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Sample records for face detection face

  1. 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.

  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. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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....

  10. 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.

  11. 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...

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  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. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  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. 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.

  9. 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

  10. 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.

  11. 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...

  12. “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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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°.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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,

  13. 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%.

  14. 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.

  15. 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

  16. 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

  17. 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 ...

  18. About Face

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    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 ...

  19. 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...

  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 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.

  2. 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.

  3. 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.

  4. 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…

  5. About Face

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    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 ...

  6. 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 ...

  7. 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.

  8. 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.

  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. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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).

  15. 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.

  16. 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.

  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. 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…

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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...

  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. 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.

  13. 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).

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. European cinema: face to face with Hollywood

    NARCIS (Netherlands)

    T. Elsaesser

    2005-01-01

    In the face of renewed competition from Hollywood since the early 1980s and the challenges posed to Europe's national cinemas by the fall of the Wall in 1989, independent filmmaking in Europe has begun to re-invent itself. European Cinema: Face to Face with Hollywood re-assesses the different debate

  7. Mapping Teacher-Faces

    Science.gov (United States)

    Thompson, Greg; Cook, Ian

    2013-01-01

    This paper uses Deleuze and Guattari's concept of faciality to analyse the teacher's face. According to Deleuze and Guattari, the teacher-face is a special type of face because it is an "overcoded" face produced in specific landscapes. This paper suggests four limit-faces for teacher faciality that actualise different mixes of significance and…

  8. 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

  9. 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.

  10. 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).

  11. Face-Lift

    Science.gov (United States)

    Tests and Procedures Face-lift By Mayo Clinic Staff A face-lift (rhytidectomy) is a cosmetic surgical procedure to improve the look of your face and neck. During a face-lift, facial soft tissues are lifted, excess skin is ...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. About (above) a face - a face

    OpenAIRE

    2009-01-01

    This text intents to unfold some considerations regardind the perception of the image of the Lóri’s face, from the book Uma aprendizagem ou o livro dos prazeres, published by Clarice Lispector in 1969. For that, will be studied the politicians devices who involve the apprehension of the face as a qualifying of the subject and, at the same time, its relation with the lenguage.

  2. About (above a face - a face

    Directory of Open Access Journals (Sweden)

    Diego Cervelin

    2009-07-01

    Full Text Available This text intents to unfold some considerations regardind the perception of the image of the Lóri’s face, from the book Uma aprendizagem ou o livro dos prazeres, published by Clarice Lispector in 1969. For that, will be studied the politicians devices who involve the apprehension of the face as a qualifying of the subject and, at the same time, its relation with the lenguage.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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,…

  8. 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.

  9. The composite face illusion.

    Science.gov (United States)

    Murphy, Jennifer; Gray, Katie L H; Cook, Richard

    2017-04-01

    Few findings in cognitive science have proved as influential as the composite face effect. When the top half of one face is aligned with the bottom half of another, and presented upright, the resulting composite arrangement induces a compelling percept of a novel facial configuration. Findings obtained using composite face procedures have contributed significantly to our understanding of holistic face processing, the detrimental effects of face inversion, the development of face perception, and aberrant face perception in clinical populations. Composite paradigms continue to advance our knowledge of face perception, as exemplified by their recent use for investigating the perceptual mechanisms underlying dynamic face processing. However, the paradigm has been the subject of intense scrutiny, particularly over the last decade, and there is a growing sense that the composite face illusion, whilst easy to illustrate, is deceptively difficult to measure and interpret. In this review, we provide a focussed overview of the existing composite face literature, and identify six priorities for future research. Addressing these gaps in our knowledge will aid the evaluation and refinement of theoretical accounts of the illusion.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Oracle ADF Faces cookbook

    CERN Document Server

    Gawish, Amr

    2014-01-01

    This is a cookbook that covers more than 80 different recipes to teach you about different aspects of Oracle ADF Faces. It follows a practical approach and covers how to build your components for reuse in different applications. This book will also help you in tuning the performance of your ADF Faces application. If you are an ADF developer who wants to harness the power of Oracle ADF Faces to create exceptional user interfaces and reactive applications, this book will provide you with the recipes needed to do just that. You will not need to be familiar with Oracle ADF Faces, but you should be

  2. 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.

