin; Schindler, Sebastian; Wabnitz, Pascal; Neuner, Frank

    2015-12-01

    Recent studies have shown that the perceptual processing of human faces is affected by context information, such as previous experiences and information about the person represented by the face. The present study investigated the impact of verbally presented information about the person that varied with respect to affect (neutral, physically threatening, socially threatening) and reference (self-referred, other-referred) on the processing of faces with an inherently neutral expression. Stimuli were presented in a randomized presentation paradigm. Event-related potential (ERP) analysis demonstrated a modulation of the evoked potentials by reference at the EPN (early posterior negativity) and LPP (late positive potential) stage and an enhancing effect of affective valence on the LPP (700-1000 ms) with socially threatening context information leading to the most pronounced LPP amplitudes. We also found an interaction between reference and valence with self-related neutral context information leading to more pronounced LPP than other related neutral context information. Our results indicate an impact of self-reference on early, presumably automatic processing stages and also a strong impact of valence on later stages. Using a randomized presentation paradigm, this study confirms that context information affects the visual processing of faces, ruling out possible confounding factors such as facial configuration or conditional learning effects.

  1. 基于肤色模型的人脸检测研究%Research of Face Detection Based on Skin Colour Model

    Institute of Scientific and Technical Information of China (English)

    李智勇; 田贞

    2011-01-01

    For the existing face detection methods can not achieve an ideal detecting effect for the colorized face image obtained in complex illumination environment , the face detection method based on skin color segmentation and template matching is improved, and a human faces detection method based on lighting pre-processing, skin model and template matching is proposed after making a study of the current face detection methods.Experimental results obtained with the new method show that the correct rate of detecting the positive and quasi-positive facial images in real environment is 84% , algorithm is insensitive for the illumination and has high robustness to the Changes in posture and expression of face images.%现有的人脸检测方法,对复杂光照环境下获得的彩色人脸图像的检测效果仍不太理想.在仔细研究目前人脸检测方法的基础上,对基于肤色分割结合模板匹配的人脸检测方法进行改进,提出基于"光照预处理+肤色模型+模板匹配"的人脸检测问题解决思路.实验结果表明,该方法对实际场景中正面和准正面的人脸图像,平均准检率达到84%,同时对光照变化不敏感,而且对姿态和表情的变化也具有较好的鲁棒性.

  2. Face detection tracking and feature point positioning system%人脸检测跟踪与特征点定位系统

    Institute of Scientific and Technical Information of China (English)

    何英杰; 李国新

    2012-01-01

    实现的人脸检测跟踪与特征点定位系统,基于VC++6.0开发平台,使用opencv作为开发工具,有效缩短了系统的开发时间。首先,本系统采用adaboost算法进行人脸检测,通过合理的特征模板的选择实现了人脸的实时检测;其次,人脸跟踪模块选用camshift算法,利用人脸检测模块生成的人脸坐标传递给跟踪模块,实现人脸的自动实时跟踪,同时建立多个camshift跟踪器对多人脸进行跟踪,并有效地解决了人脸遮挡的问题;最后,通过ASM(active shapemodel)算法实现了实时人脸特征点定位。实验结果表明该系统实现的人脸实时检测跟踪及特征点定位,效果明显,可以作为表情分析和情感计算、视频人脸识别开发的基础。%Face detection and tracking and feature point locating system of this article,based on VC++6.0 development platform,using OpenCV as development tools,effectively shortens the development time for systems.Firstly,The system adopts the adaboost algorithm for face detection,implements face real-time detection by means of a reasonable feature template selection.Secondly,the face tracking module selects camshift algorithm,the article uses face detection generating face coordinates passing it to the tracking module,realizes automatic face real-time tracking,and tracks multiple faces by using multiple camshift Tracker,and effectively solves the problem of face block.Finally,the system accomplishes real-time facial feature point location algorithm by ASM(active shape model).The results state that the effect of the system of real-time detection and tracking of facial feature point location is obvious,the algorithm can be used as the basis of expression analysis,emotion computing,the development of video face recognition.

  3. Face detection in C#

    OpenAIRE

    Soto Entrena, Roberto Javier

    2012-01-01

    Actualmente la detección del rostro humano es un tema difícil debido a varios parámetros implicados. Llega a ser de interés cada vez mayor en diversos campos de aplicaciones como en la identificación personal, la interface hombre-máquina, etc. La mayoría de las imágenes del rostro contienen un fondo que se debe eliminar/discriminar para poder así detectar el rostro humano. Así, este proyecto trata el diseño y la implementación de un sistema de detección facial humana, como el primer paso e...

  4. Development of Human Face Detection System Based on Real-time Camera Image%摄像头实时图像人脸检测系统开发

    Institute of Scientific and Technical Information of China (English)

    孙雅琪; 刘羽

    2013-01-01

    人脸检测是计算机视觉领域中一个重要的研究热点,也是人脸识别、表情识别等研究的基础.论文首先通过截取摄像头实时图像,然后通过转换彩色空间、人脸肤色建模、图像处理和人脸定位算法实现了人脸检测功能.详细介绍了基于摄像头的人脸图像采集开发和人脸检测等主要步骤,并由此开发了摄像头实时图像的人脸检测系统.试验结果表明,论文提出的方法是可行的.%Human face detection is an important research in the field of computer vision.It also is a basic research of face recognition and expression recognition etc.Firstly,the camera real-time image is captured,and then the face detection function is realized through conversing of color space,skin color model,image processing and face location algorithm are built.The main steps of developing the face images acquisition based on camera and face detection are introduced in detail.At last,the face detection system based on real-time camera image is developed.The test results show that,the proposed method is feasible.

  5. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300

    Directory of Open Access Journals (Sweden)

    Lawrence A. Farwell

    2014-12-01

    Full Text Available A classification concealed information test (CIT used the brain fingerprinting method of applying P300 event-related potential (ERP in detecting information that is 1 acquired in real life and 2 unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to 3 types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified. We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP? versus comparison CIT (Does a probe produce a larger ERP than an irrelevant? using P300 plus the late negative component (LNP; together, P300-MERMER. Comparison CIT produced a significantly higher error rate (20% and lower statistical confidences -- mean 67%; information-absent mean was 28.9%, less than chance (50%. We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational

  6. Contextual Information Retrieval based on Algorithmic Information Theory and Statistical Outlier Detection

    CERN Document Server

    Martinez, Rafael; Rodriguez, Francisco de Borja; Camacho, David

    2007-01-01

    The main contribution of this paper is to design an Information Retrieval (IR) technique based on Algorithmic Information Theory (using the Normalized Compression Distance- NCD), statistical techniques (outliers), and novel organization of data base structure. The paper shows how they can be integrated to retrieve information from generic databases using long (text-based) queries. Two important problems are analyzed in the paper. On the one hand, how to detect "false positives" when the distance among the documents is very low and there is actual similarity. On the other hand, we propose a way to structure a document database which similarities distance estimation depends on the length of the selected text. Finally, the experimental evaluations that have been carried out to study previous problems are shown.

  7. 基于改进的AdaBoost人脸检测算法的研究%Research on Face Detection Based on Improved AdaBoost Algorithm

    Institute of Scientific and Technical Information of China (English)

    丁知平

    2013-01-01

    Face detection is a fundamental research theme in the topic of computer vision ,and it has a broad application in many fields such as video surveillance,automatic face recognition,etc. To improve the detection speed of AdaBoost based face detection algorithm, proposes a rapid im-proved AdaBoost based face detection algorithm. Experiments shows that, compared with the current algorithm less features are selected in the inspection, and a high detection correct rate is achieved with the proposed algorithm.%  人脸检测是计算机视觉领域的基础研究,在视频监控、自动人脸识别等领域有着重要应用价值。针对传统的AdaBoost算法用于人脸检测时需要的特征数目多、检测速度慢的问题,提出一种基于改进的AdaBoost人脸检测算法。实验结果表明,相对于传统的AdaBoost人脸检测算法,该算法使用较少的特征即可达到较高的检测准确率,检测速度得到显著提高。

  8. Query-Based Outlier Detection in Heterogeneous Information Networks

    Science.gov (United States)

    Kuck, Jonathan; Zhuang, Honglei; Yan, Xifeng; Cam, Hasan; Han, Jiawei

    2015-01-01

    Outlier or anomaly detection in large data sets is a fundamental task in data science, with broad applications. However, in real data sets with high-dimensional space, most outliers are hidden in certain dimensional combinations and are relative to a user’s search space and interest. It is often more effective to give power to users and allow them to specify outlier queries flexibly, and the system will then process such mining queries efficiently. In this study, we introduce the concept of query-based outlier in heterogeneous information networks, design a query language to facilitate users to specify such queries flexibly, define a good outlier measure in heterogeneous networks, and study how to process outlier queries efficiently in large data sets. Our experiments on real data sets show that following such a methodology, interesting outliers can be defined and uncovered flexibly and effectively in large heterogeneous networks. PMID:27064397

  9. Face Tracking in the Compressed Domain

    Directory of Open Access Journals (Sweden)

    Fonseca Pedro Miguel

    2006-01-01

    Full Text Available A compressed domain generic object tracking algorithm offers, in combination with a face detection algorithm, a low-compu-tational-cost solution to the problem of detecting and locating faces in frames of compressed video sequences (such as MPEG-1 or MPEG-2. Objects such as faces can thus be tracked through a compressed video stream using motion information provided by existing forward and backward motion vectors. The described solution requires only low computational resources on CE devices and offers at one and the same time sufficiently good location rates.

  10. Face Tracking in the Compressed Domain

    Science.gov (United States)

    Fonseca, Pedro Miguel; Nesvadba, Jan

    2006-12-01

    A compressed domain generic object tracking algorithm offers, in combination with a face detection algorithm, a low-compu-tational-cost solution to the problem of detecting and locating faces in frames of compressed video sequences (such as MPEG-1 or MPEG-2). Objects such as faces can thus be tracked through a compressed video stream using motion information provided by existing forward and backward motion vectors. The described solution requires only low computational resources on CE devices and offers at one and the same time sufficiently good location rates.

  11. Face Detection Method Based on Semi-supervised Clustering%基于半监督聚类的人脸检测方法

    Institute of Scientific and Technical Information of China (English)

    王燕; 蒋正午

    2012-01-01

    The paper proposes a method of face detection combined color of skin with continuous AdaBoost algorithm. In order to establish skin color model, this paper takes advantage of semi-supervised strategy to guide skin color clustering, and it also proposes a new algorithm SKDK in the process of clustering, skin color model can be established by the probability statistics distribution characteristics of each pixel cluster. On this basis, mathematical morphology of knowledge is used to handle image and find face candidate, which is the input of continuous AdaBoost classifier for final face detection. Experimental results prove that face detection ability of the method is superior to that directly using continuous AdaBoost method for face detection especially in multi-face situation.%将肤色与连续AdaBoost算法相结合进行人脸检测,并引入半监督策略指导肤色聚类从而建立肤色模型.在肤色聚类过程中,提出一种基于半监督的SKDK算法引导肤色聚类,依据各个像素簇的概率统计分布特性得到肤色模型.在此基础上利用数学形态学等知识对图像进行处理,得到人脸候选区域,将其作为连续AdaBoost分类器的输入进行人脸检测.实验结果表明,在多人脸的场景下,该方法的检测效果优于直接使用连续AdaBoost方法进行人脸检测的检测效果.

  12. Designing and Implementation of Real Time Face Detecting Module%实时人脸检测模块的设计和实现

    Institute of Scientific and Technical Information of China (English)

    王文武; 王华昌

    2011-01-01

    在达芬奇系列处理器TMS320DM6437平台上,利用Canny边沿检测算子,排除视频中大量非人脸部分,对可能为人脸的区域,运行Adaboost算法,完成人脸检测,实现一个高速的人脸检测模块.实验结果表明,该模块检测结果准确、运行稳定且高效.%On the platform of DaVinci processor TMS320DM6437, many of non-face blocks are rejected with the help of Canny operator.For the rest image, face detecting is achieved by the Adaboost algorithm, then a fast and real time face detecting module is implemented.Experiments indicate the module is efficient and stable in face detection.The detection rate is close to the state of the arts.

  13. Design of Information System for Milking Dairy Cattle and Detection of Mastitis

    OpenAIRE

    Ming-Chih Chen; Chien-Hsing Chen; Chong-Yu Siang

    2014-01-01

    A novel information system for detecting mastitis in dairy cattle and managing their milking processes in the milking parlor is designed. The system comprises three major subsystems—the mastitis detection device, the information display device, and the cloud database. The mastitis detection device can detect and evaluate the degree of mastitis immediately before the milking operations are carried out. The information display device shows information on the health of the dairy cattle obtained ...

  14. Du rapport entre la négation et l’impolitesse dans les Exchanges d’informations face a face en français

    Directory of Open Access Journals (Sweden)

    Ruth de OLIVEIRA

    2015-12-01

    Full Text Available Dans cette contribution, nous nous proposons d’aborder la question de l’impolitesse linguistique en français dans le cadre de la conversation ordinaire et plus précisément dans l’échange d’informations. De par son caractère éminemment fonctionnel, l’échange d’informations constitue un lieu privilégié d’observation des rapports entre langue et culture. À travers une étude de mécanismes interactionnels (i.e. question-réponse, notamment de la séquence/réponse négative récurrente je ne sais pas moi, nous nous demanderons ce qui distingue cette construction-là de celle-ci je ne sais pas; pourquoi et dans quelles situations, ou à quel moment de l’interaction, le locuteur emploie celle-là plutôt que celle-ci ou vice-versa ? Quels sont les effets socio interactifs produits ? Qu’en ressort-il au niveau du profil du locuteur ? Les éléments de réponse que nous apporterons à ces questions s’appuient sur une approche théorique et méthodologique combinatoire des apports de la polyphonie linguistique, l’analyse conversationnelle, la grammaire des émotions et le concept d’impolitesse.

  15. Phylogenetically informed logic relationships improve detection of biological network organization

    Science.gov (United States)

    2011-01-01

    Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

  16. 复杂光照环境下视频人脸序列的自动检测方法%Automatic Face Detection in Video Sequences in Complex Lighting Environments

    Institute of Scientific and Technical Information of China (English)

    谢倩茹; 耿国华

    2011-01-01

    Auto human face detection from video sequences is the base of studies for human face recognition and tracking. This paper proposed an efficient and robust method to detect face in vido sequences. The key step of this work is to use the technique of image enhancement to alleviate the impact of human face detection caused by variation illumination such as local shadow and highlight. The approach firstly strengthens the edge and detail information of images by means of high-frequency enhanced filtering and uses histogram-based technique to adjust the brightness of the image, then applies the Gabor wavelet to extract features of images,finally trains samples using the adaboost algorithm and complete face detection. The experimental results show that the approach can detect human face accurately under different lighting conditions.%基于视频序列人脸自动检测是人脸跟踪、识别等研究的基础.提出了一种结合图像增强技术、gabor特征变换和adaboost算法的视频序列人脸检测方法,其主要思想是使用图像增强技术对图像进行光照补偿,减轻不同的光照条件(如局部的阴影和高亮等)对检测结果的影响.该方法首先通过高频增强滤波强化图像的边缘和细节信息,用基于直方图的技术采调节图像的亮度,然后应用gabor小波变换进行特征抽取,最后采用adaboost方法训练样本,完成人脸的检测.实验表明,该方法能够在不同的光照条件下准确检测出人脸,显示出较强的鲁棒性.

  17. Improvement of AdaBoost Face Detection Algorithm Based on Skin Color Detection%基于肤色检测的AdaBoost人脸检测算法改进

    Institute of Scientific and Technical Information of China (English)

    李明瑞; 傅明; 曹敦

    2012-01-01

    AdaBoost人脸检测算法用于嵌入式实时高清视频时检测速度缓慢.为此,提出一种改进的人脸检测算法.对图像做肤色检测,将检测到的区域进行形态学处理,并作为感兴趣区域,完成AdaBoost人脸检测,以得到检测结果.实验结果表明,该算法在嵌入式系统上运行稳定,能提高检测速度和检测正确率.%An improved face detection algorithm is proposed to solve the problem of slow speed in real-time HD video face detection. This paper does face detection on high color image, gets the morphology processing detection results, sets the Region of Interest(ROI), and does AdaBoost face detection on ROI to get the result. Experimental results show that the algorithm can steadily operate on embedded systems, and improve the detection accuracy and the detection speed.

  18. Detection of morphological changes in cliff face surrounding a waterfall using terrestrial laser scanning and unmanned aerial system

    Science.gov (United States)

    Hayakawa, Yuichi S.; Obanawa, Hiroyuki

    2015-04-01

    Waterfall or bedrock knickpoint appears as an erosional front in bedrock rivers forming deep v-shaped valley downstream. Following the rapid fluvial erosion of waterfall, rockfalls and gravita-tional collapses often occur in surrounding steep cliffs. Although morphological changes of such steep cliffs are sometimes visually observed, quantitative and precise measurements of their spatio-temporal distribution have been limited due to the difficulties in direct access to such cliffs if with classical measurement methods. However, for the clarification of geomorphological processes oc-curring in the cliffs, multi-temporal mapping of the cliff face at a high resolution is necessary. Re-mote sensing approaches are therefore suitable for the topographic measurements and detection of changes in such inaccessible cliffs. To achieve accurate topographic mapping of cliffs around a wa-terfall, here we perform multi-temporal terrestrial laser scanning (TLS), as well as structure-from-motion multi-view stereo (SfM-MVS) photogrammetry based on unmanned aerial system (UAS). The study site is Kegon Falls in central Japan, having a vertical drop of surface water from top of its overhanging cliff, as well as groundwater outflows from its lower portions. The bedrock is composed of alternate layers of andesite lava and conglomerates. Minor rockfalls in the cliffs are often ob-served by local people. The latest major rockfall occurred in 1986, causing ca. 8-m upstream propa-gation of the waterfall lip. This provides a good opportunity to examine the changes in the surround-ing cliffs following the waterfall recession. Multi-time point clouds were obtained by TLS measure-ment over years, and the three-dimensional changes of the rock surface were detected, uncovering the locus of small rockfalls and gully developments. Erosion seems particularly frequent in relatively weak the conglomerates layer, whereas small rockfalls seems to have occurred in the andesite layers. Also, shadows in the

  19. Detection of non-self-correcting nature of information cascade

    CERN Document Server

    Mori, Shintaro; Hisakado, Masato; Takahashi, Taiki

    2015-01-01

    We propose a method of detecting non-self-correcting information cascades in experiments in which subjects choose an option sequentially by observing the choices of previous subjects. The method uses the correlation function $C(t)$ between the first and the $t+1$-th subject's choices. $C(t)$ measures the strength of the domino effect, and the limit value $c\\equiv \\lim_{t\\to \\infty}C(t)$ determines whether the domino effect lasts forever $(c>0)$ or not $(c=0)$. The condition $c>0$ is an adequate condition for a non-self-correcting system, and the probability that the majority's choice remains wrong in the limit $t\\to \\infty$ is positive. We apply the method to data from two experiments in which $T$ subjects answered two-choice questions: (i) general knowledge questions ($T_{avg}=60$) and (ii) urn-choice questions ($T=63$). We find $c>0$ for difficult questions in (i) and all cases in (ii), and the systems are not self-correcting.

  20. Pornographic information of Internet views detection method based on the connected areas

    Science.gov (United States)

    Wang, Huibai; Fan, Ajie

    2017-01-01

    Nowadays online porn video broadcasting and downloading is very popular. In view of the widespread phenomenon of Internet pornography, this paper proposed a new method of pornographic video detection based on connected areas. Firstly, decode the video into a serious of static images and detect skin color on the extracted key frames. If the area of skin color reaches a certain threshold, use the AdaBoost algorithm to detect the human face. Judge the connectivity of the human face and the large area of skin color to determine whether detect the sensitive area finally. The experimental results show that the method can effectively remove the non-pornographic videos contain human who wear less. This method can improve the efficiency and reduce the workload of detection.