  3. 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…

  4. 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.

  5. Generalization of affective learning about faces to perceptually similar faces.

    Science.gov (United States)

    Verosky, Sara C; Todorov, Alexander

    2010-06-01

    Different individuals have different (and different-looking) significant others, friends, and foes. The objective of this study was to investigate whether these social face environments can shape individual face preferences. First, participants learned to associate faces with positive, neutral, or negative behaviors. Then, they evaluated morphs combining novel faces with the learned faces. The morphs (65% and 80% novel faces) were within the categorical boundary of the novel faces: They were perceived as those faces in a preliminary study. Moreover, a second preliminary study showed that following the learning, the morphs' categorization as similar to the learned faces was indistinguishable from the categorization of actual novel faces. Nevertheless, in the main experiment, participants evaluated morphs of "positive" faces more positively than morphs of "negative" faces. This learning generalization effect increased as a function of the similarity of the novel faces to the learned faces. The findings suggest that general learning mechanisms based on similarity can account for idiosyncratic face preferences.

  6. 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.

  7. 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...

  8. 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.

  9. Social judgments from faces.

    Science.gov (United States)

    Todorov, Alexander; Mende-Siedlecki, Peter; Dotsch, Ron

    2013-06-01

    People make rapid and consequential social judgments from minimal (non-emotional) facial cues. There has been rapid progress in identifying the perceptual basis of these judgments using data-driven, computational models. In contrast, our understanding of the neural underpinnings of these judgments is rather limited. Meta-analyses of neuroimaging studies find a wide range of seemingly inconsistent responses in the amygdala that co-vary with social judgments from faces. Guided by computational models of social judgments, these responses can be accounted by positing that the amygdala (and posterior face selective regions) tracks face typicality. Atypical faces, whether positively or negatively evaluated, elicit stronger responses in the amygdala. We conclude with the promise of data-driven methods for modeling neural responses to social judgments from faces.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  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. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. Is Face Distinctiveness Gender Based?

    Science.gov (United States)

    Baudouin, Jean-Yves; Gallay, Mathieu

    2006-01-01

    Two experiments were carried out to study the role of gender category in evaluations of face distinctiveness. In Experiment 1, participants had to evaluate the distinctiveness and the femininity-masculinity of real or artificial composite faces. The composite faces were created by blending either faces of the same gender (sexed composite faces,…

  6. 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.

  7. 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.

  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. Facing Aggression: Cues Differ for Female versus Male Faces

    Science.gov (United States)

    Geniole, Shawn N.; Keyes, Amanda E.; Mondloch, Catherine J.; Carré, Justin M.; McCormick, Cheryl M.

    2012-01-01

    The facial width-to-height ratio (face ratio), is a sexually dimorphic metric associated with actual aggression in men and with observers' judgements of aggression in male faces. Here, we sought to determine if observers' judgements of aggression were associated with the face ratio in female faces. In three studies, participants rated photographs of female and male faces on aggression, femininity, masculinity, attractiveness, and nurturing. In Studies 1 and 2, for female and male faces, judgements of aggression were associated with the face ratio even when other cues in the face related to masculinity were controlled statistically. Nevertheless, correlations between the face ratio and judgements of aggression were smaller for female than for male faces (F1,36 = 7.43, p = 0.01). In Study 1, there was no significant relationship between judgements of femininity and of aggression in female faces. In Study 2, the association between judgements of masculinity and aggression was weaker in female faces than for male faces in Study 1. The weaker association in female faces may be because aggression and masculinity are stereotypically male traits. Thus, in Study 3, observers rated faces on nurturing (a stereotypically female trait) and on femininity. Judgements of nurturing were associated with femininity (positively) and masculinity (negatively) ratings in both female and male faces. In summary, the perception of aggression differs in female versus male faces. The sex difference was not simply because aggression is a gendered construct; the relationships between masculinity/femininity and nurturing were similar for male and female faces even though nurturing is also a gendered construct. Masculinity and femininity ratings are not associated with aggression ratings nor with the face ratio for female faces. In contrast, all four variables are highly inter-correlated in male faces, likely because these cues in male faces serve as “honest signals”. PMID:22276184

  10. Face Recognition using Curvelet Transform

    CERN Document Server

    Cohen, Rami

    2011-01-01

    Face recognition has been studied extensively for more than 20 years now. Since the beginning of 90s the subject has became a major issue. This technology is used in many important real-world applications, such as video surveillance, smart cards, database security, internet and intranet access. This report reviews recent two algorithms for face recognition which take advantage of a relatively new multiscale geometric analysis tool - Curvelet transform, for facial processing and feature extraction. This transform proves to be efficient especially due to its good ability to detect curves and lines, which characterize the human's face. An algorithm which is based on the two algorithms mentioned above is proposed, and its performance is evaluated on three data bases of faces: AT&T (ORL), Essex Grimace and Georgia-Tech. k-nearest neighbour (k-NN) and Support vector machine (SVM) classifiers are used, along with Principal Component Analysis (PCA) for dimensionality reduction. This algorithm shows good results, ...

  11. 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%.

  12. 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...

  13. Facing Sound - Voicing Art

    DEFF Research Database (Denmark)

    Lønstrup, Ansa

    2013-01-01

    This article is based on examples of contemporary audiovisual art, with a special focus on the Tony Oursler exhibition Face to Face at Aarhus Art Museum ARoS in Denmark in March-July 2012. My investigation involves a combination of qualitative interviews with visitors, observations of the audienc......´s interactions with the exhibition and the artwork in the museum space and short analyses of individual works of art based on reception aesthetics and phenomenology and inspired by newer writings on sound, voice and listening....

  14. 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.

  15. 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…

  16. Pedagogical Characteristics of Online and Face-to-Face Classes

    Science.gov (United States)

    Wuensch, Karl; Aziz, Shahnaz; Ozan, Erol; Kishore, Masao; Tabrizi, M. H. Nassehzadeh

    2008-01-01

    Currently, many students have had experience with both face-to-face and online classes. We asked such students at 46 different universities in the United States to evaluate the pedagogical characteristics of their most recently completed face-to-face class and their most recently completed online class. The results show that students rate online…

  17. Bayesian Face Recognition and Perceptual Narrowing in Face-Space

    Science.gov (United States)

    Balas, Benjamin

    2012-01-01

    During the first year of life, infants' face recognition abilities are subject to "perceptual narrowing", the end result of which is that observers lose the ability to distinguish previously discriminable faces (e.g. other-race faces) from one another. Perceptual narrowing has been reported for faces of different species and different races, in…

  18. Real Time Face Quality Assessment for Face Log Generation

    DEFF Research Database (Denmark)

    Kamal, Nasrollahi; Moeslund, Thomas B.

    2009-01-01

    Summarizing a long surveillance video to just a few best quality face images of each subject, a face-log, is of great importance in surveillance systems. Face quality assessment is the back-bone for face log generation and improving the quality assessment makes the face logs more reliable....... Developing a real time face quality assessment system using the most important facial features and employing it for face logs generation are the concerns of this paper. Extensive tests using four databases are carried out to validate the usability of the system....

  19. 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.

  20. Face recognition system and method using face pattern words and face pattern bytes

    Energy Technology Data Exchange (ETDEWEB)

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  1. 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

  2. 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

  3. Two Faces of Japan.

    Science.gov (United States)

    Beasley, Conger, Jr.

    1992-01-01

    Discusses the inconsistency between Japanese exploitation of world natural resources and gestures to provide leadership in ecologically innovative technology. Explores Japanese culture, power structure, population trends, environmental ethics, industrialism, and international business practices as they relate to the philosophical face of…

  4. Bayesian Face Sketch Synthesis.

    Science.gov (United States)

    Wang, Nannan; Gao, Xinbo; Sun, Leiyu; Li, Jie

    2017-03-01

    Exemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical models. The proposed Bayesian framework consists of two parts: the neighbor selection model and the weight computation model. Within the proposed framework, we further propose a Bayesian face sketch synthesis method. The essential rationale behind the proposed Bayesian method is that we take the spatial neighboring constraint between adjacent image patches into consideration for both aforementioned models, while the state-of-the-art methods neglect the constraint either in the neighbor selection model or in the weight computation model. Extensive experiments on the Chinese University of Hong Kong face sketch database demonstrate that the proposed Bayesian method could achieve superior performance compared with the state-of-the-art methods in terms of both subjective perceptions and objective evaluations.