  1. Face Detection System Based on PCANet-RF%基于PCANet-RF的人脸检测系统

    Institute of Scientific and Technical Information of China (English)

    张丹丹; 李雷

    2016-01-01

    A face detection system was presented based on a simple convolutional neural network. Feature extraction of image is usually complicated which needs much pretreatment. Deep learning reduces pretreatment,such as convolutional neural network,but it needs more time of training and requires certain ability to adjust the parameters,which contrary to the original intention. What is more,classification capability and result of convolutional neural network is not well. Combination of above,the PCANet for feature extraction is applied to lower the ability to adjust the parameters and Random Forest for image classification is used to improve the recognition rate. This method has got a recognition rate as 99%. Experiments has confirmed that PCANet-RF can be successfully used in image classification.%文中提出一种基于简化卷积神经网络的特征提取方法的人脸检测算法。图像的特征提取较为复杂,需要大量的预处理。深度学习减少了特征提取的工作量,卷积神经网络就是这方面应用的典型例子。但是,卷积神经网络参数训练时间过长,调参主要依靠实验人员的调参技巧,这大大降低了卷积神经网络应用的初衷。此外,卷积神经网络的分类能力较弱,分类效果并不好。综合以上两点,文中应用一种简化的深度学习方法PCANet(主成分分析网络)提取图像特征,降低对调参的要求,同时用RF(随机森林)对其进行后期分类,提高人脸识别分类效果。实验结果表明,提出的方法对人脸识别率可以达到99%,进一步证明了PCANet在特征提取方面的优越性。

  2. Research of Face Detection module Base on OpenCV in Android platform%Android平台下OpenCV的人脸检测模块的实现

    Institute of Scientific and Technical Information of China (English)

    袁晨; 李雪源; 姜代红

    2014-01-01

    This paper proposesa a method the face detection based on OpenCV(OpenCV Source Computer Vision) in Android platform.It is introducing the implementation process of this application and Adaboost Algorithm,The concrete steps of using JNI(Jave Native Interface) to call OpenCV function and the NDK compiler generated dynamic library. The experimental results show the face detection of the Android platform function is good.%本文提出了使用OpenCV在Android平台下实现人脸检测的方法。介绍利用Android实现应用程序过程及Adaboost算法,同时详细阐述了使用JNI调用OpenCV有关函数和NDK编译生成动态库的具体步骤。实验结果表明此Android平台下人脸检测功能性能良好。

  3. Comparison of face Recognition Algorithms on Dummy Faces

    Directory of Open Access Journals (Sweden)

    Aruni Singh

    2012-09-01

    Full Text Available In the age of rising crime face recognition is enormously important in the contexts of computer vision, psychology, surveillance, fraud detection, pattern recognition, neural network, content based video processing, etc. Face is a non intrusive strong biometrics for identification and hence criminals always try to hide their facial organs by different artificial means such as plastic surgery, disguise and dummy. The availability of a comprehensive face database is crucial to test the performance of these face recognition algorithms. However, while existing publicly-available face databases contain face images with a wide variety of poses, illumination, gestures and face occlusions but there is no dummy face database is available in public domain. The contributions of this research paper are: i Preparation of dummy face database of 110 subjects ii Comparison of some texture based, feature based and holistic face recognition algorithms on that dummy face database, iii Critical analysis of these types of algorithms on dummy face database.

  4. Intersensory Redundancy Hinders Face Discrimination in Preschool Children: Evidence for Visual Facilitation

    Science.gov (United States)

    Bahrick, Lorraine E.; Krogh-Jespersen, Sheila; Argumosa, Melissa A.; Lopez, Hassel

    2014-01-01

    Although infants and children show impressive face-processing skills, little research has focused on the conditions that facilitate versus impair face perception. According to the intersensory redundancy hypothesis (IRH), face discrimination, which relies on detection of visual featural information, should be impaired in the context of…

  5. Face haulage equipment failure analysis. Volume I. Technical information and conclusions. Final technical report as of November 30, 1980

    Energy Technology Data Exchange (ETDEWEB)

    Patterson, W.N.; Orona, F.

    1980-11-01

    Face haulage equipment used in conjunction with continuous miners (shuttle cars, diesel haulers, battery scoops, and bridge conveyors) was investigated by recording section delay reports for computer analysis to determine the effect of haulage equipment failures and downtime on productivity, pinpoint the causes of machine failures and downtime, and develop the possible design and operational changes required to reduce machine failures and downtime and increase section productivity. For the mobile vehicle type of haulage (shuttle car, diesel hauler, and battery scoop) failure of one unit in multiple unit haulage operations would not normally stop section production. Bridge conveyors as a haulage system provide continuous haulage of section production but when any part of the bridge system fails, the section production is stopped. In the course of this program, it was determined through the use of daily section shift reports on 200 machines that face haulage equipment is responsible for about 40 to 56 minutes of lost section production time per shift. The most prevalent failure for shuttle cars was found to be the trailing cable umbilical. Bridge conveyors had the most trouble with the conveyor subsystem. Discussions of these and other recorded failures are developed with possible solutions outlined for future implementation. This report only covers the face haulage element of the continuous miner system. Companion reports were developed for the continuous miner and roof bolter elements under separate task orders.

  6. Community detection with consideration of non-topological information

    Institute of Scientific and Technical Information of China (English)

    Zou Sheng-Rong; Peng Yu-Jing; Liu Ai-Fen; Xu Xiu-Lian; He Da-Ren

    2011-01-01

    In a network described by a graph, only topological structure information is considered to determine how the nodes are connected by edges. Non-topological information denotes that which cannot be determined directly from topological information. This paper shows, by a simple example where scientists in three research groups and one external group form four communities, that in some real world networks non-topological information (in this example,the research group affiliation) dominates community division. If the information has some influence on the network topological structure, the question arises as to how to find a suitable algorithm to identify the communities based only on the network topology. We show that weighted Newman algorithm may be the best choice for this example. We believe that this idea is general for real-world complex networks.

  7. Conjunction Faces Alter Confidence-Accuracy Relations for Old Faces

    Science.gov (United States)

    Reinitz, Mark Tippens; Loftus, Geoffrey R.

    2017-01-01

    The authors used a state-trace methodology to investigate the informational dimensions used to recognize old and conjunction faces (made by combining parts of separately studied faces). Participants in 3 experiments saw faces presented for 1 s each. They then received a recognition test; faces were presented for varying brief durations and…

  8. New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs

    NARCIS (Netherlands)

    Schalekamp, S.; Ginneken, B. van; Heggelman, B.; Imhof-Tas, M.W.; Somers, I.; Brink, M.; Spee, M.; Schaefer-Prokop, C.M.; Karssemeijer, N.

    2014-01-01

    Objective: To investigate two new methods of using computer-aided detection (CAD) system information for the detection of lung nodules on chest radiographs. We evaluated an interactive CAD application and an independent combination of radiologists and CAD scores. Methods: 300 posteroanterior and lat

  9. Information leakage and steganography: detecting and blocking covert channels

    OpenAIRE

    Blasco Alís, Jorge

    2012-01-01

    This PhD Thesis explores the threat of information theft perpetrated by malicious insiders. As opposite to outsiders, insiders have access to information assets belonging the organization, know the organization infrastructure and more importantly, know the value of the different assets the organization holds. The risk created by malicious insiders have led both the research community and commercial providers to spend efforts on creating mechanisms and solutions to reduce it. However, the lack...

  10. Face pain

    Science.gov (United States)

    ... begin in other places in the body. Abscessed tooth (ongoing throbbing pain on one side of the lower face that ... face, and aggravated by eating. Call a dentist. Pain is persistent, ... by other unexplained symptoms. Call your primary provider.

  11. Change Detection Algorithms for Information Assurance of Computer Networks

    Science.gov (United States)

    2002-01-01

    LIST OF FIGURES 2.1 Code Red I Infection (source CAIDA ) . . . . . . . . . . . . . . . . . 17 2.2 Number of probes due to the w32.Leave worm...16 Figure 2.1: Code Red I Infection (source CAIDA ) 2.3.2 Detection of an exponential signal in noise The i.i.d. assumption of the observations after

  12. Detection, information fusion, and temporal processing for intelligence in recognition

    Energy Technology Data Exchange (ETDEWEB)

    Casasent, D. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    1996-12-31

    The use of intelligence in vision recognition uses many different techniques or tools. This presentation discusses several of these techniques for recognition. The recognition process is generally separated into several steps or stages when implemented in hardware, e.g. detection, segmentation and enhancement, and recognition. Several new distortion-invariant filters, biologically-inspired Gabor wavelet filter techniques, and morphological operations that have been found very useful for detection and clutter rejection are discussed. These are all shift-invariant operations that allow multiple object regions of interest in a scene to be located in parallel. We also discuss new algorithm fusion concepts by which the results from different detection algorithms are combined to reduce detection false alarms; these fusion methods utilize hierarchical processing and fuzzy logic concepts. We have found this to be most necessary, since no single detection algorithm is best for all cases. For the final recognition stage, we describe a new method of representing all distorted versions of different classes of objects and determining the object class and pose that most closely matches that of a given input. Besides being efficient in terms of storage and on-line computations required, it overcomes many of the problems that other classifiers have in terms of the required training set size, poor generalization with many hidden layer neurons, etc. It is also attractive in its ability to reject input regions as clutter (non-objects) and to learn new object descriptions. We also discuss its use in processing a temporal sequence of input images of the contents of each local region of interest. We note how this leads to robust results in which estimation efforts in individual frames can be overcome. This seems very practical, since in many scenarios a decision need not be made after only one frame of data, since subsequent frames of data enter immediately in sequence.

  13. Spectral information for detection of acoustic time to arrival

    DEFF Research Database (Denmark)

    Gordon, Michael S.; Russo, Frank A.; MacDonald, Ewen

    2013-01-01

    The exponential increase of intensity for an approaching sound source provides salient information for a listener to make judgments of time to arrival (TTA). Specifically, a listener will experience a greater rate of increasing intensity for higher than for lower frequencies during a sound source......’s approach. To examine the relative importance of this spectral information, listeners were asked to make judgments about the arrival times of nine 1-octave-band sound sources (the bands were consecutive, nonoverlapping single octaves, ranging from 40–80 Hz to ~10–20 kHz). As is typical in TTA tasks...

  14. Sociolinguistically Informed Natural Language Processing: Automating Irony Detection

    Science.gov (United States)

    2015-04-13

    representation for verbal irony detection. Indeed, sociolinguistic theories of verbal irony imply that a 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND... social media REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S ACRONYM(S) ARO 8. PERFORMING ORGANIZATION...contrast to most text classification problems, word counts and syntactic features alone do not constitute an adequate representation for verbal irony

  15. Chromatic Information and Feature Detection in Fast Visual Analysis

    Science.gov (United States)

    Del Viva, Maria M.; Punzi, Giovanni; Shevell, Steven K.

    2016-01-01

    The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-and-white movies provide compelling representations of real world scenes. Also, the contrast sensitivity of color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. We conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in. PMID:27478891

  16. Spatial anomaly detection in sensor networks using neighborhood information

    NARCIS (Netherlands)

    Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

    2016-01-01

    The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capabil- ity, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

  17. Design of face detection module based on OpenCV in Android system%Android系统下OpenCV的人脸检测模块的设计

    Institute of Scientific and Technical Information of China (English)

    公衍宇; 郭琦; 于超

    2012-01-01

    针对解决OpenCV人脸检测模块在Android平台编译和移植的问题,提出一种利用JNI技术(Java Native Interface)调用OpenCV以及采用Android NDK(Native Development Kit)生成共享库的目标检测方法。文中从分析利用Android NDK编译Android平台所需要的OpenCV静态库的问题入手,详细阐述了利用JNI调用OpenCV相关函数的具体步骤。经过多次试验,证明该人脸检测模块的平均检测时间为1 280 ms,具有较高的检测速度和检测精度。%Aiming at the problem of the OpenCV face detection module compiling and transplant in the Android platform,a JNI technology(Java Native-Interface) call OpenCV and Android NDK(Native Development Kit) to generate a shared library object detection method is proposed.Starting from analysis of compile the OpenCV static libraries needed by Android platform use Android NDK,Implementation steps of using JNI to call the relative functions of OpenCV are explained in detail.After numerous experiments to prove that the face detection module,the average detection time 1 280 ms,a high detection speed and detection accuracy.

  18. Information Seeking Behavior in Blind People of Iran : a Survey based on Various Experiences faced by them

    Directory of Open Access Journals (Sweden)

    Hasan Siamian

    2016-12-01

    Full Text Available Access to information and its dissemination for the planning of health and social care is essential. While information is not always available as per the needs of the blind people, thus the public libraries and information centers led for meeting the information needs culture and proper knowledge. The study was based on a Descriptive-analytic method in which we included 384 blind people of both the sex selected by the multi-clustering method from 10 provinces of Iran. Health information of the subjects was collect through a researcher-based questionnaire. Results showed that religion, occupations, and access to healthy living, were the first top priority of blind people for meeting information needs in three cultural; social in addition, health forms. The blind people try to look for information on a daily basis and seeking up-to-date technologies. They are most used to audio media rather than any other media to access, utilise information, and rarely used new technologies. Unlike normal people, blind people have high expectations from the library. An attempt has also been taken to present a new model.

  19. A Heuristic Clustering Algorithm for Intrusion Detection Based on Information Entropy

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper studied on the clustering problem for intrusion detection with the theory of information entropy, it was put forward that the clustering problem for exact intrusion detection based on information entropy is NP-complete, therefore, the heuristic algorithm to solve the clustering problem for intrusion detection was designed, this algorithm has the characteristic of incremental development, it can deal with the database with large connection records from the internet.

  20. 人脸检测算法的改进与仿真研究%Simulation on Face Detection Based on Improved Adaboost Algorithm

    Institute of Scientific and Technical Information of China (English)

    陈园园

    2011-01-01

    Improving the accuracy of face detection algorithm, the traditional adaBoost algorithms have degradation phenomenon and low recognition rate problem, this paper put forward a face detection method based on improved adaBoost algorithm. Sample weights are updated dynamically by false positive, weights are prevented increasing excessively by adjusting regulatory factors, and classifier recognition ability is improved by decision threshold based on the traditional adaBoost algorithm. The method is tested by the CMU+MIT face image database, the results show that the improved adaboost Algorithm solves the traditional adaBoost algorithm's degeneration problem, it can reduce false alarm rate while holding a high detection rate.%研究提高人脸检测算法准确率问题,针对传统AdaBoost算法在人脸检测训练过程中出现的退化现象和识别率低的问题,提出了一种改进的AdaBoost人脸检测方法.在传统AdaBoost算法的基础上,通过假阳性对样本的权值进行动态更新,调节因子对调节权值进行修正防止其过分增大,通过判决阈值改善分类器识别能力.在CMU+MIT人脸库上对算法进行了实现,实验结果表明,改进的AdaBoost算法较好地解决了传统AdaBoost算法所出现的退化问题,在保证识别率的同时降低了误检率.

  1. Digital image modification detection using color information and its histograms.

    Science.gov (United States)

    Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

    2016-09-01

    The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring.

  2. Multi-sources information fusion algorithm in airborne detection systems

    Institute of Scientific and Technical Information of China (English)

    Yang Yan; Jing Zhanrong; Gao Tian; Wang Huilong

    2007-01-01

    To aim at the multimode character of the data from the airplane detecting system, the paper combines DempsterSharer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode data fusion algorithm. The algorithm adopts a prorated algorithm relate to the incertitude evaluation to convert the probability evaluation into the precognition probability in an identity frame, and ensures the adaptability of different data from different source to the mixed system. To guarantee real time fusion, a combination of time domain fusion and space domain fusion is established, this not only assure the fusion of data chain in different time of the same sensor, but also the data fusion from different sensors distributed in different platforms and the data fusion among different modes. The feasibility and practicability are approved through computer simulation.

  3. Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa

    Science.gov (United States)

    Mavridis, Nikolaos; Kazmi, Wajahat; Toulis, Panos

    The "friendship" relation, a social relation among individuals, is one of the primary relations modeled in some of the world's largest online social networking sites, such as "FaceBook." On the other hand, the "co-occurrence" relation, as a relation among faces appearing in pictures, is one that is easily detectable using modern face detection techniques. These two relations, though appearing in different realms (social vs. visual sensory), have a strong correlation: faces that co-occur in photos often belong to individuals who are friends. Using real-world data gathered from "Facebook," which were gathered as part of the "FaceBots" project, the world's first physical face-recognizing and conversing robot that can utilize and publish information on "Facebook" was established. We present here methods as well as results for utilizing this correlation in both directions. Both algorithms for utilizing knowledge of the social context for faster and better face recognition are given, as well as algorithms for estimating the friendship network of a number of individuals given photos containing their faces. The results are quite encouraging. In the primary example, doubling of the recognition accuracy as well as a sixfold improvement in speed is demonstrated. Various improvements, interesting statistics, as well as an empirical investigation leading to predictions of scalability to much bigger data sets are discussed.

  4. Automatic detection of protected health information from clinic narratives.

    Science.gov (United States)

    Yang, Hui; Garibaldi, Jonathan M

    2015-12-01

    This paper presents a natural language processing (NLP) system that was designed to participate in the 2014 i2b2 de-identification challenge. The challenge task aims to identify and classify seven main Protected Health Information (PHI) categories and 25 associated sub-categories. A hybrid model was proposed which combines machine learning techniques with keyword-based and rule-based approaches to deal with the complexity inherent in PHI categories. Our proposed approaches exploit a rich set of linguistic features, both syntactic and word surface-oriented, which are further enriched by task-specific features and regular expression template patterns to characterize the semantics of various PHI categories. Our system achieved promising accuracy on the challenge test data with an overall micro-averaged F-measure of 93.6%, which was the winner of this de-identification challenge.

  5. Libor at crossroads: Stochastic switching detection using information theory quantifiers

    Science.gov (United States)

    Bariviera, Aurelio F.; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

    2016-07-01

    This paper studies the 28 time series of Libor rates, classified in seven maturities and four currencies), during the last 14 years. The analysis was performed using a novel technique in financial economics: the Complexity-Entropy Causality Plane. This planar representation allows the discrimination of different stochastic and chaotic regimes. Using a temporal analysis based on moving windows, this paper unveals an abnormal movement of Libor time series arround the period of the 2007 financial crisis. This alteration in the stochastic dynamics of Libor is contemporary of what press called "Libor scandal", i.e. the manipulation of interest rates carried out by several prime banks. We argue that our methodology is suitable as a market watch mechanism, as it makes visible the temporal redution in informational efficiency of the market.

  6. Botnet Detection Architecture Based on Heterogeneous Multi-sensor Information Fusion

    Directory of Open Access Journals (Sweden)

    HaiLong Wang

    2011-12-01

    Full Text Available As technology has been developed rapidly, botnet threats to the global cyber community are also increasing. And the botnet detection has recently become a major research topic in the field of network security. Most of the current detection approaches work only on the evidence from single information source, which can not hold all the traces of botnet and hardly achieve high accuracy. In this paper, a novel botnet detection architecture based on heterogeneous multi-sensor information fusion is proposed. The architecture is designed to carry out information integration in the three fusion levels of data, feature, and decision. As the core component, a feature extraction module is also elaborately designed. And an extended algorithm of the Dempster-Shafer (D-S theory is proved and adopted in decision fusion. Furthermore, a representative case is provided to illustrate that the detection architecture can effectively fuse the complicated information from various sensors, thus to achieve better detection effect.