  5. Facing Up to Death

    Science.gov (United States)

    Ross, Elizabeth Kubler

    1972-01-01

    Doctor urges that Americans accept death as a part of life and suggests ways of helping dying patients and their families face reality calmly, with peace. Dying children and their siblings, as well as children's feelings about relatives' deaths, are also discussed. (PD)

  6. Autonomous Face Segmentation

    Science.gov (United States)

    1992-09-01

    and Rhea Diamond. "From Piecemeal to Configurational Repre- sentation of Faces," Science, 195:312-314 (Jan 1977). 3. Damasio , Antonio R...34Prosopagnosia," Trends in Neuroscience, 8:132-135 (1985). 4. Damasio , Antonio R. and others. "Prosopagnosia: Anatomic Basis and Behav- ioral Mechanisms

  7. PrimeFaces blueprints

    CERN Document Server

    Jonna, Sudheer

    2014-01-01

    If you are a Java developer with experience of frontend UI development, and want to take the plunge to develop stunning UI applications with the most popular JSF framework, PrimeFaces, then this book is for you. For those with entrepreneurial aspirations, this book will provide valuable insights into how to utilize successful business models.

  8. Facing Up to Death

    Science.gov (United States)

    Ross, Elizabeth Kubler

    1972-01-01

    Doctor urges that Americans accept death as a part of life and suggests ways of helping dying patients and their families face reality calmly, with peace. Dying children and their siblings, as well as children's feelings about relatives' deaths, are also discussed. (PD)

  9. 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.

  10. 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.

  11. Face aftereffects predict individual differences in face recognition ability.

    Science.gov (United States)

    Dennett, Hugh W; McKone, Elinor; Edwards, Mark; Susilo, Tirta

    2012-01-01

    Face aftereffects are widely studied on the assumption that they provide a useful tool for investigating face-space coding of identity. However, a long-standing issue concerns the extent to which face aftereffects originate in face-level processes as opposed to earlier stages of visual processing. For example, some recent studies failed to find atypical face aftereffects in individuals with clinically poor face recognition. We show that in individuals within the normal range of face recognition abilities, there is an association between face memory ability and a figural face aftereffect that is argued to reflect the steepness of broadband-opponent neural response functions in underlying face-space. We further show that this correlation arises from face-level processing, by reporting results of tests of nonface memory and nonface aftereffects. We conclude that face aftereffects can tap high-level face-space, and that face-space coding differs in quality between individuals and contributes to face recognition ability.

  12. Human faces are slower than chimpanzee faces.

    Directory of Open Access Journals (Sweden)

    Anne M Burrows

    Full Text Available BACKGROUND: While humans (like other primates communicate with facial expressions, the evolution of speech added a new function to the facial muscles (facial expression muscles. The evolution of speech required the development of a coordinated action between visual (movement of the lips and auditory signals in a rhythmic fashion to produce "visemes" (visual movements of the lips that correspond to specific sounds. Visemes depend upon facial muscles to regulate shape of the lips, which themselves act as speech articulators. This movement necessitates a more controlled, sustained muscle contraction than that produced during spontaneous facial expressions which occur rapidly and last only a short period of time. Recently, it was found that human tongue musculature contains a higher proportion of slow-twitch myosin fibers than in rhesus macaques, which is related to the slower, more controlled movements of the human tongue in the production of speech. Are there similar unique, evolutionary physiologic biases found in human facial musculature related to the evolution of speech? METHODOLOGY/PRINICIPAL FINDINGS: Using myosin immunohistochemistry, we tested the hypothesis that human facial musculature has a higher percentage of slow-twitch myosin fibers relative to chimpanzees (Pan troglodytes and rhesus macaques (Macaca mulatta. We sampled the orbicularis oris and zygomaticus major muscles from three cadavers of each species and compared proportions of fiber-types. Results confirmed our hypothesis: humans had the highest proportion of slow-twitch myosin fibers while chimpanzees had the highest proportion of fast-twitch fibers. CONCLUSIONS/SIGNIFICANCE: These findings demonstrate that the human face is slower than that of rhesus macaques and our closest living relative, the chimpanzee. They also support the assertion that human facial musculature and speech co-evolved. Further, these results suggest a unique set of evolutionary selective pressures on

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Automated Face Recognition System

    Science.gov (United States)

    1992-12-01

    atestfOl.feature-vectjJ -averageljJ); for(j=l; <num-coefsj++) for(i= 5 num-train-faces;i++) sdlQjI -(btrainhil.feaure..vecU1- veagU (btraintil.feature- vecU ... vecU ])* (atest(O1.feature-vecUJ - btrain[iI.feature- vecU ]) + temp; btrain(ii.distance = sqrt ( (double) temp); I**** Store the k-nearest neighbors rank

  1. Auto Industry Faces Change

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A number of indicators show that China's auto industry is facing a new round of large-scale restructuring. When the global auto industry was undergoing reorganization 10 years ago, China's auto industry was in its early stages, acting in a relatively closed market, and thus it missed out on that important event. However, the situation is different today. In the past decade, China's auto industry has grown at a rapid pace. While the world's major transnational companies are

  2. 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.

  3. 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.

  4. Decoding of faces and face components in face-sensitive human visual cortex

    Directory of Open Access Journals (Sweden)

    David F Nichols

    2010-07-01

    Full Text Available A great challenge to the field of visual neuroscience is to understand how faces are encoded and represented within the human brain. Here we show evidence from functional magnetic resonance imaging (fMRI for spatially distributed processing of the whole face and its components in face-sensitive human visual cortex. We used multi-class linear pattern classifiers constructed with a leave-one-scan-out verification procedure to discriminate brain activation patterns elicited by whole faces, the internal features alone, and the external head outline alone. Furthermore, our results suggest that whole faces are represented disproportionately in the fusiform cortex (FFA whereas the building blocks of faces are represented disproportionately in occipitotemporal cortex (OFA. Faces and face components may therefore be organized with functional clustering within both the FFA and OFA, but with specialization for face components in the OFA and the whole face in the FFA.

  5. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, Gerrit Maarten

    2009-01-01

    Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their a

  6. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, G.M.

    2009-01-01

    Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their ap

  7. Face-space: A unifying concept in face recognition research.

    Science.gov (United States)

    Valentine, Tim; Lewis, Michael B; Hills, Peter J

    2016-10-01

    The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

  8. 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.

  9. 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.

  10. 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...

  11. Face-to-Face Interference in Typical and Atypical Development

    Science.gov (United States)

    Riby, Deborah M.; Doherty-Sneddon, Gwyneth; Whittle, Lisa

    2012-01-01

    Visual communication cues facilitate interpersonal communication. It is important that we look at faces to retrieve and subsequently process such cues. It is also important that we sometimes look away from faces as they increase cognitive load that may interfere with online processing. Indeed, when typically developing individuals hold face gaze…

  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. Challenges facing production grids

    Energy Technology Data Exchange (ETDEWEB)

    Pordes, Ruth; /Fermilab

    2007-06-01

    Today's global communities of users expect quality of service from distributed Grid systems equivalent to that their local data centers. This must be coupled to ubiquitous access to the ensemble of processing and storage resources across multiple Grid infrastructures. We are still facing significant challenges in meeting these expectations, especially in the underlying security, a sustainable and successful economic model, and smoothing the boundaries between administrative and technical domains. Using the Open Science Grid as an example, I examine the status and challenges of Grids operating in production today.

  14. Many Faces of Migrations

    Directory of Open Access Journals (Sweden)

    Milica Antić Gaber

    2013-12-01

    The title “Many faces of migration”, connecting contributions in this special issue, is borrowed from the already mentioned Gallup Institute’s report on global migration (Esipova, 2011. The guiding principle in the selection of the contributions has been their diversity, reflected also in the list of disciplines represented by the authors: sociology, geography, ethnology and cultural anthropology, history, art history, modern Mediterranean studies, gender studies and media studies. Such an approach necessarily leads not only to a diverse, but at least seemingly also incompatib

  15. Faced with a dilemma

    DEFF Research Database (Denmark)

    Christensen, Anne Vinggaard; Christiansen, Anne Hjøllund; Petersson, Birgit

    2013-01-01

    's legal right to choose TOP and considerations about the foetus' right to live were suppressed. Midwives experienced a dilemma when faced with aborted foetuses that looked like newborns and when aborted foetuses showed signs of life after a termination. Furthermore, they were critical of how physicians...... counsel women/couples after prenatal diagnosis. CONCLUSIONS: The midwives' practice in relation to late TOP was characterised by an acknowledgement of the growing ethical status of the foetus and the emotional reactions of the women/couples going through late TOP. Other professions as well as structural...