  7. On the detection of thermohygrometric differences of Juniperus turbinata habitat between north and south faces in the island of El Hierro (Canary Islands)

    Science.gov (United States)

    Salva-Catarineu, Montserrat; Salvador-Franch, Ferran; Lopez-Bustins, Joan A.; Padrón-Padrón, Pedro A.; Cortés-Lucas, Amparo

    2016-04-01

    The current extent of Juniperus turbinata in the island of El Hierro is very small due to heavy exploitation for centuries. The recovery of its natural habitat has such a high environmental and scenic interest since this is a protected species in Europe. The study of the environmental factors that help or limit its recovery is indispensable. Our research project (JUNITUR) studied the populations of juniper woodlands in El Hierro from different environments. These environments are mainly determined by their altitude and exposure to north-easterly trade winds. The main objective of this study was to compare the thermohygrometric conditions of three juniper woodlands: La Dehesa (north-west face at 528 m a.s.l.), El Julan (south face at 996 m a.s.l.) and Sabinosa (north face at 258 m a.s.l.). They are located at different altitude and orientation in El Hierro and present different recovery rates. We used air sensor data loggers fixed to tree branches for recording hourly temperature and humidity data in the three study areas. We analysed daily data of three annual cycles (from September 2012 to August 2015). Similar thermohygrometric annual cycles among the three study areas were observed. We detected the largest differences in winter temperature and summer humidity between the north (to windward) (Sabinosa and La Dehesa) and south (to leeward) (El Julan) faces of the island. The juniper woodland with a highest recovery rate (El Julan) showed the most extreme temperature conditions in both winter and summer seasons. The results of this project might contribute to the knowledge of the juniper bioclimatology in El Hierro, where there is the biggest population of Juniperus turbinata throughout the Canary Islands.

  8. Design of Information System for Milking Dairy Cattle and Detection of Mastitis

    Directory of Open Access Journals (Sweden)

    Ming-Chih Chen

    2014-01-01

    Full Text Available A novel information system for detecting mastitis in dairy cattle and managing their milking processes in the milking parlor is designed. The system comprises three major subsystems—the mastitis detection device, the information display device, and the cloud database. The mastitis detection device can detect and evaluate the degree of mastitis immediately before the milking operations are carried out. The information display device shows information on the health of the dairy cattle obtained from a cloud database to manage the milk production of a dairy farm. Importantly, the proposed system utilizes a wireless sensor network (WSN with low power consumption that connects the information display device with the remote management system. Experimental results reveal that our proposed system can reduce the risk of milking cattle with mastitis and improve efficiency of milk production.

  9. 基于肤色HSV彩色模型下的人脸检测%Human Face Detection Based on HSV Model Space of Skin Color

    Institute of Scientific and Technical Information of China (English)

    刘萌

    2012-01-01

    每一种人种皮肤彩色分布在一个较窄的频带上。一般所用的RGB彩色模型对光线的亮暗程度比较敏感,而在HSV彩色模型中,色相H分量表示了图像的彩色信息,受到光线变化的影响缓慢。鉴于此,采用在HSV彩色模型下建立肤色模型,并对其进行训练,从而用训练后的模型对图像进行人脸检测。实验结果表明,提出的方法是有效而快速的。%The face skin color of each kind of race distributes in a narrow frequency band.RGB Model Space of Color is quite sensitive to the light degree,the chosen model,HSV Model Space of Color,is slowly changed by the light for the color information just expressed in the Hue component.The face skin color model is established under the HSV Model Space of Color in this paper.After training the model,it can examine the face area in one picture.Experimental results show that the proposed scheme is efficient and effective.

  10. Rapid Growth of Hispanic Populations in Western States. The Changing Face of the Rural West. WRDC Information Brief.

    Science.gov (United States)

    Berry, E. Helen; Kirschner, Annabel

    Between 1990 and 2000, the Hispanic population of the West increased by 54 percent, compared to a 13 percent increase for non-Hispanics. The Hispanic population now represents 25 percent of the West's population, up from 19 percent in 1990. This information brief describes the increase in Hispanic populations in the West from 1990 to 2000 and…

  11. The Changing Face of Librarianship in Papua New Guinea: Libraries for Life in the Papua New Guinea Information Society?

    Science.gov (United States)

    Obi, Margaret J.

    "Libraries for life" in Papua New Guinea today is not an impossible goal to strive for to achieve with today's new and old information and communication technologies. However, in order for this to happen, a number of questions will need to be asked. There are three that need immediate attention: (1) What is an "information…

  12. Face Detection and Feature Localization Based on GPU%基于GPU的人脸检测和特征点定位研究

    Institute of Scientific and Technical Information of China (English)

    张印; 董兰芳; 王建富

    2014-01-01

    Face analysis has been used more and more widely. However, with the wide-spread use of high definition video and images, the traditional program designed and implemented based on has been difficult to meet the requirement for time efficiency. To speed up the process, this paper presents an approach for Adaboost face detection with Haar-like features on the GPU which is regarded as massively parallel coprocessors through Nvidia's CUDA computation paradigm by two steps, parallelism processing based on window and classification. Also on the basis of face detection we propose a method for obtaining the initial model in a constant time, parallel implementing ASM algorithm. Compared with the implementation of the method in OpenCV based on CPU, the present method based on GPU achieves certain improvement in speed.%人脸分析相关应用越来越广泛,但随着高清视频影像的广泛使用,传统的基于CPU设计实现的程序已难以满足时效性要求。本文基于GPU平台实现了人脸检测和特征点定位的并行化。首先为了加速人脸检测过程,使用Nvidia的CUDA计算范式,通过"窗口级并行"和"分类器级并行"两步实现基于Haar特征的Adaboost算法;然后在人脸检测的基础上,提出一种在常量时间内获得初始模型的方法,并行实现ASM算法。与OpenCV中基于CPU的方法相比,基于GPU的本方法有一定速率提升。

  13. 复杂背景的快速人脸检测研究%Study on Fast Face Detection in Complex Background

    Institute of Scientific and Technical Information of China (English)

    杨稀; 杨帆; 李岩; 唐红梅

    2011-01-01

    Human faces need to be detected from the input images with complex background. To deal with the problem of massive adherent resemble skin color and color zones in color images, the algorithms including light and illumination compensation, skin color segmentation are both discussed. According to these, an improved method inosculating both the projection method and GVL is proposed, which can greatly reduce the number of skin color zones. Finally, a method of locating face by hair on a human head is proposed based on skin color segmentation and connected area segmentation. The experiment demonstrates that this method is competent to detect human faces of various expressions rotated within 45 angles in complex background quickly. This method can apply widely.%对于彩色图片,为了能够快速地在复杂背景中检测出多姿态人脸,解决肤色分割后大量粘连的类肤色和肤色区域等问题,在阐述光照和色彩补偿、肤色分割等算法的同时,提出了利用投影法和GLV法相结合的改进算法及利用人的头发来定位人脸的方法.实验结果表明,该方法能够在很短的时间内较为准确地检测出复杂环境中旋转不超过45°的多姿态人脸.因此,具有很好的应用前景.

  14. Identify-Isolate-Inform: A Tool for Initial Detection and Management of Measles Patients in the Emergency Department

    Directory of Open Access Journals (Sweden)

    Koenig, Kristi

    2015-03-01

    Full Text Available Measles (rubeola is a highly contagious airborne disease that was declared eliminated in the U.S. in the year 2000. Only sporadic U.S. cases and minor outbreaks occurred until the larger outbreak beginning in 2014 that has become a public health emergency. The “Identify-Isolate-Inform” tool will assist emergency physicians to be better prepared to detect and manage measles patients presenting to the emergency department. Measles typically presents with a prodrome of high fever, and cough/coryza/conjunctivitis, sometimes accompanied by the pathognomonic Koplik spots. Two to four days later, an erythematous maculopapular rash begins on the face and spreads down the body. Suspect patients must be immediately isolated with airborne precautions while awaiting laboratory confirmation of disease. Emergency physicians must rapidly inform the local public health department and hospital infection control personnel of suspected measles cases. [West J Emerg Med. 2015;16(2:212–219.

  15. Attribute selection using information gain for a fuzzy logic intrusion detection system

    Science.gov (United States)

    González-Pino, Jesús; Edmonds, Janica; Papa, Mauricio

    2006-04-01

    In the modern realm of information technology, data mining and fuzzy logic are often used as effective tools in the development of novel intrusion detection systems. This paper describes an intrusion detection system that effectively deploys both techniques and uses the concept of information gain to guide the attribute selection process. The advantage of this approach is that it provides a computationally efficient solution that helps reduce the overhead associated with the data mining process. Experimental results obtained with a prototype system implementation show promising opportunities for improving the overall detection performance of our intrusion detection system.

  16. Exploiting Multi-Look Information for Landmine Detection in Forward Looking Infrared Video

    Science.gov (United States)

    Malof, Jordan Milton

    Forward Looking Infrared (FLIR) cameras have recently been studied as a sensing modality for use in landmine detection systems. FLIR-based detection systems benefit from larger standoff distances and faster rates of advance than other sensing modalities, but they also present significant challenges for detection algorithm design. FLIR video typically yields multiple looks at each object in the scene, each from a different camera perspective. As a result each object in the scene appears in multiple video frames, and each time at a different shape and size. This presents questions about how best to utilize such information. Evidence in the literature suggests such multi-look information can be exploited to improve detection performance but, to date, there has been no controlled investigation of multi-look information in detection. Any results are further confounded because no precise definition exists for what constitutes multi-look information. This thesis addresses these problems by developing a precise mathematical definition of "a look", and how to quantify the multi-look content of video data. Controlled experiments are conducted to assess the impact of multi-look information on FLIR detection using several popular detection algorithms. Based on these results two novel video processing techniques are presented, the plan-view framework and the FLRX algorithm, to better exploit multi-look information. The results show that multi-look information can have a positive or negative impact on detection performance depending on how it is used. The results also show that the novel algorithms presented here are effective techniques for analyzing video and exploiting any multi-look information to improve detection performance.

  17. Distinct spatial scale sensitivities for early categorisation of Faces and Places: Neuromagnetic and Behavioural Findings

    Directory of Open Access Journals (Sweden)

    Bhuvanesh eAwasthi

    2013-03-01

    Full Text Available Research exploring the role of spatial frequencies in rapid stimulus detection and categorisation report flexible reliance on specific spatial frequency bands. Here, through a set of behavioural and magnetoencephalography (MEG experiments, we investigated the role of low spatial frequency (LSF(<8 cpf and high spatial frequency (HSF(>25 cpf information during the categorisation of faces and places. Reaction time measures revealed significantly faster categorisation of faces driven by LSF information, while rapid categorisation of places was facilitated by HSF information. The MEG study showed significantly earlier latency of the M170 component for LSF faces compared to HSF faces. Moreover, the M170 amplitude was larger for LSF faces than for LSF places, whereas the reverse pattern was evident for HSF faces and places. These results suggest that spatial frequency modulates the processing of category specific information for faces and places.

  18. AUTOMATIC URBAN ILLEGAL BUILDING DETECTION USING MULTI-TEMPORAL SATELLITE IMAGES AND GEOSPATIAL INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam

    2015-12-01

    Full Text Available With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  19. Weak signal detection based on the information fusion and chaotic oscillator.

    Science.gov (United States)

    Xiang, Xiuqiao; Shi, Baochang

    2010-03-01

    Based on the chaotic oscillator, a method for weak signal detection using information fusion technology is proposed in this paper. On the one hand, various methods are employed to the amplitude detection of the same weak periodic signal, then the detection outcomes are fused by the adaptive weighted fusion method. On the other hand, during the detection course, information entropy, statistic distance, and Walsh transform are, respectively, used in the state recognition of chaotic oscillator from the viewpoint of time domain or frequency domain, then the recognition results are fused by the k/l fusion method. Numerical results show that the proposed approach detects signal more precisely, identifies state more accurately, and represents information more completely compared with traditional methods.

  20. Changing the face of reference: adapting biomedical and health information services for the classroom, clinic, and beyond.

    Science.gov (United States)

    Tennant, Michele R; Auten, Beth; Botero, Cecilia E; Butson, Linda C; Edwards, Mary E; Garcia-Milian, Rolando; Lyon, Jennifer A; Norton, Hannah F

    2012-01-01

    This article describes how the reference department at a large academic health sciences library evolved to address the clinical and research information needs of the parent organization without losing its close connections to the classroom and curriculum. Closing the reference desk, moving to on-call and house call models, designing positions such as clinical research librarian and basic biomedical sciences librarian, finding alternative funding to grow the department, providing technology and training to facilitate librarians' work, and developing programming for and taking advice from library clients facilitated efforts to create a relevant presence and solidify the library's place in the university community.

  1. A special purpose knowledge-based face localization method

    Science.gov (United States)

    Hassanat, Ahmad; Jassim, Sabah

    2008-04-01

    This paper is concerned with face localization for visual speech recognition (VSR) system. Face detection and localization have got a great deal of attention in the last few years, because it is an essential pre-processing step in many techniques that handle or deal with faces, (e.g. age, face, gender, race and visual speech recognition). We shall present an efficient method for localization human's faces in video images captured on mobile constrained devices, under a wide variation in lighting conditions. We use a multiphase method that may include all or some of the following steps starting with image pre-processing, followed by a special purpose edge detection, then an image refinement step. The output image will be passed through a discrete wavelet decomposition procedure, and the computed LL sub-band at a certain level will be transformed into a binary image that will be scanned by using a special template to select a number of possible candidate locations. Finally, we fuse the scores from the wavelet step with scores determined by color information for the candidate location and employ a form of fuzzy logic to distinguish face from non-face locations. We shall present results of large number of experiments to demonstrate that the proposed face localization method is efficient and achieve high level of accuracy that outperforms existing general-purpose face detection methods.

  2. Multi—pose Color Face Recognition in a Complex Background

    Institute of Scientific and Technical Information of China (English)

    ZHUChangren; WANGRunsheng

    2003-01-01

    Face recognition has wider application fields. In recurrent references, most of the algorithms that deal with the face recognition in the static images are with simple background, and only used for ID picture recogni-tion. It is necessary to study the whole process of multi-pose face recognition in a clutter background. In this pa-per an automatic multi-pose face recognition system with multi-feature is proposed. It consists of several steps: face detection, detection and location of the face organs, feature extraction for recognition, recognition decision. In face de-tection the combination of skin-color and multi-verification which consists of the analysis of the shape, local organ fea-tures and head model is applied to improve the perfor-mance. In detection and location of the face organ feature points, with the analysis of multiple features and their pro-jections, the combination of an iterative search with a con-fidence function and template matching at the candidate points is adopted to improve the performance of accuracy and speed. In feature extraction for recognition, geome-try normalization based on three-point afflne transform is adopted to conserve the information to a maximum con-tent before the feature extraction of principal component analysis (PCA). In recognition decision, a hierarchical face model with the division of the face poses is introduced to reduce its retrieval space and thus to cut its time consump-tion. In addition, a fusion decision is applied to improve the face recognition performance. Also, pose recognition result can be got simultaneously. The new approach is ap-plied to 420 color images which consist of multi-pose faces with two visible eyes in a complex background, and the results are satisfactory.

  3. Phase synchronization of delta and theta oscillations increase during the detection of relevant lexical information

    Directory of Open Access Journals (Sweden)

    Enzo eBrunetti

    2013-06-01

    Full Text Available During monitoring of the discourse, the detection of the relevance of incoming lexical information could be critical for its incorporation to update mental representations in memory. Because, in these situations, the relevance for lexical information is defined by abstract rules that are maintained in memory, results critical to understand how an abstract level of knowledge maintained in mind mediates the detection of the lower-level semantic information. In the present study, we propose that neuronal oscillations participate in the detection of relevant lexical information, based on ‘kept in mind’ rules deriving from more abstract semantic information. We tested our hypothesis using an experimental paradigm that restricted the detection of relevance to inferences based on explicit information, thus controlling for ambiguities derived from implicit aspects. We used a categorization task, in which the semantic relevance was previously defined based on the congruency between a kept in mind category (abstract knowledge, and the lexical-semantic information presented. Our results show that during the detection of the relevant lexical information, phase synchronization of neuronal oscillations selectively increases in delta and theta frequency bands during the interval of semantic analysis. These increments were independent of the semantic category maintained in memory, had a temporal profile specific for each subject, and were mainly induced, as they had no effect on the evoked mean global field power. Also, recruitment of an increased number of pairs of electrodes was a robust observation during the detection of semantic contingent words. These results are consistent with the notion that the detection of relevant lexical information based on a particular semantic rule, could be mediated by increasing the global phase synchronization of neuronal oscillations, which may contribute to the recruitment of an extended number of cortical regions.

  4. Fire detection and incidents localization based on public information channels and social media

    Science.gov (United States)

    Thanos, Konstantinos-Georgios; Skroumpelou, Katerina; Rizogiannis, Konstantinos; Kyriazanos, Dimitris M.; Astyakopoulos, Alkiviadis; Thomopoulos, Stelios C. A.

    2017-05-01

    In this paper a solution is presented aiming to assist the early detection and localization of a fire incident by exploiting crowdsourcing and unofficial civilian online reports. It consists of two components: (a) the potential fire incident detection and (b) the visualization component. The first component comprises two modules that run in parallel and aim to collect reports posted on public platforms and conclude to potential fire incident locations. It collects the public reports, distinguishes reports that refer to a potential fire incident and store the corresponding information in a structured way. The second module aggregates all these stored reports and conclude to a probable fire location, based on the amount of reports per area, the time and location of these reports. In further the result is entered to a fusion module which combines it with information collected by sensors if available in order to provide a more accurate fire event detection capability. The visualization component is a fully - operational public information channel which provides accurate and up-to-date information about active and past fires, raises awareness about forest fires and the relevant hazards among citizens. The channel has visualization capabilities for presenting in an efficient way information regarding detected fire incidents fire expansion areas, and relevant information such as detecting sensors and reporting origin. The paper concludes with insight to current CONOPS end user with regards to the inclusion of the proposed solution to the current CONOPS of fire detection.

  5. Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

    Science.gov (United States)

    Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

    2014-10-15

    Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe.

  6. Driver's face detection based on Adaboost and skin color segmentation%基于Adaboost与肤色分割融合的驾驶员图像脸部检测

    Institute of Scientific and Technical Information of China (English)

    孙伟; 张为公; 张小瑞; 陈刚

    2009-01-01

    An improved face detection algorithm based on Adaboost is used to detect the face area possibly existing in the image, the detected area is extended properly and an face detection algorithm based on skin color segmentation in RGB space is used to locate the face again in the extended area, accurate fusion detection algorithm of face is achieved by the defined area coincidence degree and the geometric features of human face. Experiment results show the robustness and real-time performance of the algorithm.%采用改进的基于Adaboost的人脸检测算法检测出可能存在的初始人脸区域,适当扩大初始人脸区域的面积,在此基础上,利用基于RGB颜色空间的肤色分割算法进行人脸区域的二次定位,根据定义的脸部区域重合度和人脸几何特征实现对脸部区域的精确融合检测.实验结果证实了该算法的鲁棒性和实时性.

  7. A Wipe Transition Detection Approach Using Macroblock Type Information for MPEG Videos

    Institute of Scientific and Technical Information of China (English)

    WANG Jian; ZHOU Yuan-hua; ZHOU Lei

    2006-01-01

    A new wipe transition detection approach was proposed. By analyzing the spatial-temporal characteristics of an ideal wipe production model, the concept of wipe transition strip (TS) was introduced. The macroblock type information of P-frames is used to extract TS regions. An improved TS region accumulation technique is performed for detecting and verifying wipe transitions. The experimental results indicate that the proposed approach is capable of detecting various wipe transitions quickly and accurately.

  8. About Face

    Medline Plus

    Full Text Available Skip to Content Menu Closed (Tap to Open) Home Videos by Topic Videos by Type Search All ... What is AboutFace? Resources for Professionals Get Help Home Watch Videos by Topic Videos by Type Search ...

  9. About Face

    Medline Plus

    Full Text Available ... Home Videos by Topic Videos by Type Search All Videos PTSD Basics PTSD Treatment What is AboutFace? ... Watch Videos by Topic Videos by Type Search All Videos Learn More PTSD Basics PTSD Treatment What ...

  10. Estimation and detection information trade-off for x-ray system optimization

    Science.gov (United States)

    Cushing, Johnathan B.; Clarkson, Eric W.; Mandava, Sagar; Bilgin, Ali

    2016-05-01

    X-ray Computed Tomography (CT) systems perform complex imaging tasks to detect and estimate system parameters, such as a baggage imaging system performing threat detection and generating reconstructions. This leads to a desire to optimize both the detection and estimation performance of a system, but most metrics only focus on one of these aspects. When making design choices there is a need for a concise metric which considers both detection and estimation information parameters, and then provides the user with the collection of possible optimal outcomes. In this paper a graphical analysis of Estimation and Detection Information Trade-off (EDIT) will be explored. EDIT produces curves which allow for a decision to be made for system optimization based on design constraints and costs associated with estimation and detection. EDIT analyzes the system in the estimation information and detection information space where the user is free to pick their own method of calculating these measures. The user of EDIT can choose any desired figure of merit for detection information and estimation information then the EDIT curves will provide the collection of optimal outcomes. The paper will first look at two methods of creating EDIT curves. These curves can be calculated using a wide variety of systems and finding the optimal system by maximizing a figure of merit. EDIT could also be found as an upper bound of the information from a collection of system. These two methods allow for the user to choose a method of calculation which best fits the constraints of their actual system.

  11. A comparative study of face processing using scrambled faces

    OpenAIRE

    Taubert, Jessica; Aagten-Murphy, David; Parr, Lisa A.

    2012-01-01

    It is a widespread assumption that all primate species process faces in the same way because the species are closely related and they engage in similar social interactions. However, this approach ignores potentially interesting and informative differences that may exist between species. This paper describes a comparative study of holistic face processing. Twelve subjects (six chimpanzees Pan troglodytes and six rhesus monkeys Macaca mulatta) were trained to discriminate whole faces (faces wit...

  12. Face Forward

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Last November, surgeons in France successfully performed the world's first face transplant surgery. Ten days later, Chen Huanran in Beijing began soliciting patients who were ready to accept a face transplant, searching for China's first such patient through an advertisement on his website and other channels. Chen, chief orthopedic surgeon at the Plastic Surgery Hospital under the Chinese Academy of Medical Sciences, has conducted more than 300 transsexual operations and was considered one of the top com...

  13. Geophysical hazard detection from the working face. Open file report 28 Sep 77-24 Jun 80

    Energy Technology Data Exchange (ETDEWEB)

    Suhler, S.A.; Owen, T.E.; Duff, B.M.; Spiegel, R.J.

    1981-01-15

    The objective of this project was to define and demonstrate the feasibility of remotely sensing abandoned mine workings from underground. Geophysical probing techniques based upon electrical, seismic, and electromagnetic methods were evaluated with the result that the seismic method was determined to be the most favorable. Guided seismic wave propagation in coal seam was shown to offer the potential of detecting inundation hazards 200 feet or more ahead of mining. Controlled-waveform seismic source transducers and specialized receiving transducers were conceived and developed. Emphasis was on concept demonstration and experimental guided wave propagation studies. Two major field tests were undertaken in Kentucky and Virginia. Guided wave propagation phenomena were observed in 54- and 70-inch coal seams.

  14. An Improved Face Recognition Approach Based on a Combination of Haar Feature and Skin Color Detection%基于Haar特征和肤色特征的一种面部检测方法

    Institute of Scientific and Technical Information of China (English)

    傅为

    2012-01-01

      本文提出用于人脸识别系统(Face Recognition System,简称FRS系统)中基于Haar特征和肤色特征的一种面部检测方法:首先用Haar特征对可能存在人脸的图像进行快速的检测,然后用肤色特征消除相应的彩色图像中误判的人脸检测。实验结果表明该系统具有较快的识别速度、较高的人脸识别率和较低的人脸误检率。%  The author proposed an efficient Face Recognition System (FRS) based on Haar feature and skin color algorithm. At the first step, a Haar Feature based face detector is applied for grey-scale image to rapidly detect possible face positions in the image. Later, false face detections are eliminated by skin color filtering on corresponding color image. The results show higher face recognition speed, more accurate face recognition rate, and less false face recognition rate.

  15. Uma outra face dos metadados: informações para a gestão da preservação digitalAnother face of the metadata: information for management of digital preservation

    Directory of Open Access Journals (Sweden)

    Luis Fernando Sayão

    2010-10-01

    Full Text Available O conceito tradicional de metadado pode ser ampliado para abrigar um conjunto de informações que apóiem as atividades de gestão da preservação de materiais digitais. Esse tipo de metadados, chamados de metadados de preservação, tem como função instruir e documentar os processos de preservação digital de longo prazo, garantindo que os conteúdos digitais possam ser acessados e interpretados no futuro. Nos últimos anos foram desenvolvidos inúmeros esquemas e infraestruturas de metadados voltados para a preservação digital, que tiveram como maior desafio antecipar que informações são realmente necessárias para suportar um processo específico de preservação. A iniciativa mais importante e mais abrangente nesse campo é o dicionário de dados PREMIS cujo desenvolvimento teve como base a infraestrutura conceitual definida pela norma OAIS. A idéia básica deste trabalho é revisar os principais conceitos, padrões e tecnologias envolvidos no desenvolvimento de esquemas de metadados de preservação.The traditional concept of metadata can be expanded to provide a set of information to support the management activities of the preservation of digital materials. This type of metadata, called preservation metadata, is designed to inform and document the process of digital preservation of long-term, assuring that digital content can be accessed and interpreted in the future. In recent years many metadata schemes and infrastructure oriented for digital preservation have been developed; the greatest challenge they face has been to anticipate what information is actually required to support a particular process of digital preservation. The most important and comprehensive initiative in this field is the PREMIS Data Dictionary, developed based on the conceptual infrastructure defined by the OAIS ISO standard. The basic idea of this paper is to review the main concepts, standards and technologies involved in the development of metadata

  16. Tools for Multimode Quantum Information: Modulation, Detection, and Spatial Quantum Correlations

    DEFF Research Database (Denmark)

    Lassen, Mikael Østergaard; Delaubert, Vincent; Janousek, Jirí

    2007-01-01

    We present here all the tools required for continuous variable parallel quantum information protocols based on spatial multi-mode quantum correlations and entanglement. We describe techniques for encoding and detecting this quantum information with high efficiency in the individual modes. We use ...

  17. 一种适用于人脸检测具有强聚类能力的新颜色空间YCH%A New Color Space YCH with Strong Clustering Power for Face Detection

    Institute of Scientific and Technical Information of China (English)

    钟志光

    2011-01-01

    Using information of skin color to detect face region is quick and effective. However, it is very difficult to choose a suitable color space. In this paper, A novel adaptive color space YCH is proposed. It fuses the merits of the commonly used color spaces into a new simple nonlinear transformation. All the transformation coefficients can adjust automatically according to the respective characteristics of each pixel in the face image, and then eliminate effectively various unfavorable influence factors to the classifying result of the skin color and non-skin color. Experimental results demonstrate the good discriminating power of the proposed color space to all kinds of face images.%利用肤色信息检测人脸是一种快速而有效的方法,但选取合适的颜色空间是一个十分棘手的问题.文中提出一种自适应颜色空间YCH,将最常用颜色空间的优点融合到一个新的简单的非线性变换,其中所有的变换系数都能根据人脸图像中每个像素自身的特性自动调整,因而可有效消除影响肤色与非肤色分类结果的各种不利因素.实验结果表明提出的颜色空间对各类人脸图像都有很强的聚类能力.

  18. Rapid prefrontal cortex activation towards aversively paired faces and enhanced contingency detection are observed in highly trait-anxious women under challenging conditions

    Directory of Open Access Journals (Sweden)

    Maimu Alissa Rehbein

    2015-06-01

    Full Text Available Relative to healthy controls, anxiety-disorder patients show anomalies in classical conditioning that may either result from, or provide a risk factor for, clinically relevant anxiety. Here, we investigated whether healthy participants with enhanced anxiety vulnerability show abnormalities in a challenging affective-conditioning paradigm, in which many stimulus-reinforcer associations had to be acquired with only few learning trials. Forty-seven high and low trait-anxious females underwent MultiCS conditioning, in which 52 different neutral faces (CS+ were paired with an aversive noise (US, while further 52 faces (CS- remained unpaired. Emotional learning was assessed by evaluative (rating, behavioral (dot-probe, contingency report, and neurophysiological (magnetoencephalography measures before, during, and after learning. High and low trait-anxious groups did not differ in evaluative ratings or response priming before or after conditioning. High trait-anxious women, however, were better than low trait-anxious women at reporting CS+/US contingencies after conditioning, and showed an enhanced prefrontal cortex activation towards CS+ in the M1 (i.e., 80 to 117 ms and M170 time intervals (i.e., 140 to 160 ms during acquisition. These effects in MultiCS conditioning observed in individuals with elevated trait anxiety are consistent with theories of enhanced conditionability in anxiety vulnerability. Furthermore, they point towards increased threat monitoring and detection in highly trait-anxious females, possibly mediated by alterations in visual working memory.

  19. Effects of localized auditory information on visual target detection performance using a helmet-mounted display.

    Science.gov (United States)

    Nelson, W T; Hettinger, L J; Cunningham, J A; Brickman, B J; Haas, M W; McKinley, R L

    1998-09-01

    An experiment was conducted to evaluate the effects of localized auditory information on visual target detection performance. Visual targets were presented on either a wide field-of-view dome display or a helmet-mounted display and were accompanied by either localized, nonlocalized, or no auditory information. The addition of localized auditory information resulted in significant increases in target detection performance and significant reductions in workload ratings as compared with conditions in which auditory information was either nonlocalized or absent. Qualitative and quantitative analyses of participants' head motions revealed that the addition of localized auditory information resulted in extremely efficient and consistent search strategies. Implications for the development and design of multisensory virtual environments are discussed. Actual or potential applications of this research include the use of spatial auditory displays to augment visual information presented in helmet-mounted displays, thereby leading to increases in performance efficiency, reductions in physical and mental workload, and enhanced spatial awareness of objects in the environment.

  20. Multibiometrics for face recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond; Deravi, Farzin; Tao, Qian

    2008-01-01

    Fusion is a popular practice to combine multiple sources of biometric information to achieve systems with greater performance and flexibility. In this paper various approaches to fusion within a multibiometrics context are considered and an application to the fusion of 2D and 3D face information is

  1. Multibiometrics for face recognition

    NARCIS (Netherlands)

    Veldhuis, Raymond N.J.; Deravi, Farzin; Tao, Q.

    Fusion is a popular practice to combine multiple sources of biometric information to achieve systems with greater performance and flexibility. In this paper various approaches to fusion within a multibiometrics context are considered and an application to the fusion of 2D and 3D face information is

  2. A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    2015-03-01

    Full Text Available A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance.

  3. Priming with threatening faces modulates the self-face advantage by enhancing the other-face processing rather than suppressing the self-face processing.

    Science.gov (United States)

    Guan, Lili; Qi, Mingming; Li, Haijiang; Hitchman, Glenn; Yang, Juan; Liu, Yijun

    2015-05-22

    Social emotional information influences self-processing in everyday activities, but few researchers have investigated this process. The current ERP study adopted a prime paradigm to investigate how socially threatening faces impact on the self-face processing advantage. After being primed with emotional faces (happy, angry or neutral), participants judged whether the target face (self, friend, and stranger) was familiar or unfamiliar. Results showed an interaction effect between the prime face and the target face at posterior P3, suggesting that after priming with happy and neutral faces, self-faces elicited larger P3 amplitudes than friend-faces and stranger-faces; however, after priming with angry faces, the P3 amplitudes were not significantly different between self-face and friend-face. Moreover, the P3 amplitudes of self-faces did not differ between priming with angry and neutral faces; however, the P3 amplitude of both friend-faces and stranger-faces showed enhanced responses after priming with angry faces compared to priming with neutral faces. We suggest that the self-face processing advantage (self vs. friend) could be weakened by priming with threatening faces, through enhancement of the other-faces processing rather than suppression of self-faces processing in angry vs. neutral face prime.

  4. Laughing in the Face of Fear (of Disease Detection): Using Humor to Promote Cancer Self-Examination Behavior.

    Science.gov (United States)

    Nabi, Robin L

    2016-07-01

    This research examines the possible benefit of using humor to reduce anxiety associated with performing cancer self-examination behaviors. In Study 1, 187 undergraduates read a humorous public service announcement (PSA) script promoting either breast or testicular self-exams. Results suggest that perception of humor reduced anxiety about self-exams, which, in turn, related to more positive self-exam attitudes. Simultaneously, humor perception associated with greater message processing motivation, which, in turn, associated with more supportive self-exam attitudes. Self-exam attitudes also positively associated with self-exam intentions. These results were largely replicated in Study 2. Further, self-exam intentions predicted self-exam behavior 1 week later. However, consistent with past research, the humorous and serious messages did not generate differences in subsequent self-exam behavior, though the intention-behavior relationship was stronger and significant for those exposed to the humorous versus the serious messages. In light of these findings, and given that humor has the advantage of attracting and holding attention in real message environments, the use of carefully constructed humor appeals may be a viable message strategy to promote health detection behaviors.

  5. Mlifdect: Android Malware Detection Based on Parallel Machine Learning and Information Fusion

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2017-01-01

    Full Text Available In recent years, Android malware has continued to grow at an alarming rate. More recent malicious apps’ employing highly sophisticated detection avoidance techniques makes the traditional machine learning based malware detection methods far less effective. More specifically, they cannot cope with various types of Android malware and have limitation in detection by utilizing a single classification algorithm. To address this limitation, we propose a novel approach in this paper that leverages parallel machine learning and information fusion techniques for better Android malware detection, which is named Mlifdect. To implement this approach, we first extract eight types of features from static analysis on Android apps and build two kinds of feature sets after feature selection. Then, a parallel machine learning detection model is developed for speeding up the process of classification. Finally, we investigate the probability analysis based and Dempster-Shafer theory based information fusion approaches which can effectively obtain the detection results. To validate our method, other state-of-the-art detection works are selected for comparison with real-world Android apps. The experimental results demonstrate that Mlifdect is capable of achieving higher detection accuracy as well as a remarkable run-time efficiency compared to the existing malware detection solutions.

  6. The design of face detection system based on computer vision technology%基于计算机视觉技术的人脸检测系统设计

    Institute of Scientific and Technical Information of China (English)

    王斌; 郭攀; 张坤; 黄乐

    2011-01-01

    通过对基于Haar-like特征的AdaBoost人脸检测算法研究,利用由该算法训练的级联分类器和计算机视觉类库OpenCV进行人脸检测系统设计,实现了基于静态图像、摄像头视频和avi视频的人脸检测与标记,以及标记后的人脸区域图像实时显示和存盘。此外,在VC++6.0环境下实现了对人脸检测系统软件界面的开发。实验结果表明,该检测系统开发周期短,检测速度快,实时性强,检测率高,可作为人脸识别和人脸跟踪系统的开发基础。%Through the research for AdaBoost face detection algorithm based on Haar-like features,make use of the cascade classifier trained by this algorithm and computer vision library OpenCV to design a face detection system,realize face detection and mark based on static image,camera video and avi video,finish displaying and saving the face region images marked by rectangles real-timely.Besides,achieve the development of software interface by VC++ 6.0.The experiment result shows that the face detection system has features of short develop cycle,rapid detection,real-time and high detection rate,which can be used for the bases of face recognition system and face tracking system.

  7. Image preprocessing study on KPCA-based face recognition

    Science.gov (United States)

    Li, Xuan; Li, Dehua

    2015-12-01

    Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

  8. Development of a methodology for the detection of hospital financial outliers using information systems.

    Science.gov (United States)

    Okada, Sachiko; Nagase, Keisuke; Ito, Ayako; Ando, Fumihiko; Nakagawa, Yoshiaki; Okamoto, Kazuya; Kume, Naoto; Takemura, Tadamasa; Kuroda, Tomohiro; Yoshihara, Hiroyuki

    2014-01-01

    Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers. Copyright © 2013 John Wiley & Sons, Ltd.

  9. Robust Point Set Matching for Partial Face Recognition.

    Science.gov (United States)

    Weng, Renliang; Lu, Jiwen; Tan, Yap-Peng

    2016-03-01

    Over the past three decades, a number of face recognition methods have been proposed in computer vision, and most of them use holistic face images for person identification. In many real-world scenarios especially some unconstrained environments, human faces might be occluded by other objects, and it is difficult to obtain fully holistic face images for recognition. To address this, we propose a new partial face recognition approach to recognize persons of interest from their partial faces. Given a pair of gallery image and probe face patch, we first detect keypoints and extract their local textural features. Then, we propose a robust point set matching method to discriminatively match these two extracted local feature sets, where both the textural information and geometrical information of local features are explicitly used for matching simultaneously. Finally, the similarity of two faces is converted as the distance between these two aligned feature sets. Experimental results on four public face data sets show the effectiveness of the proposed approach.

  10. Advanced detection technology of Rayleigh wave for detection of abnormal geological structure in excavation face%瑞利波技术超前探测掘进工作面构造异常

    Institute of Scientific and Technical Information of China (English)

    李胜; 祁晓鑫; 李军文

    2015-01-01

    In the front of excavation face, there exist abnormal geological structures such as fault, karst cave, col-lapsed pillars and aquifer, which usually bring about hazards like “pervious to water” and “roof fall” etc. How to accurately and effectively detect the geological structure in the front of excavation face has became a problem ur-gently needed to solve during production in coal mine. TYR (D) Rayleigh wave detector was adopted in advanced detection in driving face 7603 of Wuyang mine. The collected data were processed and analyzed, the conclusion is basically consistent with the engineering verification, thus obtaining good application effect.%掘进工作面前方存在断层、溶洞、陷落柱、含水层等地质构造,常常导致透水、冒顶等灾害性事故。采用YTR(D)瑞利波探测仪对山西潞安集团五阳煤矿7603掘进工作面进行超前探测,并对现场采集的数据进行处理和分析。结果显示,2个测点共发现9处异常区,通过后期工程验证,有7处探测异常区与实际揭露的结果基本一致,探测与实际揭露异常区域位置误差均在4m以内。

  11. 基于重建图像信噪比特征的脸部位置检测方法%Detection of Face Position Based on SNR of Reconstructed Images

    Institute of Scientific and Technical Information of China (English)

    郁洪强; 刘瑾; 周鹏

    2011-01-01

    Objective A new detection method of face position based on signal-to-noise ( SNR) of reconstructed images was developed, which can improve the accuracy of finding the face position in the image. Methods The SNR of reconstructed images was acquired by projecting to eigenface space and used in the face detection. Correspondingly , the face was detected according to the dynamic change of SNR. The results of experiments showed that the SNR of faces in whole image was the maximum when the image was scanned horizontally and vertically. If the image only includes one face, then SNR of the face was global maximum. Results One hundred images from face database of Yale University and 50 images from photos acquired by camera were detected. The correct rate of the detection reached to 98% . Furthermore ,we scaned the acquired faces by above method again ,and then the center zone of face was marked without hair and so on. In this face , the positions of eyes were determined by sharpening and template matching. The face would be rotated in order to make eyes being horizontal, then the face were cropped again according to the proportions. The correction rata of eye position detection reached to 96% . Conclusions The detection method based on SNR of reconstructed images improves the accuracy of finding the face position in the image, and it is simple and efficient for face position detection.%目的 通过研究找到一种基于重建图像信噪比(signal-to-noise,SNR)的人脸检测方法,从而提高在图片中找到人脸所在位置的准确率.方法 首先通过图像向特征脸空间投影得到重建图像,然后利用重建图像的SNR进行人脸检测.经实验发现,在对一幅图像进行扫描的过程中,人脸的位置既是信噪比值横向的极大值点,又是纵向的极大值点,且在单幅人脸图像中,人脸处的SNR为全局极大值,因此可以利用该动态规律准确地找到人脸位置.结果 利用上述方法对耶鲁人脸库100

  12. Face Processing: Models For Recognition

    Science.gov (United States)

    Turk, Matthew A.; Pentland, Alexander P.

    1990-03-01

    The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

  13. About Face

    Medline Plus

    Full Text Available ... PTSD (posttraumatic stress disorder). Watch the intro This is AboutFace In these videos, Veterans, family members, and ... to hear what they have to say. What is PTSD? → How does PTSD affect loved ones? → Am ...

  14. About Face

    Medline Plus

    Full Text Available ... traumatic event — like combat, an assault, or a disaster — it's normal to feel scared, keyed up, or sad at first. But if it's been months or years since the trauma and you're not feeling better, you may have PTSD (posttraumatic stress disorder). Watch the intro This is AboutFace In ...

  15. [Fast Detection of Camellia Sinensis Growth Process and Tea Quality Informations with Spectral Technology: A Review].

    Science.gov (United States)

    Peng, Ji-yu; Song, Xing-lin; Liu, Fei; Bao, Yi-dan; He, Yong

    2016-03-01

    The research achievements and trends of spectral technology in fast detection of Camellia sinensis growth process information and tea quality information were being reviewed. Spectral technology is a kind of fast, nondestructive, efficient detection technology, which mainly contains infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy and mass spectroscopy. The rapid detection of Camellia sinensis growth process information and tea quality is helpful to realize the informatization and automation of tea production and ensure the tea quality and safety. This paper provides a review on its applications containing the detection of tea (Camellia sinensis) growing status(nitrogen, chlorophyll, diseases and insect pest), the discrimination of tea varieties, the grade discrimination of tea, the detection of tea internal quality (catechins, total polyphenols, caffeine, amino acid, pesticide residual and so on), the quality evaluation of tea beverage and tea by-product, the machinery of tea quality determination and discrimination. This paper briefly introduces the trends of the technology of the determination of tea growth process information, sensor and industrial application. In conclusion, spectral technology showed high potential to detect Camellia sinensis growth process information, to predict tea internal quality and to classify tea varieties and grades. Suitable chemometrics and preprocessing methods is helpful to improve the performance of the model and get rid of redundancy, which provides the possibility to develop the portable machinery. Future work is to develop the portable machinery and on-line detection system is recommended to improve the further application. The application and research achievement of spectral technology concerning about tea were outlined in this paper for the first time, which contained Camellia sinensis growth, tea production, the quality and safety of tea and by-produce and so on, as well as some problems to be solved

  16. 多特征双重匹配验证的驾驶员脸部融合检测%Face Fusion Detection of Multi-feature and Double Matching Verification for Driver

    Institute of Scientific and Technical Information of China (English)

    孙伟; 张为公; 张小瑞; 陈刚; 吕成绪

    2009-01-01

    Referring to the limitation of driver face detection algorithm based on single feature in detection precision and reliability, a novel fusion algorithm of driver face detection is proposed. Firstly, an improved face detection algorithm based on Haar-like feature is used to detect the possibly existing face region in the whole image. Then, the detected region is extended adaptively and a face detection algorithm based on skin color feature in YCbCr space is used to detect the face again in the extended area. Finally, double matching verification is made by the defined area coincidence degree and geometric prior knowledge of human face and fusion detection of driver face region is achieved by establishing relevant location rules. Experiment results in various complicated road conditions show the effectiveness of the proposed algorithm.%针对基于单一特征驾驶员脸部检测算法在检测精度和可靠性方面的局限性,提出了一种新颖的驾驶员脸部检测融合算法.首先采用改进的基于Haar-like特征的人脸检测算法在整幅图像上检测出可能存在的初始人脸区域,然后自适应地扩大初始人脸区域范围,并在此基础上利用基于肤色特征的方法在YCbCr空间上进行脸部的二次检测,最后根据定义的脸部区域重合度和人脸几何先验知识对驾驶员脸部区域进行双重匹配验证进而制定相应的定位规则对脸部进行融合检测.各种复杂路况下的实验结果证明了该算法的有效性.

  17. Efficient Structural System Reliability Updating with Subspace-Based Damage Detection Information

    DEFF Research Database (Denmark)

    Döhler, Michael; Thöns, Sebastian

    modelling is introduced building upon the non-destructive testing reliability which applies to structural systems and DDS containing a strategy to overcome the high computational efforts for the pre-determination of the DDS reliability. This approach takes basis in the subspace-based damage detection method......Damage detection systems and algorithms (DDS and DDA) provide information of the structural system integrity in contrast to e.g. local information by inspections or non-destructive testing techniques. However, the potential of utilizing DDS information for the structural integrity assessment...... and prognosis is hardly exploited nor treated in scientific literature up to now. In order to utilize the information provided by DDS for the structural performance, usually high computational efforts for the pre-determination of DDS reliability are required. In this paper, an approach for the DDS performance...

  18. Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction

    Directory of Open Access Journals (Sweden)

    Jan Mielniczuk

    2017-01-01

    Full Text Available We reconsider the properties and relationships of the interaction information and its modified versions in the context of detecting the interaction of two SNPs for the prediction of a binary outcome when interaction information is positive. This property is called predictive interaction, and we state some new sufficient conditions for it to hold true. We also study chi square approximations to these measures. It is argued that interaction information is a different and sometimes more natural measure of interaction than the logistic interaction parameter especially when SNPs are dependent. We introduce a novel measure of predictive interaction based on interaction information and its modified version. In numerical experiments, which use copulas to model dependence, we study examples when the logistic interaction parameter is zero or close to zero for which predictive interaction is detected by the new measure, while it remains undetected by the likelihood ratio test.

  19. Application of artificial neural network and information theory to detection of insulators

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Information theory is used to obtain the information gain for each identification feature, and this gain is used as the weight factor for this feature to stress the role of effective feature, and the ART model based on artificial neural network theory is then used for identification thereby forming the detection system for poor insulators. Exper-iments and calculations show this approach is correct and feasible.

  20. [Face recognition in patients with schizophrenia].

    Science.gov (United States)

    Doi, Hirokazu; Shinohara, Kazuyuki

    2012-07-01

    It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.

  1. Failure detection of liquid cooled electronics in sealed packages. [in airborne information management system

    Science.gov (United States)

    Hoadley, A. W.; Porter, A. J.

    1991-01-01

    The theory and experimental verification of a method of detecting fluid-mass loss, expansion-chamber pressure loss, or excessive vapor build-up in NASA's Airborne Information Management System (AIMS) are presented. The primary purpose of this leak-detection method is to detect the fluid-mass loss before the volume of vapor on the liquid side causes a temperature-critical part to be out of the liquid. The method detects the initial leak after the first 2.5 pct of the liquid mass has been lost, and it can be used for detecting subsequent situations including the leaking of air into the liquid chamber and the subsequent vapor build-up.

  2. Domain Information Based Blacklisting Method for the Detection of Malicious Webpages

    Directory of Open Access Journals (Sweden)

    Ralph Edem Agbefu

    2015-05-01

    Full Text Available Malicious web pages that host drive by download exploits have become a popular means by which an attacker delivers malicious contents to computers across the internet. The popularity of the attack has led to researchers developing systems to detect and stop such attacks. These methods include dynamic solutions, static solutions and the use of blacklisting and whitelisting methods. Blacklisting and in particular URL blacklisting is one of such detection methods. URL blacklisting analyzes the structure of a web page URL. URL blacklisting are however prone to evasion attacks when the lexical structure of the URL changes. In this paper, we propose the usage of domain related information for the detection of drive by download web pages. These domain features are used to model a scoring mechanism classification system. We show the effectiveness of detecting malicious web pages using domain based by obtaining a high detection rate and a relatively low false negative.

  3. Congenital prosopagnosia: face-blind from birth.

    Science.gov (United States)

    Behrmann, Marlene; Avidan, Galia

    2005-04-01

    Congenital prosopagnosia refers to the deficit in face processing that is apparent from early childhood in the absence of any underlying neurological basis and in the presence of intact sensory and intellectual function. Several such cases have been described recently and elucidating the mechanisms giving rise to this impairment should aid our understanding of the psychological and neural mechanisms mediating face processing. Fundamental questions include: What is the nature and extent of the face-processing deficit in congenital prosopagnosia? Is the deficit related to a more general perceptual deficit such as the failure to process configural information? Are any neural alterations detectable using fMRI, ERP or structural analyses of the anatomy of the ventral visual cortex? We discuss these issues in relation to the existing literature and suggest directions for future research.

  4. A connectionist computational method for face recognition

    Directory of Open Access Journals (Sweden)

    Pujol Francisco A.

    2016-06-01

    Full Text Available In this work, a modified version of the elastic bunch graph matching (EBGM algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.

  5. Face detection based on MB-LBP and eye tracking%基于多块局部二值模式特征和人眼定位的人脸检测

    Institute of Scientific and Technical Information of China (English)

    王小玉; 张亚洲; 陈德运

    2014-01-01

    人脸检测是人脸识别和重构问题中最基本的任务,同样也是人脸识别问题中的一个关键环节,其结果直接关乎到人脸识别最终的效果。所以,构建一种稳健而优秀的检测算法是人脸检测的目的。本文提出了一种基于多块局部二值模式特征的 adaboost 算法和模板匹配的人眼定位方法,从而提高人脸检测的正确率和稳定率,减少了误差。通过 MIT CBCL人脸数据库、生活、网络等渠道照片的实验验证,该方法提高了检测效率,降低误检率,兼具了实时性和鲁棒性。%Face detection is not only a basic task for face recognition and reconstruction, but also is the key section of face recognition system. The result of face detection has important influence on the effect of face recognition. It is necessary to build an excellent face detection algorithm. The face detection method based on MB-LBP and eye tracking is presented. Experimental result shows that the method not only enhances the accuracy and robustness, but also reduces the false alarm rate and operation time.

  6. Reading faces and Facing words

    DEFF Research Database (Denmark)

    Robotham, Julia Emma; Lindegaard, Martin Weis; Delfi, Tzvetelina Shentova

    It has long been argued that perceptual processing of faces and words is largely independent, highly specialised and strongly lateralised. Studies of patients with either pure alexia or prosopagnosia have strongly contributed to this view. The aim of our study was to investigate how visual...

  7. Reading faces and Facing words

    DEFF Research Database (Denmark)

    Robotham, Julia Emma; Lindegaard, Martin Weis; Delfi, Tzvetelina Shentova

    performed within normal range on at least one test of visual categorisation, strongly suggesting that their abnormal performance with words and faces does not represent a generalised visuo-perceptual deficit. Our results suggest that posterior areas in both hemispheres may be critical for both reading...

  8. Quantified Faces

    DEFF Research Database (Denmark)

    Sørensen, Mette-Marie Zacher

    2016-01-01

    Abstract: The article presents three contemporary art projects that, in various ways, thematise questions regarding numerical representation of the human face in relation to the identification of faces, for example through the use of biometric video analysis software, or DNA technology. The Dutch...... and critically examine bias in surveillance technologies, as well as scientific investigations, regarding the stereotyping mode of the human gaze. The American artist Heather Dewey-Hagborg creates three-dimensional portraits of persons she has “identified” from their garbage. Her project from 2013 entitled....... The three works are analysed with perspectives to historical physiognomy and Francis Galton's composite portraits from the 1800s. It is argued that, rather than being a statistical compression like the historical composites, contemporary statistical visual portraits (composites) are irreversible...

  9. Summarization of Surveillance Video Sequences Using Face Quality Assessment

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.; Rahmati, Mohammad

    2011-01-01

    Constant working surveillance cameras in public places, such as airports and banks, produce huge amount of video data. Faces in such videos can be extracted in real time. However, most of these detected faces are either redundant or useless. Redundant information adds computational costs to facial...... analysis systems and useless data makes the final results of such systems noisy, unstable, and erroneous. Thus, there is a need for a mechanism to summarize the original video sequence to a set of the most expressive images of the sequence. The proposed system in this paper uses a face quality assessment...

  10. Face Search at Scale.

    Science.gov (United States)

    Wang, Dayong; Otto, Charles; Jain, Anil K

    2016-06-20

    rsons of interest among the billions of shared photos on these websites. Despite significant progress in face recognition, searching a large collection of unconstrained face images remains a difficult problem. To address this challenge, we propose a face search system which combines a fast search procedure, coupled with a state-of-the-art commercial off the shelf (COTS) matcher, in a cascaded framework. Given a probe face, we first filter the large gallery of photos to find the top-k most similar faces using features learned by a convolutional neural network. The k retrieved candidates are re-ranked by combining similarities based on deep features and those output by the COTS matcher. We evaluate the proposed face search system on a gallery containing 80 million web-downloaded face images. Experimental results demonstrate that while the deep features perform worse than the COTS matcher on a mugshot dataset (93.7% vs. 98.6% TAR@FAR of 0.01%), fusing the deep features with the COTS matcher improves the overall performance (99.5% TAR@FAR of 0.01%). This shows that the learned deep features provide complementary information over representations used in state-of-the-art face matchers. On the unconstrained face image benchmarks, the performance of the learned deep features is competitive with reported accuracies. LFW database: 98.20% accuracy under the standard protocol and 88.03% TAR@FAR of 0.1% under the BLUFR protocol; IJB-A benchmark: 51.0% TAR@FAR of 0.1% (verification), rank 1 retrieval of 82.2% (closed-set search), 61.5% FNIR@FAR of 1% (open-set search). The proposed face search system offers an excellent trade-off between accuracy and scalability on galleries with millions of images. Additionally, in a face search experiment involving photos of the Tsarnaev brothers, convicted of the Boston Marathon bombing, the proposed cascade face search system could find the younger brother's (Dzhokhar Tsarnaev) photo at rank 1 in 1 second on a 5M gallery and at rank 8 in 7

  11. Surprise, p-value, s-value and a diagnostic procedure to detect not informative experiments

    Science.gov (United States)

    Recchia, Daniela R.; Ostermann, Thomas; Garcia, Jesus E.

    2016-06-01

    In this paper, examples of diverse measures of significance are studied in the frame of Neyman-Pearson hypothesis tests. A diagnostic procedure is proposed, to detect non informative experiments where the p-value procedure might fail to measure the significance of the outcome of an experiment.

  12. 一种基于肤色后置滤波的快速人脸检测算法%A Fast Face-Detection Algorithm based on Post Skin-Color-Verification

    Institute of Scientific and Technical Information of China (English)

    崔晓琳; 蔡灿辉; 朱建清

    2013-01-01

    Traditional AdaBoost face detector uses motion and complexion detection as its pre-filter for promoting the detection speed. However, this approach suffers if the detected face is in a highlight or low illuminated background. To address this problem, an AdaBoost face-detection algorithm with motion detection as its pre-filtering and adaptive skin-color verification as its post-processing is proposed in this paper, thus to improve the robustness of face-detection system under the complex change conditions of illumination. Experimental results indicate that compared with the traditional approach, the proposed face detection algorithm can effectively remove textural interference, and is more robust to the illumination change.%针对传统的以运动和肤色检测为前置的AdaBoost人脸检测算法在高光或低照度下肤色检测失败,导致人脸漏检的问题,提出一种后置自适应肤色验证的人脸检测算法。首先用运动检测减小人脸检测搜索范围,然后用AdaBoost算法检测出人脸候选区,最后再对正常亮度的人脸候选区采用肤色验证进行人脸确认,排除虚警。实验结果表明,该算法能有效地排除纹理干扰,与传统的人脸检测算法相比具有更好的光照鲁棒性。

  13. A simple method for detection of gunshot residue particles from hands, hair, face, and clothing using scanning electron microscopy/wavelength dispersive X-ray (SEM/WDX).

    Science.gov (United States)

    Kage, S; Kudo, K; Kaizoji, A; Ryumoto, J; Ikeda, H; Ikeda, N

    2001-07-01

    We devised a simple and rapid method for detection of gunshot residue (GSR) particles, using scanning electron microscopy/wavelength dispersive X-ray (SEM/WDX) analysis. Experiments were done on samples containing GSR particles obtained from hands, hair, face, and clothing, using double-sided adhesive coated aluminum stubs (tape-lift method). SEM/WDX analyses for GSR were carried out in three steps: the first step was map analysis for barium (Ba) to search for GSR particles from lead styphnate primed ammunition, or tin (Sn) to search for GSR particles from mercury fulminate primed ammunition. The second step was determination of the location of GSR particles by X-ray imaging of Ba or Sn at a magnification of x 1000-2000 in the SEM, using data of map analysis, and the third step was identification of GSR particles, using WDX spectrometers. Analysis of samples from each primer of a stub took about 3 h. Practical applications were shown for utility of this method.

  14. 基于颜色和特征匹配的视频图像人脸检测实现技术%Face Detection Using Skin-Color and Feature Matching

    Institute of Scientific and Technical Information of China (English)

    牛德姣; 詹永照; 宋顺林

    2003-01-01

    A face detection method using statistical skin-color model and facial feature matching is presented in this paper. According to skin-color distribution in YUV color space,we develope a statistical skin-color model through interactive sample training and learning. Using this method we convert the color image to binary image and then segment face-candidate regions in the video images. In order to improve the quality of binary image and remove unwanted noises ,filtering and mathematical morphology are empolied. After these two processing,we use facial feature matching for further detection. The presence or absence of a face in each region is verified by means of mouth detector based on a template matching method. The experimental results show the proposed method has the features of high speed and high efficiency,but also robust to face variation to some extent. So it is suitable to be applied to real-time face detection and tracking in video sequences.

  15. 较强光照下肤色结合发色检测人脸的方法研究%Research of face detection by skin color with hair color under strong light condition

    Institute of Scientific and Technical Information of China (English)

    黄亦佳; 潘巍

    2011-01-01

    研究了基于不同颜色空间的人脸检测算法,并在此基础上针对较强光照条件下或肤色与背景色比较接近时检测算法可能会将人脸检测为背景的情况,提出了一种新的基于肤色和发色的人脸检测自适应算法.实验结果表明,即使在较强光照条件下或肤色与背景比较接近时,该算法一样能准确地检测到正面或略有倾斜的人脸.%This paper discusses face detection algorithms based on different color spaces,and then provides a new adaptive face detection algorithm based on both face-color and hair-color space. Experimental results show that even under the strong light conditions,or the background color and face color is similar,the algorithm also can accurately detect a front or slightly sloping of the face.

  16. A novel thermal face recognition approach using face pattern words

    Science.gov (United States)

    Zheng, Yufeng

    2010-04-01

    A reliable thermal face recognition system can enhance the national security applications such as prevention against terrorism, surveillance, monitoring and tracking, especially at nighttime. The system can be applied at airports, customs or high-alert facilities (e.g., nuclear power plant) for 24 hours a day. In this paper, we propose a novel face recognition approach utilizing thermal (long wave infrared) face images that can automatically identify a subject at both daytime and nighttime. With a properly acquired thermal image (as a query image) in monitoring zone, the following processes will be employed: normalization and denoising, face detection, face alignment, face masking, Gabor wavelet transform, face pattern words (FPWs) creation, face identification by similarity measure (Hamming distance). If eyeglasses are present on a subject's face, an eyeglasses mask will be automatically extracted from the querying face image, and then masked with all comparing FPWs (no more transforms). A high identification rate (97.44% with Top-1 match) has been achieved upon our preliminary face dataset (of 39 subjects) from the proposed approach regardless operating time and glasses-wearing condition.e

  17. An Indoor Obstacle Detection System Using Depth Information and Region Growth

    Directory of Open Access Journals (Sweden)

    Hsieh-Chang Huang

    2015-10-01

    Full Text Available This study proposes an obstacle detection method that uses depth information to allow the visually impaired to avoid obstacles when they move in an unfamiliar environment. The system is composed of three parts: scene detection, obstacle detection and a vocal announcement. This study proposes a new method to remove the ground plane that overcomes the over-segmentation problem. This system addresses the over-segmentation problem by removing the edge and the initial seed position problem for the region growth method using the Connected Component Method (CCM. This system can detect static and dynamic obstacles. The system is simple, robust and efficient. The experimental results show that the proposed system is both robust and convenient.

  18. A Semiautomatic Large-Scale Detection of Simple Geometric Primitives for Detecting Structural Defects from Range-Based Information

    Directory of Open Access Journals (Sweden)

    R. Martínez

    2011-12-01

    Full Text Available Buildings in Cultural Heritage environments exhibit some common structural defects in elements which can be recognized by their differences with respect to the ideal geometric model. The global approach consists of detecting misalignments between elements corresponding to sections perpendicular to an axis, e.g. The local approach consists of detecting lack of verticality or meaningful differences (facades or internal walls in curved elements with typical components (apses or vaults, e.g. appearing in indoor environments. Geometric aspects concern to the basic model which supports successive layers corresponding to materials analysis and mechanical structural behaviour. A common strategy for detecting simple shapes consists of constructing maps of normal which can be extracted by an appropriate sampling of unit normal vectors linked to a points cloud. The most difficult issue concerns to the sampling process. A profusion of decorative details or even the small variations corresponding to small columns which are prolonging the nerves of vaults generate a dispersion of data which can be solved in a manual way by removing notrelevant zones for structural analysis. This method can be appropriate for small churches with a low number of vaults, but it appears as tedious when we are trying to analyse a large cathedral or an urban district. To tackle this problem different strategies for sampling information are designed, where some of them involving geometric aspects have been implemented. We illustrate our approach with several examples concerning to outdoor urban districts and indoor structural elements which display different kinds of pathologies.

  19. [Comparative studies of face recognition].

    Science.gov (United States)

    Kawai, Nobuyuki

    2012-07-01

    Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.

  20. WIRELESS SENSOR NETWORKS AND FUSION OF CONTEXTUAL INFORMATION FOR WEATHER OUTLIER DETECTION

    Directory of Open Access Journals (Sweden)

    A. Amidi

    2013-09-01

    Full Text Available Weather stations are often expensive hence it may be difficult to obtain data with a high spatial coverage. A low cost alternative is wireless sensor network (WSN, which can be deployed as weather stations and address the aforementioned shortcoming. Due to imperfect sensors in WSNs context, provided raw data may be drawn in from of a low quality and reliability level, expectedly that is an emergence of applying outlier detection methods. Outliers may include errors or potentially useful information called events. In this research, forecast values as contextual information are utilized for weather outlier detection. In this paper, outliers are identified by comparing the patterns of WSN and forecasts. With that approach, temporal outliers are detected with respect to slopes of the WSNs and forecasts in the presence of pre-defined tolerance. The experimental results from the real data-set validate the applicability of using contextual information in the context of WSNs for outlier detection in terms of accuracy and energy efficiency.

  1. Design of Face Detection System Based on Dual Skin Models and AdaBoost Algorithm%基于双肤色模型和AdaBoost的人脸检测系统设计

    Institute of Scientific and Technical Information of China (English)

    侯顺艳; 郄建敏; 许静

    2014-01-01

    本文在Windows平台下,基于VS2010和Intel开源计算机视觉库OpenCV设计了一个实用的人脸检测系统,实现复杂背景图像中可能存在的人脸区域检测。人脸检测功能的实现主要融合双肤色模型和AdaBoost算法。首先基于YCbCr颜色空间的简单边界模型和高斯模型对图像实现分割并分析处理,实现人脸区域的粗定位。然后对人脸候选区域采用 AdaBoost算法进行精检测。该系统使用简单,检测效果较好。%A practical face detection system which is based on VS2010 and Intel open source computer vision library (OpenCV) under the platfrom of windows.was designed. It shoud bring out the face region detection in the complex backgroud image which may consist of face regions. The realization of face detection function is mainly fusion of dual skin models and Adaboost algorithm. The image segemention of skin region was firstly got based on a smiple boundary skin model and Gaussian skin color model in the YCbCr color space. The face coarse region location was determined by using the results of skin color segmentaion. Combining Adaboost algorithm, the accurate candidate face region was acquired secondly. This system is easy to use and has better detection.

  2. The Use of Contextual Information to Detection of Fraud on On - line Auctions

    Directory of Open Access Journals (Sweden)

    JIRI KNIZEK

    2013-12-01

    Full Text Available Currently, Internet auction portals are an integral part of business activities on the Internet. Anyone can easily participate in online auctions, either as a seller or a buyer (bidder, and the total turnover on Internet auction portals represents billions of dollars. However, the amount of fraud in these Internet auctions is related to their popularity. To prevent discovery,fraudsters exhibit normal trading behaviors and disguise themselves as honest members. It is therefore not easy to detect fraud in online auctions. There are some papers and approaches dealing with this problem with varying resultsthem concentrate on the selection of the attributes available within online auction portals and on computational methods for theirprocessing. This study proposes extendedthe fraud detection approach by using certain contextual information whose origin is outside online auctions portals. The suggested model integrates information from auctions and relevant contextual information with the aim to evaluate the behavior of certain sellers in an online auction and determine whether it is legal or not. Experimental results show that this approach based on the use of contextual information from other Internet sources provides good results and enhances significantly the accuracy of detection of certain types of fraud in online auctions.

  3. Detection of left ventricular motion abnormality via information measures and bayesian filtering.

    Science.gov (United States)

    Punithakumar, Kumaradevan; Ben Ayed, Ismail; Ross, Ian G; Islam, Ali; Chong, Jaron; Li, Shuo

    2010-07-01

    We present an original information theoretic measure of heart motion based on the Shannon's differential entropy (SDE), which allows heart wall motion abnormality detection. Based on functional images, which are subject to noise and segmentation inaccuracies, heart wall motion analysis is acknowledged as a difficult problem, and as such, incorporation of prior knowledge is crucial for improving accuracy. Given incomplete, noisy data and a dynamic model, the Kalman filter, a well-known recursive Bayesian filter, is devised in this study to the estimation of the left ventricular (LV) cavity points. However, due to similarity between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem, which we investigate with a global measure based on the SDE. We further derive two other possible information theoretic abnormality detection criteria, one is based on Rényi entropy and the other on Fisher information. The proposed methods analyze wall motion quantitatively by constructing distributions of the normalized radial distance estimates of the LV cavity. Using 269 x 20 segmented LV cavities of short-axis MRI obtained from 30 subjects, the experimental analysis demonstrates that the proposed SDE criterion can lead to a significant improvement over other features that are prevalent in the literature related to the LV cavity, namely, mean radial displacement and mean radial velocity.

  4. Heart motion abnormality detection via an information measure and Bayesian filtering.

    Science.gov (United States)

    Punithakumar, Kumaradevan; Li, Shuo; Ben Ayed, Ismail; Ross, Ian; Islam, Ali; Chong, Jaron

    2009-01-01

    This study investigates heart wall motion abnormality detection with an information theoretic measure of heart motion based on the Shannon's differential entropy (SDE) and recursive Bayesian filtering. Heart wall motion is generally analyzed using functional images which are subject to noise and segmentation inaccuracies, and incorporation of prior knowledge is crucial in improving the accuracy. The Kalman filter, a well known recursive Bayesian filter, is used in this study to estimate the left ventricular (LV) cavity points given incomplete and noisy data, and given a dynamic model. However, due to similarities between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem which we proposed to investigate with a global measure based on the SDE. We further derive two other possible information theoretic abnormality detection criteria, one is based on Rényi entropy and the other on Fisher information. The proposed method analyzes wall motion quantitatively by constructing distributions of the normalized radial distance estimates of the LV cavity. Using 269 x 20 segmented LV cavities of short-axis magnetic resonance images obtained from 30 subjects, the experimental analysis demonstrates that the proposed SDE criterion can lead to significant improvement over other features that are prevalent in the literature related to the LV cavity, namely, mean radial displacement and mean radial velocity.

  5. Information-theoretic approach to the gravitational-wave burst detection problem

    Science.gov (United States)

    Lynch, Ryan; Vitale, Salvatore; Essick, Reed; Katsavounidis, Erik; Robinet, Florent

    2017-05-01

    The observational era of gravitational-wave astronomy began in the fall of 2015 with the detection of GW150914. One potential type of detectable gravitational wave is short-duration gravitational-wave bursts, whose waveforms can be difficult to predict. We present the framework for a detection algorithm for such burst events—oLIB—that can be used in low latency to identify gravitational-wave transients. This algorithm consists of (1) an excess-power event generator based on the Q transform—Omicron—, (2) coincidence of these events across a detector network, and (3) an analysis of the coincident events using a Markov chain Monte Carlo Bayesian evidence calculator—LALInferenceBurst. These steps compress the full data streams into a set of Bayes factors for each event. Through this process, we use elements from information theory to minimize the amount of information regarding the signal-versus-noise hypothesis that is lost. We optimally extract this information using a likelihood-ratio test to estimate a detection significance for each event. Using representative archival LIGO data across different burst waveform morphologies, we show that the algorithm can detect gravitational-wave burst events of astrophysical strength in realistic instrumental noise. We also demonstrate that the combination of Bayes factors by means of a likelihood-ratio test can improve the detection efficiency of a gravitational-wave burst search. Finally, we show that oLIB's performance is robust against the choice of gravitational-wave populations used to model the likelihood-ratio test likelihoods.

  6. Information detective quantum efficiency of X-ray film-intensifier foil systems

    Energy Technology Data Exchange (ETDEWEB)

    Hoeschen, D.; Stargardt, A.; Mirande, W.

    1988-04-01

    The capability of screen-film combinations of detection and representation of information is described by the detective quantum efficiency (DQE). The DQE may be calculated from the sensitivity, the gradient of the characteristic curve, the modulation transfer function and the Wiener spectrum. These parameters have been determined for fourteen screen-film combinations and the DQE's have been calculated. It is shown that the low frequency region the DQE does not depend on spatial frequency. This constant level of DQE is mostly dependent on the absorbance of the screens. Consequences from this fact, as well for the manufacturer as for the user of the screens, are discussed.

  7. Fisher-information condition for enhanced signal detection via stochastic resonance.

    Science.gov (United States)

    Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek

    2011-11-01

    Various situations where a signal is enhanced by noise through stochastic resonance are now known. This paper contributes to determining general conditions under which improvement by noise can be a priori decided as feasible or not. We focus on the detection of a known signal in additive white noise. Under the assumptions of a weak signal and a sufficiently large sample size, it is proved, with an inequality based on the Fisher information, that improvement by adding noise is never possible, generically, in these conditions. However, under less restrictive conditions, an example of signal detection is shown with favorable action of adding noise.

  8. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    WuLifang; ShenLansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to rec-ognize faces with variant postures from front-view face.A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to facial symmetry.Then based on the relationship between the two mesh models,the nrmalized front-view face is formed by gray level mapping.Finally,the face recognition will be finished based on Principal Component Analysis(PCA).Experiments show that better face recognition performance is achieved in this way.

  9. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    Wu Lifang; Shen Lansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to recognize faces with variant postures from front-view face. A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to the facial symmetry. Then based on the inner relationship between the two mesh models, the normalized front-view face is formed by gray level mapping. Finally, the face recognition will be finished based on Principal Component Analysis (PCA). Experiments show that better face recognition performance is achieved in this way.

  10. Study of Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Sangeeta Kaushik

    2014-12-01

    Full Text Available A study of both face recognition and detection techniques is carried out using the algorithms like Principal Component Analysis (PCA, Kernel Principal Component Analysis (KPCA, Linear Discriminant Analysis (LDA and Line Edge Map (LEM. These algorithms show different rates of accuracy under different conditions. The automatic recognition of human faces presents a challenge to the pattern recognition community. Typically, human faces are different in shapes with minor similarity from person to person. Furthermore, lighting condition changes, facial expressions and pose variations further complicate the face recognition task as one of the difficult problems in pattern analysis.

  11. Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment.

    Science.gov (United States)

    Liu, Yang; Xu, Songhua; Tourassi, Georgia

    2015-01-01

    In the midst of today's pervasive influence of social media content and activities, information credibility has increasingly become a major issue. Accordingly, identifying false information, e.g. rumors circulated in social media environments, attracts expanding research attention and growing interests. Many previous studies have exploited user-independent features for rumor detection. These prior investigations uniformly treat all users relevant to the propagation of a social media message as instances of a generic entity. Such a modeling approach usually adopts a homogeneous network to represent all users, the practice of which ignores the variety across an entire user population in a social media environment. Recognizing this limitation of modeling methodologies, this study explores user-specific features in a social media environment for rumor detection. The new approach hypothesizes that whether a user tends to spread a rumor is dependent upon specific attributes of the user in addition to content characteristics of the message itself. Under this hypothesis, information propagation patterns of rumors versus those of credible messages in a social media environment are systematically differentiable. To explore and exploit this hypothesis, we develop a new information propagation model based on a heterogeneous user representation for rumor recognition. The new approach is capable of differentiating rumors from credible messages through observing distinctions in their respective propagation patterns in social media. Experimental results show that the new information propagation model based on heterogeneous user representation can effectively distinguish rumors from credible social media content.

  12. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  13. Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

    Science.gov (United States)

    Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

    2012-01-01

    With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

  14. Modeling Social Perception of Faces

    NARCIS (Netherlands)

    Todorov, A.T.; Oosterhof, N.N.

    2011-01-01

    The face is our primary source of visual information for identifying people and reading their emotional and mental states. With the exception of prosopagnosics (who are unable to recognize faces) and those suffering from such disorders of social cognition as autism, people are extremely adept at the

  15. MULTIMODAL INFORMATION FUSION AND TEMPORAL INTEGRATION FOR VIOLENCE DETECTION IN MOVIES

    OpenAIRE

    Penet, Cédric; Demarty, Claire-Hélène; Gravier, Guillaume; Gros, Patrick

    2012-01-01

    International audience; This paper presents a violent shots detection system that studies several methods for introducing temporal and multimodal information in the framework. It also investigates different kinds of Bayesian network structure learning algorithms for modelling these problems. The system is trained and tested using the MediaEval 2011 Affect Task corpus, which comprises of 15 Hollywood movies. It is experimentally shown that both multimodality and temporality add interesting inf...

  16. An improved adaboost algorithm based on new Haar-like feature for face detection%基于新 Haar-like 特征的 Adaboost 人脸检测算法

    Institute of Scientific and Technical Information of China (English)

    江伟坚; 郭躬德; 赖智铭

    2014-01-01

    为解决基于 Haar-like 特征的 Adaboost 人脸检测方法存在的特征计算复杂度较高的问题,提出两组 Haar-like特征扩展集;利用积分图给出特征组的计算方法;采用 Adaboost 算法在正脸和侧脸样本库分别训练出正脸和侧脸级联分类器,并将其组成双通道分类器。在开源视觉库 OpenCV 上的实验结果表明,本方法具有较少的弱分类器数,检测效率高、计算速度快,对于多角度人脸检测具有较好的鲁棒性。%To solve problem of highly complexity of multi-angle face detection by the Adaboost algorithm based on the Haar-like,two new groups of extended Haar-like feature were proposed and the calculation method were exploited by the integral image. Then,the frontal faces' cascaded classifier and the profile faces' cascaded classifier was trained on the face database by the Adaboost algorithm respectively. Finally,the two-channel cascaded classifier was built. On OpenCV which is an open source vision database,the experimental results showed that the proposed method had better performance both in accuracy and computing speed,and could detect face with less weak classifiers. Meanwhile,the cascaded classifier had a good ability of robustness on detecting multi-angle face.

  17. Detecting communities in social networks using label propagation with information entropy

    Science.gov (United States)

    Chen, Naiyue; Liu, Yun; Chen, Haiqiang; Cheng, Junjun

    2017-04-01

    Community detection has become an important and effective methodology to understand the structure and function of real world networks. The label propagation algorithm (LPA) is a near-linear time algorithm used to detect non-overlapping community. However, it merely considers the direct neighbor relationship. In this paper, we propose an algorithm to consider information entropy as the measurement of the relationship between direct neighbors and indirect neighbors. In a label update, we proposed a new belonging coefficient to describe the weight of the label. With the belonging coefficient no less than a threshold each node can keep one or more labels to constitute an overlapping community. Experimental results on both real-world and benchmark networks show that our algorithm also possesses high accuracy on detecting community structure in networks.

  18. Effective indexing for face recognition

    Science.gov (United States)

    Sochenkov, I.; Sochenkova, A.; Vokhmintsev, A.; Makovetskii, A.; Melnikov, A.

    2016-09-01

    Face recognition is one of the most important tasks in computer vision and pattern recognition. Face recognition is useful for security systems to provide safety. In some situations it is necessary to identify the person among many others. In this case this work presents new approach in data indexing, which provides fast retrieval in big image collections. Data indexing in this research consists of five steps. First, we detect the area containing face, second we align face, and then we detect areas containing eyes and eyebrows, nose, mouth. After that we find key points of each area using different descriptors and finally index these descriptors with help of quantization procedure. The experimental analysis of this method is performed. This paper shows that performing method has results at the level of state-of-the-art face recognition methods, but it is also gives results fast that is important for the systems that provide safety.

  19. Famous face recognition, face matching, and extraversion.

    Science.gov (United States)

    Lander, Karen; Poyarekar, Siddhi

    2015-01-01

    It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

  20. An information-theoretic approach to the gravitational-wave burst detection problem

    Science.gov (United States)

    Katsavounidis, E.; Lynch, R.; Vitale, S.; Essick, R.; Robinet, F.

    2016-03-01

    The advanced era of gravitational-wave astronomy, with data collected in part by the LIGO gravitational-wave interferometers, has begun as of fall 2015. One potential type of detectable gravitational waves is short-duration gravitational-wave bursts, whose waveforms can be difficult to predict. We present the framework for a new detection algorithm - called oLIB - that can be used in relatively low-latency to turn calibrated strain data into a detection significance statement. This pipeline consists of 1) a sine-Gaussian matched-filter trigger generator based on the Q-transform - known as Omicron -, 2) incoherent down-selection of these triggers to the most signal-like set, and 3) a fully coherent analysis of this signal-like set using the Markov chain Monte Carlo (MCMC) Bayesian evidence calculator LALInferenceBurst (LIB). We optimally extract this information by using a likelihood-ratio test (LRT) to map these search statistics into a significance statement. Using representative archival LIGO data, we show that the algorithm can detect gravitational-wave burst events of realistic strength in realistic instrumental noise with good detection efficiencies across different burst waveform morphologies. With support from the National Science Foundation under Grant PHY-0757058.

  1. Strabismic amblyopia affects relational but not featural and Gestalt processing of faces.

    Science.gov (United States)

    Cattaneo, Zaira; Vecchi, Tomaso; Monegato, Maura; Pece, Alfredo; Merabet, Lotfi B; Carbon, Claus-Christian

    2013-03-22

    The ability to identify faces is of critical importance for normal social interactions. Previous evidence suggests that early visual deprivation may impair certain aspects of face recognition. The effects of strabismic amblyopia on face processing have not been investigated previously. In this study, a group of individuals with amblyopia were administered two tasks known to selectively measure face detection based on a Gestalt representation of a face (Mooney faces task) and featural and relational processing of faces (Jane faces task). Our data show that--when relying on their amblyopic eye only - strabismic amblyopes perform as well as normally sighted individuals in face detection and recognition on the basis of their single features. However, they are significantly impaired in discriminating among different faces on the basis of the spacing of their single features (i.e., configural processing of relational information). Our findings are the first to demonstrate that strabismic amblyopia may cause specific deficits in face recognition, and add to previous reports characterizing visual perceptual deficits associated in amblyopia as high-level and not only as low-level processing.

  2. Perspective projection for variance pose face recognition from camera calibration

    Science.gov (United States)

    Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

    2016-04-01

    Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

  3. New Faces

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The Department of Chinese Language and Literature at Peking University welcomes new students at its 100th anniversary september 1 brings throngs of new students to Peking University. Across the campus,information booths forevery department stand waiting toreceive the freshmen and freshwomen.

  4. Uncertain Reasoning for Detection of Selling Stolen Goods in Online Auctions Using Contextual Information

    Directory of Open Access Journals (Sweden)

    Ladislav Beranek

    2014-01-01

    Full Text Available This work describes the design of a decision support system for detection of fraudulent behavior of selling stolen goods in online auctions. In this system, each seller is associated with a type of certification, namely “proper seller,” “suspect seller,” and “selling stolen goods.” The certification level is determined on the basis of a seller’s behaviors and especially on the basis of contextual information whose origin is outside online auctions portals. In this paper, we focus on representing knowledge about sellers in online auctions, the influence of additional information available from other Internet source, and reasoning on bidders’ trustworthiness under uncertainties using Dempster-Shafer theory of evidence. To demonstrate the practicability of our approach, we performed a case study using real auction data from Czech auction portal Aukro. The analysis results show that our approach can be used to detect selling stolen goods. By applying Dempster-Shafer theory to combine multiple sources of evidence for the detection of this fraudulent behavior, the proposed approach can reduce the number of false positive results in comparison to approaches using a single source of evidence.

  5. Detection technique of transmission in-seam wave for concealed fault in working face of underground coal mine%煤矿井下工作面内隐伏断层透射槽波探测技术

    Institute of Scientific and Technical Information of China (English)

    李刚

    2016-01-01

    The concealed fault influences not only the highly efficient extraction of coal resources, but also brings potential threat for safe production in coal mine. The paper conducted in-seam seismic numeric simulation for the concealed fault in a working face, verified the feasibility of the detection of the consealed fault by transmission method. Then the holographic observation was used to conduct transmission in-seam wave detection in working face 45301, through analysis of frequence dispersion and CT imaging, the distribution of the conceraled faults in working face was found out. The comparison of the detection and the mining show that the transmission in-seam detection tehnique can efficiently detect the consealed faults in working face, provide efficient technical support for safe mining in coal mine.%工作面内隐伏断层不仅严重影响煤炭资源的高效回采,而且给煤矿安全生产带来了潜在威胁。通过对工作面内隐伏断层的槽波地震数值模拟,证实了槽波透射法探测隐伏断层的可行性。采用全息观测方式对45301工作面进行了透射槽波探测,通过频散分析及 CT 成像,查明了工作面隐伏断层分布情况。探采对比表明,透射槽波探测技术能够有效探查工作面内部的隐伏断层,为煤矿安全开采提供有效技术支撑。

  6. [Information quality in general public French-speaking websites dedicated to oral cancer detection].

    Science.gov (United States)

    Vivien, A; Kowalski, V; Chatellier, A; Babin, E; Bénateau, H; Veyssière, A

    2017-02-01

    The goal set by the French highest national authorities in the 2014-2019 Cancer Plan is to "heal more sick persons by promoting early diagnosis through screening". Screening requires information. Nowadays, Internet allows for access to information "in one click". The aim of our study was to evaluate the quality of information found on the Internet. Several sites dedicated to oral cavity cancer screening were selected on Google. The quality of health information found in these sites was evaluated by the DISCERN questionnaire. The quality of decision support provided by the sites was evaluated by the IPDAS checklist. Twenty-seven sites were selected. The average DISCERN score was 25.1/75 (15/75 to 40/75). Eighteen sites (66.6%) had very poor, 8 sites (29.6%) had poor and 1 site had average information quality. IPDAS scores ranged from 11.1 to 38.1. Eight sites (29.6%) had less than 20%, 14 sites (51.9%) had between 20 and 30% and 5 sites (18.5%) had 30% or more validated criteria. No site achieved the pass mark. The quality of general public French-speaking website dedicated to oral cancer detection is very bad. The role of health professionals such as general practitioners and head and neck surgeons, remains essential. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  7. Information-Aided Smart Schemes for Vehicle Flow Detection Enhancements of Traffic Microwave Radar Detectors

    Directory of Open Access Journals (Sweden)

    Tan-Jan Ho

    2016-07-01

    Full Text Available For satisfactory traffic management of an intelligent transport system, it is vital that traffic microwave radar detectors (TMRDs can provide real-time traffic information with high accuracy. In this study, we develop several information-aided smart schemes for traffic detection improvements of TMRDs in multiple-lane environments. Specifically, we select appropriate thresholds not only for removing noise from fast Fourier transforms (FFTs of regional lane contexts but also for reducing FFT side lobes within each lane. The resulting FFTs of reflected vehicle signals and those of clutter are distinguishable. We exploit FFT and lane-/or time stamp-related information for developing smart schemes, which mitigate adverse effects of lane-crossing FFT side lobes of a vehicle signal. As such, the proposed schemes can enhance the detection accuracy of both lane vehicle flow and directional traffic volume. On-site experimental results demonstrate the advantages and feasibility of the proposed methods, and suggest the best smart scheme.

  8. From Parts to Identity: Invariance and Sensitivity of Face Representations to Different Face Halves.

    Science.gov (United States)

    Anzellotti, Stefano; Caramazza, Alfonso

    2016-05-01

    Recognizing the identity of a face is computationally challenging, because it requires distinguishing between similar images depicting different people, while recognizing even very different images depicting a same person. Previous human fMRI studies investigated representations of face identity in the presence of changes in viewpoint and in expression. Despite the importance of holistic processing for face recognition, an investigation of representations of face identity across different face parts is missing. To fill this gap, we investigated representations of face identity and their invariance across different face halves. Information about face identity with invariance across changes in the face half was individuated in the right anterior temporal lobe, indicating this region as the most plausible candidate brain area for the representation of face identity. In a complementary analysis, information distinguishing between different face halves was found to decline along the posterior to anterior axis in the ventral stream.

  9. Adaptive integration of local region information to detect fine-scale brain activity patterns

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    With the rapid development of functional magnetic resonance imaging (fMRI) technology, the spatial resolution of fMRI data is continuously growing. This pro- vides us the possibility to detect the fine-scale patterns of brain activities. The es- tablished univariate and multivariate methods to analyze fMRI data mostly focus on detecting the activation blobs without considering the distributed fine-scale pat- terns within the blobs. To improve the sensitivity of the activation detection, in this paper, multivariate statistical method and univariate statistical method are com- bined to discover the fine-grained activity patterns. For one voxel in the brain, a local homogenous region is constructed. Then, time courses from the local ho- mogenous region are integrated with multivariate statistical method. Univariate statistical method is finally used to construct the interests of statistic for that voxel. The approach has explicitly taken into account the structures of both activity pat- terns and existing noise of local brain regions. Therefore, it could highlight the fine-scale activity patterns of the local regions. Experiments with simulated and real fMRI data demonstrate that the proposed method dramatically increases the sensitivity of detection of fine-scale brain activity patterns which contain the subtle information about experimental conditions.

  10. Brain Stroke Detection by Microwaves Using Prior Information from Clinical Databases

    Directory of Open Access Journals (Sweden)

    Natalia Irishina

    2013-01-01

    Full Text Available Microwave tomographic imaging is an inexpensive, noninvasive modality of media dielectric properties reconstruction which can be utilized as a screening method in clinical applications such as breast cancer and brain stroke detection. For breast cancer detection, the iterative algorithm of structural inversion with level sets provides well-defined boundaries and incorporates an intrinsic regularization, which permits to discover small lesions. However, in case of brain lesion, the inverse problem is much more difficult due to the skull, which causes low microwave penetration and highly noisy data. In addition, cerebral liquid has dielectric properties similar to those of blood, which makes the inversion more complicated. Nevertheless, the contrast in the conductivity and permittivity values in this situation is significant due to blood high dielectric values compared to those of surrounding grey and white matter tissues. We show that using brain MRI images as prior information about brain's configuration, along with known brain dielectric properties, and the intrinsic regularization by structural inversion, allows successful and rapid stroke detection even in difficult cases. The method has been applied to 2D slices created from a database of 3D real MRI phantom images to effectively detect lesions larger than 2.5 × 10−2 m diameter.

  11. A pipeline to link meteorological information and TGFs detected by AGILE

    Science.gov (United States)

    Ursi, A.; Sanò, P.; Casella, D.; Marisaldi, M.; Dietrich, S.; Tavani, M.

    2017-02-01

    Terrestrial gamma ray flashes (TGFs) are brief (approximately hundreds of microseconds) intense gamma ray emissions coming from Earth's atmosphere (˜15 km above sea level), correlated with thunderstorms and atmospheric electric activity. Since their unexpected discovery in the early 1990s by the Burst And Transient Source Experiment/Compton Gamma Ray Observatory, TGFs have been further investigated by several satellites devoted to high-energy astrophysics. The Astrorivelatore Gamma ad Immagini LEggero (AGILE) mission turned out to be particularly suitable to detect these events, due to a very wide energy range (up to 100 MeV), an optimized triggering system, and a unique low-inclination near-equatorial orbit (2.5°). We describe a detection system, developed for the AGILE satellite, whose aim is to provide real-time meteorological information on each detected TGF. We take advantage of data acquired by geostationary satellites to promptly identify the associated storm and follow its evolution in space and time, in order to study its previous onset and development. Data from Low-Earth Orbit meteorological satellites, such as the Global Precipitation Mission, as well as ground measurements from lightning detection networks, can be integrated in the pipeline. This system allows us a prompt characterization of the ground meteorological conditions at TGF time which will provide instrument-independent trigger validation, fill in a database for subsequent statistical analysis, and eventually, on a longer term perspective, serve as a real-time alert service open to the community.

  12. Adaptive intesration of local resion information to detect fine-scale brain activity patterns

    Institute of Scientific and Technical Information of China (English)

    ZHEN ZongLei; TIAN Jie; ZHANG Hui

    2008-01-01

    With the rapid development of functional magnetic resonance imaging (fMRI) technology, the spatial resolution of fMRI data is continuously growing. This pro-vides us the possibility to detect the fine-scale patterns of brain activities. The es-tablished univariate and multivariate methods to analyze fMRI data mostly focus on detecting the activation blobs without considering the distributed fine-scale pat-terns within the blobs. To improve the sensitivity of the activation detection, in this paper, multivariate statistical method and univariate statistical method are com-bined to discover the fine-grained activity patterns. For one voxel in the brain, a local homogenous region is constructed. Then, time courses from the local ho-mogenous region are integrated with multivariate statistical method. Univariate statistical method is finally used to construct the interests of statistic for that voxel. The approach has explicitly taken into account the structures of both activity pat-terns and existing noise of local brain regions. Therefore, it could highlight the fine-scale activity patterns of the local regions. Experiments with simulated and real fMRI data demonstrate that the proposed method dramatically increases the sensitivity of detection of fine-scale brain activity patterns which contain the subtle information about experimental conditions.

  13. 基于DM6437的Adaboost人脸检测算法的设计与实现%Design and implementation of Adaboost face detection algorithm based on DM6437

    Institute of Scientific and Technical Information of China (English)

    倪福银

    2012-01-01

    研究并实现了基于DM6437的Adaboost人脸检测算法。在对相关的人脸检测算法研究的基础上,选择了适应能力强、错误率小的Adaboost算法,通过对输入样本进行Harr特征提取,从中选出最优的Haar特征,然后将训练得到的Haar特征转换成弱分类器,再将弱分类器优化组合成强分类器,最后形成级联强分类器用于人脸检测。通过OpenCV在计算机上仿真实现该算法’,完成了Adaboost人脸检测算法的DSP程序设计,在DM6437硬件平台上实现了人脸实时检测功能。结果表明,运用该算法能够有效地进行人脸检测,可用于工程实践。%The paper studies realizes the Adaboost face detection algorithm based on DM6437. After studying the relevant algo- rithms, the paper chooses Adaboost face detection algorithm which is adaptable and has small error rate. Firstly ,it extracts the Hart features of input samples and chooses optimal Harr features through training, and changes it into weak classifier. Then, it makes weak classifier optimized into strong classifier. Finally it forms cascade classifier which is used in face detection. It simulates Ad- aboost face detection algorithm through OpenCV on the computer. The paper completes the program design of DSP and realizes the function of real-time face detection in DM6437 hardware platform. Results show that this algorithm can be used to realize face de- tection efficiendy, and can be used in engineering practice.

  14. The Impact of Face-to-Face Orientation on Online Retention: A Pilot Study

    Science.gov (United States)

    Ali, Radwan; Leeds, Elke M.

    2009-01-01

    Student retention in online education is a concern for students, faculty and administration. Retention rates are 20% lower in online courses than in traditional face-to-face courses. As part of an integration and engagement strategy, a face-to-face orientation was added to an online undergraduate business information systems course to examine its…

  15. Observed touch on a non-human face is not remapped onto the human observer's own face

    National Research Council Canada - National Science Library

    Beck, Brianna; Bertini, Caterina; Scarpazza, Cristina; Làdavas, Elisabetta

    2013-01-01

    Visual remapping of touch (VRT) is a phenomenon in which seeing a human face being touched enhances detection of tactile stimuli on the observer's own face, especially when the observed face expresses fear...

  16. Temperature anomaly detection and estimation using microwave radiometry and anatomical information

    Science.gov (United States)

    Kelly, Patrick; Sobers, Tamara; St. Peter, Benjamin; Siqueira, Paul; Capraro, Geoffrey

    2011-03-01

    Many medically significant conditions (e.g., ischemia, carcinoma and inflammation) involve localized anomalies in physiological parameters such as the metabolic and blood perfusion rates. These in turn lead to deviations from normal tissue temperature patterns. Microwave radiometry is a passive system for sensing the radiation that objects emit naturally in the microwave frequency band. Since the emitted power depends on temperature, and since radiation at low microwave frequencies can propagate through several centimeters of tissue, microwave radiometry has the potential to provide valuable information about subcutaneous anomalies. The radiometric temperature measurement for a tissue region can be modeled as the inner product of the temperature pattern and a weighting function that depends on tissue properties and the radiometer's antenna. In the absence of knowledge of the weighting functions, it can be difficult to extract specific information about tissue temperature patterns (or the underlying physiological parameters) from the measurements. In this paper, we consider a scenario in which microwave radiometry works in conjunction with another imaging modality (e.g., 3D-CT or MRI) that provides detailed anatomical information. This information is used along with sensor properties in electromagnetic simulation software to generate weighting functions. It also is used in bio-heat equations to generate nominal tissue temperature patterns. We then develop a hypothesis testing framework that makes use of the weighting functions, nominal temperature patterns, and maximum likelihood estimates to detect anomalies. Simulation results are presented to illustrate the proposed detection procedures. The design and performance of an S-band (2-4 GHz) radiometer, and some of the challenges in using such a radiometer for temperature measurements deep in tissue, are also discussed.

  17. Role of Informed Consent in a Decision-making on Participation in The Clinical Trial: Multicenter study in Russia “Face to Face”

    Directory of Open Access Journals (Sweden)

    O. I. Zvonareva

    2016-01-01

    getting into the placebo group were also assessed at significantly lower score by group of patients that acquainted with IC together with the researcher (2,87 ± 1,28, vs 3,33 ± 1,17, p = 0,024; 2,51 ±1,25, vs 3,03 ± 1,34, p = 0,022 respectively. Furthermore, it was found that in the case of the researcher’s assistance acquaintance time with IC reduced threefold. We also evaluated the effect of the complexity of IC text on the decision-making process on participation in clinical trials. The group of respondents, who rated the IC as easy, appeared to be more interested in the final results of the study.Conclusion. Thus, when assessing the impact of the researcher on the review process of informed consent with the decision to participate in clinical trials, we found that in the case of assistance of the researcher, the acquaintance time with IC is reduced three times. In addition, this group of patients during the conversation with the researcher shows better and more clear understanding of the nature and general methodology of clinical trials, resulting in an adequate assessment “objective” risk factors for participation in clinical trials. Thus, this group of patients is more informed, compared with an “independent” group. According to the study “Face to Face”, we can recommend mandatory participation of a researcher during review process of the IC.

  18. Blind information-theoretic multiuser detection algorithms for DS-CDMA and WCDMA downlink systems.

    Science.gov (United States)

    Waheed, Khuram; Salem, Fathi M

    2005-07-01

    Code division multiple access (CDMA) is based on the spread-spectrum technology and is a dominant air interface for 2.5G, 3G, and future wireless networks. For the CDMA downlink, the transmitted CDMA signals from the base station (BS) propagate through a noisy multipath fading communication channel before arriving at the receiver of the user equipment/mobile station (UE/MS). Classical CDMA single-user detection (SUD) algorithms implemented in the UE/MS receiver do not provide the required performance for modern high data-rate applications. In contrast, multi-user detection (MUD) approaches require a lot of a priori information not available to the UE/MS. In this paper, three promising adaptive Riemannian contra-variant (or natural) gradient based user detection approaches, capable of handling the highly dynamic wireless environments, are proposed. The first approach, blind multiuser detection (BMUD), is the process of simultaneously estimating multiple symbol sequences associated with all the users in the downlink of a CDMA communication system using only the received wireless data and without any knowledge of the user spreading codes. This approach is applicable to CDMA systems with relatively short spreading codes but becomes impractical for systems using long spreading codes. We also propose two other adaptive approaches, namely, RAKE -blind source recovery (RAKE-BSR) and RAKE-principal component analysis (RAKE-PCA) that fuse an adaptive stage into a standard RAKE receiver. This adaptation results in robust user detection algorithms with performance exceeding the linear minimum mean squared error (LMMSE) detectors for both Direct Sequence CDMA (DS-CDMA) and wide-band CDMA (WCDMA) systems under conditions of congestion, imprecise channel estimation and unmodeled multiple access interference (MAI).

  19. Detection of Flood Inundation Information of the Kinu River Flooding in 2015 by Social Media

    Science.gov (United States)

    Shi, Y.; Sayama, T.; Takara, K. T.

    2016-12-01

    On September 10th, 2015, due to Kanto Tohoku heavy rainfall in Japan, an overtopping occurred from the Kinu River around 6:00. At the same day, levee breach occurred at the downstream area near Joso city in Ibaraki Prefecture, Japan. This flood disaster caused two people dead, several people injured, and enormous damages on houses and infrastructures in the city. In order to mitigate such flood disasters with large inundations, it is important to identify flood-affected areas on real-time basis. The real-time flood hazard map, which is our ultimate goal of the study, provides information on location of inundated areas during a flood. However, the technology has not been achieved yet mainly due to the difficulty in identifying the flood extent on real time. With the advantage of efficiency and wide coverage, social media, such as Twitter, appears as a good data source for collecting real-time flood information. However, there are some concerns on social media information, including the trustworthiness, and the amount of useful information in the case tweets from flood affected areas. This study collected tweet regarding the Kinu River flooding and investigated how many people in affected area posted tweets on the flooding and how the detected information is useful for the eventual goal on the real-time flood hazard mapping. The tweets were collected by three ways: advanced search on twitter web page; DISAster-information ANAlyzer system; and Twitter Application Programming Interfaces. As a result, 109 disaster relevant tweets were collected. Out of the 109 tweets, 32% of the total tweets are posted at real-time, 43% of total tweets are posted with photos and 46 tweets are related to the inundation information. 46% of the inundation related tweets were able to identify locations. In order to investigate the reliability of tweet post, the location identified tweets were marked on map to compare with the real inundation extent that measured by the Geospatial

  20. The Construction of Strong Classifier Algorithm for Face Detection Based on the Principal Component Analysis%基于主元分析构造强分类器的人脸检测算法

    Institute of Scientific and Technical Information of China (English)

    郭东峰

    2013-01-01

    This paper studies the feature based face detection algorithm, According to the characteristics of weak classifi-cation ability, based on the principal component analysis feature vector space is extracted to construct weak classifier, combined with AdaBoost algorithm to construct the strong classifier, an algorithm for face detection is presented. The performance of the algorithm is tested based on MIT+CMU face database, the results show that the algorithm in the run-ning time and detection accuracy is significantly better than the algorithm based on neural network and support vector machine algorithm.%本文研究了基于特征脸的人脸检测算法,针对其分类能力差的特点,基于主元分析提取特征向量空间构造弱分类器,结合AdaBoost算法构造强分类器,提出了一种人脸检测算法。利用MIT+CMU人脸数据库测试该算法的性能,结果表明本算法在运行时间与检测正确率方面明显优于基于神经网路的算法和支持向量机算法。

  1. Learning to Discriminate Face Views

    Directory of Open Access Journals (Sweden)

    Fang Fang

    2011-05-01

    Full Text Available Although visual feature leaning has been well studied, we still know little about the mechanisms of perceptual learning of complex object. Here, human perceptual learning in discrimination of in-depth orientation of face view was studied using psychophysics, EEG and fMRI. We trained subjects to discriminate face orientations around a face view (i.e. 30° over eight daily sessions, which resulted in a significant improvement in sensitivity to the face view orientation. This improved sensitivity was highly specific to the trained orientation and persisted up to six months. Different from perceptual learning of simple visual features, this orientation-specific learning effect could completely transfer across changes in face size, visual field and face identity. A complete transfer also occurred between two partial face images that were mutually exclusive but constituted a complete face. However, the transfer of the learning effect between upright and inverted faces and between a face and a paperclip object was very weak. Before and after training, we measured EEG and fMRI BOLD signals responding to both the trained and the untrained face views. Analyses of ERPs and induced gamma activity showed that face view discrimination training led to a larger reduction of N170 latency at the left occipital-temporal area and a concurrent larger decrease of induced gamma activity at the left frontal area with the trained face view, compared with the untrained ones. BOLD signal amplitude and MVPA analyses showed that, in face-selective cortical areas, training did not lead to a significant amplitude change, but induced a more reliable spatial pattern of neural activity in the left FFA. These results suggest that the visual system had learned how to compute face orientation from face configural information more accurately and that a large amount of plastic changes took place at a level of higher visual processing where size-, location-, and identity

  2. Face Recognition Based on Facial Features

    Directory of Open Access Journals (Sweden)

    Muhammad Sharif

    2012-08-01

    Full Text Available Commencing from the last decade several different methods have been planned and developed in the prospect of face recognition that is one of the chief stimulating zone in the area of image processing. Face recognitions processes have various applications in the prospect of security systems and crime investigation systems. The study is basically comprised of three phases, i.e., face detection, facial features extraction and face recognition. The first phase is the face detection process where region of interest i.e., features region is extracted. The 2nd phase is features extraction. Here face features i.e., eyes, nose and lips are extracted out commencing the extracted face area. The last module is the face recognition phase which makes use of the extracted left eye for the recognition purpose by combining features of Eigenfeatures and Fisherfeatures.

  3. Loop closure detection by algorithmic information theory: implemented on range and camera image data.

    Science.gov (United States)

    Ravari, Alireza Norouzzadeh; Taghirad, Hamid D

    2014-10-01

    In this paper the problem of loop closing from depth or camera image information in an unknown environment is investigated. A sparse model is constructed from a parametric dictionary for every range or camera image as mobile robot observations. In contrast to high-dimensional feature-based representations, in this model, the dimension of the sensor measurements' representations is reduced. Considering the loop closure detection as a clustering problem in high-dimensional space, little attention has been paid to the curse of dimensionality in the existing state-of-the-art algorithms. In this paper, a representation is developed from a sparse model of images, with a lower dimension than original sensor observations. Exploiting the algorithmic information theory, the representation is developed such that it has the geometrically transformation invariant property in the sense of Kolmogorov complexity. A universal normalized metric is used for comparison of complexity based representations of image models. Finally, a distinctive property of normalized compression distance is exploited for detecting similar places and rejecting incorrect loop closure candidates. Experimental results show efficiency and accuracy of the proposed method in comparison to the state-of-the-art algorithms and some recently proposed methods.

  4. Indoor and outdoor people detection and shadow suppression by exploiting HSV color information

    Institute of Scientific and Technical Information of China (English)

    Baisheng CHEN

    2008-01-01

    An adaptive background model based on max-imum statistical probability and a shadow suppression scheme for indoor and outdoor people detection by exploiting hue saturation value (HSV) color information is proposed. To obtain the initial background scene, the frequency of R, G, and B component values for each pixel at the same position in the learning sequence are respec-tively calculated; the R, G, and B component values with the biggest ratios are incorporated to model the initial background. The background maintenance, or the so-called background re-initiation, is also proposed to adapt to scene changes such as illumination changes and scene geometry changes. Moving cast shadows generally exhibit a challenge for accurate moving target detection. Based on the observation that a shadow cast on a background region lowers its brightness but does not change its chro-maticity significantly, we address this problem in the ar-ticle by exploiting HSV color information. In addition, quantitative metrics is introduced to evaluate the algo-rithm on a benchmark suite of indoor and outdoor video sequences. The experimental results are given to show the performance of the algorithm.

  5. Human detection from a mobile robot using fusion of laser and vision information.

    Science.gov (United States)

    Fotiadis, Efstathios P; Garzón, Mario; Barrientos, Antonio

    2013-09-04

    This paper presents a human detection system that can be employed on board a mobile platform for use in autonomous surveillance of large outdoor infrastructures. The prediction is based on the fusion of two detection modules, one for the laser and another for the vision data. In the laser module, a novel feature set that better encapsulates variations due to noise, distance and human pose is proposed. This enhances the generalization of the system, while at the same time, increasing the outdoor performance in comparison with current methods. The vision module uses the combination of the histogram of oriented gradients descriptor and the linear support vector machine classifier. Current approaches use a fixed-size projection to define regions of interest on the image data using the range information from the laser range finder. When applied to small size unmanned ground vehicles, these techniques suffer from misalignment, due to platform vibrations and terrain irregularities. This is effectively addressed in this work by using a novel adaptive projection technique, which is based on a probabilistic formulation of the classifier performance. Finally, a probability calibration step is introduced in order to optimally fuse the information from both modules. Experiments in real world environments demonstrate the robustness of the proposed method.

  6. Human Detection from a Mobile Robot Using Fusion of Laser and Vision Information

    Directory of Open Access Journals (Sweden)

    Antonio Barrientos

    2013-09-01

    Full Text Available This paper presents a human detection system that can be employed on board a mobile platform for use in autonomous surveillance of large outdoor infrastructures. The prediction is based on the fusion of two detection modules, one for the laser and another for the vision data. In the laser module, a novel feature set that better encapsulates variations due to noise, distance and human pose is proposed. This enhances the generalization of the system, while at the same time, increasing the outdoor performance in comparison with current methods. The vision module uses the combination of the histogram of oriented gradients descriptor and the linear support vector machine classifier. Current approaches use a fixed-size projection to define regions of interest on the image data using the range information from the laser range finder. When applied to small size unmanned ground vehicles, these techniques suffer from misalignment, due to platform vibrations and terrain irregularities. This is effectively addressed in this work by using a novel adaptive projection technique, which is based on a probabilistic formulation of the classifier performance. Finally, a probability calibration step is introduced in order to optimally fuse the information from both modules. Experiments in real world environments demonstrate the robustness of the proposed method.

  7. 基于深度学习与融入梯度信息的人脸姿态分类检测%Pose Classification of Human Face Based on Deep Learning and Gradient Information Fusion

    Institute of Scientific and Technical Information of China (English)

    苏铁明; 程福运; 韩兆翠; 欧宗瑛

    2016-01-01

    针对人脸姿态分类问题,本文提出了一种基于深度学习与融入梯度信息的人脸姿态分类学习方法。首先提取人脸姿态图像灰度与灰度差组合特征,然后通过三层受限玻尔兹曼机(Restricted Boltz-mann machines,RBM)对大量样本的特征进行融合训练学习,提取反映人脸姿态内涵的深度学习特征。最后通过Softmax分类器建立深度学习特征与人脸姿态标签的对应关系。在对 CAS-PEAL-R1人脸数据库进行学习和分类检测中,获得普遍高于95%的分类精度。%Aiming at upgrading the performance of face pose classification,we proposed an algorithm of face pose classification based on deep learning and gradient information fusion.First,the pixel gray in-tensity features and the features of gray intensity difference nearby each pixel from a face image are ex-tracted.Then,these features of face images are processed with deep learning technique through a dedica-ted three-layer restricted Boltzmann machines network,which has been trained by a large number of samples.Finally,a corresponding relation between fusion deep learning features and the labels of face pose classifications is built through a Softmax classifier.The experiment results show that the proposed algorithm achieves a state of the art classification accuracy,generally higher than 9 5%,when learning and testing on CAS-PEAL-R1 face database.

  8. Direct Joint Detection from Humanoid 3D Models without using Skeleton Information

    Directory of Open Access Journals (Sweden)

    Terumasa Aoki

    2014-05-01

    Full Text Available Skeletonization, or automatic skeleton extraction, is one of the most essential technologies in 3DCG. This technology makes it possible to automatically extract skeletons (i.e. bones, joints and their hierarchical structures from 3D models. Such skeletons are important shape and pose descriptors for object representation, object recognition etc. They are used in many applications such as 3D model search, virtual character's pose estimation and collision detection between two or more 3D models. However, existing skeletonization methods have some drawbacks. Most of the existing skeletonization methods have difficulties in correctly extracting the positions of joints. In most methods, bones are extracted from a 3D model first and joints are defined as the cross points of bones. However some errors always occur when bones are extracted. Hence joints cannot be found in this scheme so often. Furthermore, they are not allowing for controlling the number of bones/joints and their structure. Therefore applying motion data acquired from motion capture devices to 3D models still involves a lot of cumbersome manual work. In this paper, we propose a novel joint detection method suited for kinematic skeleton generation, skeleton rigging etc. Unlike the existing methods, the proposed method detects joint positions directly without using skeleton (bone information. So the proposed method can avoid propagating errors occurred by skeletonization process. Also, the proposed method is able to extract the same numbers of joints/bones and the same structure as in given motion data, i.e. one can directly apply existing motion data without the need of manual adjustment. In general, 3D models describe shape information and pose information simultaneously. Distinguishing one from the other seems to be very difficult. However, the proposed method solves this problem by extracting only the pose information of 3D models by using a vertex Gauss sphere representation and

  9. An information-theoretic approach to the gravitational-wave burst detection problem

    CERN Document Server

    Lynch, Ryan; Essick, Reed; Katsavounidis, Erik; Robinet, Florent

    2015-01-01

    The advanced era of gravitational-wave astronomy, with data collected in part by the LIGO gravitational-wave interferometers, has begun as of fall 2015. One potential type of detectable gravitational waves is short-duration gravitational-wave bursts, whose waveforms can be difficult to predict. We present the framework for a new detection algorithm -- called \\textit{oLIB} -- that can be used in relatively low-latency to turn calibrated strain data into a detection significance statement. This pipeline consists of 1) a sine-Gaussian matched-filter trigger generator based on the Q-transform -- known as \\textit{Omicron} --, 2) incoherent down-selection of these triggers to the most signal-like set, and 3) a fully coherent analysis of this signal-like set using the Markov chain Monte Carlo (MCMC) Bayesian evidence calculator \\textit{LALInferenceBurst} (LIB). These steps effectively compress the full data stream into a set of search statistics for the most signal-like events, and we use elements from information t...

  10. Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

    Science.gov (United States)

    Cunningham, Corbin A; Drew, Trafton; Wolfe, Jeremy M

    2017-02-01

    In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.

  11. Copy number variation detection in whole-genome sequencing data using the Bayesian information criterion.

    Science.gov (United States)

    Xi, Ruibin; Hadjipanayis, Angela G; Luquette, Lovelace J; Kim, Tae-Min; Lee, Eunjung; Zhang, Jianhua; Johnson, Mark D; Muzny, Donna M; Wheeler, David A; Gibbs, Richard A; Kucherlapati, Raju; Park, Peter J

    2011-11-15

    DNA copy number variations (CNVs) play an important role in the pathogenesis and progression of cancer and confer susceptibility to a variety of human disorders. Array comparative genomic hybridization has been used widely to identify CNVs genome wide, but the next-generation sequencing technology provides an opportunity to characterize CNVs genome wide with unprecedented resolution. In this study, we developed an algorithm to detect CNVs from whole-genome sequencing data and applied it to a newly sequenced glioblastoma genome with a matched control. This read-depth algorithm, called BIC-seq, can accurately and efficiently identify CNVs via minimizing the Bayesian information criterion. Using BIC-seq, we identified hundreds of CNVs as small as 40 bp in the cancer genome sequenced at 10× coverage, whereas we could only detect large CNVs (> 15 kb) in the array comparative genomic hybridization profiles for the same genome. Eighty percent (14/16) of the small variants tested (110 bp to 14 kb) were experimentally validated by quantitative PCR, demonstrating high sensitivity and true positive rate of the algorithm. We also extended the algorithm to detect recurrent CNVs in multiple samples as well as deriving error bars for breakpoints using a Gibbs sampling approach. We propose this statistical approach as a principled yet practical and efficient method to estimate CNVs in whole-genome sequencing data.

  12. Breast mass detection in tomosynthesis projection images using information-theoretic similarity measures

    Science.gov (United States)

    Singh, Swatee; Tourassi, Georgia D.; Lo, Joseph Y.

    2007-03-01

    The purpose of this project is to study Computer Aided Detection (CADe) of breast masses for digital tomosynthesis. It is believed that tomosynthesis will show improvement over conventional mammography in detection and characterization of breast masses by removing overlapping dense fibroglandular tissue. This study used the 60 human subject cases collected as part of on-going clinical trials at Duke University. Raw projections images were used to identify suspicious regions in the algorithm's high-sensitivity, low-specificity stage using a Difference of Gaussian (DoG) filter. The filtered images were thresholded to yield initial CADe hits that were then shifted and added to yield a 3D distribution of suspicious regions. These were further summed in the depth direction to yield a flattened probability map of suspicious hits for ease of scoring. To reduce false positives, we developed an algorithm based on information theory where similarity metrics were calculated using knowledge databases consisting of tomosynthesis regions of interest (ROIs) obtained from projection images. We evaluated 5 similarity metrics to test the false positive reduction performance of our algorithm, specifically joint entropy, mutual information, Jensen difference divergence, symmetric Kullback-Liebler divergence, and conditional entropy. The best performance was achieved using the joint entropy similarity metric, resulting in ROC A z of 0.87 +/- 0.01. As a whole, the CADe system can detect breast masses in this data set with 79% sensitivity and 6.8 false positives per scan. In comparison, the original radiologists performed with only 65% sensitivity when using mammography alone, and 91% sensitivity when using tomosynthesis alone.

  13. ENSO detection and use to inform the operation of large scale water systems

    Science.gov (United States)

    Pham, Vuong; Giuliani, Matteo; Castelletti, Andrea

    2016-04-01

    El Nino Southern Oscillation (ENSO) is a large-scale, coupled ocean-atmosphere phenomenon occurring in the tropical Pacific Ocean, and is considered one of the most significant factors causing hydro-climatic anomalies throughout the world. Water systems operations could benefit from a better understanding of this global phenomenon, which has the potential for enhancing the accuracy and lead-time of long-range streamflow predictions. In turn, these are key to design interannual water transfers in large scale water systems to contrast increasingly frequent extremes induced by changing climate. Despite the ENSO teleconnection is well defined in some locations such as Western USA and Australia, there is no consensus on how it can be detected and used in other river basins, particularly in Europe, Africa, and Asia. In this work, we contribute a general framework relying on Input Variable Selection techniques for detecting ENSO teleconnection and using this information for improving water reservoir operations. Core of our procedure is the Iterative Input variable Selection (IIS) algorithm, which is employed to find the most relevant determinants of streamflow variability for deriving predictive models based on the selected inputs as well as to find the most valuable information for conditioning operating decisions. Our framework is applied to the multipurpose operations of the Hoa Binh reservoir in the Red River basin (Vietnam), taking into account hydropower production, water supply for irrigation, and flood mitigation during the monsoon season. Numerical results show that our framework is able to quantify the relationship between the ENSO fluctuations and the Red River basin hydrology. Moreover, we demonstrate that such ENSO teleconnection represents valuable information for improving the operations of Hoa Binh reservoir.

  14. Face Detection Based on Skin Color Model and Radial Basis Function Network%基于肤色模型和径向基函数网络的脸部检测

    Institute of Scientific and Technical Information of China (English)

    陈栋; 王丽荣

    2014-01-01

    The calculation of the closure of human eyes is commonly adopted to detect driver fatigue. In order to realize human eyes closure calculation, correct and rapid detection of human face is accomplished firstly, for the specific environment of cabs, this paper proposes a fast face detection algorithm based on skin color model and radial basis function network, which makes input image carry out RGB and YCbCr color space conversion, then establishes relevant skin model to achieve the coarse positioning of face region, finally, combines radial basis function network to train input image, so that whether it is the skin color is determined according to the training results, and the detection on face is finished. Simulation results show that the algorithm improves the human face correct detection un-der strong light, laying a foundation for drivers’ fatigue driving research.%驾驶员疲劳状态检测一般采用对人眼的闭合度进行计算,若实现对人眼的闭合度计算首先是对人脸的正确快速检测,针对驾驶室的特定环境,本文研究一种基于肤色模型和径向基函数网络为基础的快速人脸检测算法,该算法首先对输入图像进行RGB和YCbCr颜色空间的转换,其次建立相关的肤色模型,实现人脸区域的粗定位,然后结合径向基函数网络对输入的图像进行训练,这样就可以根据训练的结果判断是否是肤色,从而实现人脸检测。仿真结果表明,所研究的算法较好的提高了强光下人脸的正确检测,为驾驶员疲劳驾驶的研究奠定前期基础。

  15. Explaining Sad People’s Memory Advantage for Faces

    Science.gov (United States)

    Hills, Peter J.; Marquardt, Zoe; Young, Isabel; Goodenough, Imogen

    2017-01-01

    Sad people recognize faces more accurately than happy people (Hills et al., 2011). We devised four hypotheses for this finding that are tested between in the current study. The four hypotheses are: (1) sad people engage in more expert processing associated with face processing; (2) sad people are motivated to be more accurate than happy people in an attempt to repair their mood; (3) sad people have a defocused attentional strategy that allows more information about a face to be encoded; and (4) sad people scan more of the face than happy people leading to more facial features to be encoded. In Experiment 1, we found that dysphoria (sad mood often associated with depression) was not correlated with the face-inversion effect (a measure of expert processing) nor with response times but was correlated with defocused attention and recognition accuracy. Experiment 2 established that dysphoric participants detected changes made to more facial features than happy participants. In Experiment 3, using eye-tracking we found that sad-induced participants sampled more of the face whilst avoiding the eyes. Experiment 4 showed that sad-induced people demonstrated a smaller own-ethnicity bias. These results indicate that sad people show different attentional allocation to faces than happy and neutral people. PMID:28261138

  16. Compact Information Representations

    Science.gov (United States)

    2016-08-02

    network traffic, information retrieval, and databases are faced with very large, inherently high-dimensional, or naturally streaming datasets. This...proposal aims at developing mathematically rigorous and general- purpose statistical methods based on stable random projections, to achieve compact...detections (e.g., DDoS attacks), machine learning, databases , and search. Fundamentally, compact data representations are highly beneficial because they

  17. Simultaneous face and voice processing in schizophrenia.

    Science.gov (United States)

    Liu, Taosheng; Pinheiro, Ana P; Zhao, Zhongxin; Nestor, Paul G; McCarley, Robert W; Niznikiewicz, Margaret

    2016-05-15

    While several studies have consistently demonstrated abnormalities in the unisensory processing of face and voice in schizophrenia (SZ), the extent of abnormalities in the simultaneous processing of both types of information remains unclear. To address this issue, we used event-related potentials (ERP) methodology to probe the multisensory integration of face and non-semantic sounds in schizophrenia. EEG was recorded from 18 schizophrenia patients and 19 healthy control (HC) subjects in three conditions: neutral faces (visual condition-VIS); neutral non-semantic sounds (auditory condition-AUD); neutral faces presented simultaneously with neutral non-semantic sounds (audiovisual condition-AUDVIS). When compared with HC, the schizophrenia group showed less negative N170 to both face and face-voice stimuli; later P270 peak latency in the multimodal condition of face-voice relative to unimodal condition of face (the reverse was true in HC); reduced P400 amplitude and earlier P400 peak latency in the face but not in the voice-face condition. Thus, the analysis of ERP components suggests that deficits in the encoding of facial information extend to multimodal face-voice stimuli and that delays exist in feature extraction from multimodal face-voice stimuli in schizophrenia. In contrast, categorization processes seem to benefit from the presentation of simultaneous face-voice information. Timepoint by timepoint tests of multimodal integration did not suggest impairment in the initial stages of processing in schizophrenia.

  18. Face recognition increases during saccade preparation.

    Directory of Open Access Journals (Sweden)

    Hai Lin

    Full Text Available Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

  19. Face recognition increases during saccade preparation.

    Science.gov (United States)

    Lin, Hai; Rizak, Joshua D; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

    2014-01-01

    Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

  20. Own-race and own-age biases facilitate visual awareness of faces under interocular suppression

    OpenAIRE

    Timo eStein; Albert eEnd; Philipp eSterzer

    2014-01-01

    The detection of a face in a visual scene is the first stage in the face processing hierarchy. Although all subsequent, more elaborate face processing depends on the initial detection of a face, surprisingly little is known about the perceptual mechanisms underlying face detection. Recent evidence suggests that relatively hard-wired face detection mechanisms are broadly tuned to all face-like visual patterns as long as they respect the typical spatial configuration of the eyes above the mouth...