  16. 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.

  17. The activation of visual face memory and explicit face recognition are delayed in developmental prosopagnosia.

    Science.gov (United States)

    Parketny, Joanna; Towler, John; Eimer, Martin

    2015-08-01

    Individuals with developmental prosopagnosia (DP) are strongly impaired in recognizing faces, but the causes of this deficit are not well understood. We employed event-related brain potentials (ERPs) to study the time-course of neural processes involved in the recognition of previously unfamiliar faces in DPs and in age-matched control participants with normal face recognition abilities. Faces of different individuals were presented sequentially in one of three possible views, and participants had to detect a specific Target Face ("Joe"). EEG was recorded during task performance to Target Faces, Nontarget Faces, or the participants' Own Face (which had to be ignored). The N250 component was measured as a marker of the match between a seen face and a stored representation in visual face memory. The subsequent P600f was measured as an index of attentional processes associated with the conscious awareness and recognition of a particular face. Target Faces elicited reliable N250 and P600f in the DP group, but both of these components emerged later in DPs than in control participants. This shows that the activation of visual face memory for previously unknown learned faces and the subsequent attentional processing and conscious recognition of these faces are delayed in DP. N250 and P600f components to Own Faces did not differ between the two groups, indicating that the processing of long-term familiar faces is less affected in DP. However, P600f components to Own Faces were absent in two participants with DP who failed to recognize their Own Face during the experiment. These results provide new evidence that face recognition deficits in DP may be linked to a delayed activation of visual face memory and explicit identity recognition mechanisms.

  18. 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.

  19. Aging changes in the face

    Science.gov (United States)

    ... this page: //medlineplus.gov/ency/article/004004.htm Aging changes in the face To use the sharing ... face with age References Brodie SE, Francis JH. Aging and disorders of the eye. In: Fillit HM, ...

  20. 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%.

  1. Enabling dynamics in face analysis

    NARCIS (Netherlands)

    Dibeklioğlu, H.

    2014-01-01

    Most of the approaches in automatic face analysis rely solely on static appearance. However, temporal analysis of expressions reveals interesting patterns. For a better understanding of the human face, this thesis focuses on temporal changes in the face, and dynamic patterns of expressions. In addit

  2. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond; Quaglia, Adamo; Epifano, Calogera M.

    2012-01-01

    The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a

  3. 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

  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. 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.

  6. A Multi—View Face Recognition System

    Institute of Scientific and Technical Information of China (English)

    张永越; 彭振云; 等

    1997-01-01

    In many automatic face recognition systems,posture constraining is a key factor preventing them from application.In this paper a series of strategies will be described to achieve a system which enables face recognition under varying pose.These approaches include the multi-view face modeling,the threschold image based face feature detection,the affine transformation based face posture normalization and the template matching based face identification.Combining all of these strategies,a face recognition system with the pose invariance is designed successfully,Using a 75MHZ Pentium PC and with a database of 75 individuals,15 images for each person,and 225 test images with various postures,a very good recognition rate of 96.89% is obtained.

  7. 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。

  8. Facing the Challenges

    DEFF Research Database (Denmark)

    He, Kai

    2014-01-01

    China's rise signifies a gradual transformation of the international system from unipolarity to a non-unipolar world. ,4s an organization of small and middle powers, ASEAN faces strategic uncertainties brought about by the power transition in the system. Deepening economic interdependence between...... ASEAN and China has amplified the economic cost for the ASEAN states to use traditional military means to deal with China s rise. Applying institutional balancing theory, this paper examines how ASEAN has adopted various institutional instruments, such as the ASEAN Regional Forum (ARF), the East Asia...... Summit (EAS), the Regional Comprehensive Economic Partnership (RCEP), and the ASEAN Community, to constrain and shape China's behaviour in the region in the post-Cold War era. It argues that due to globalization and economic interdependence, the power transition in the 21st century is different from...

  9. Préface

    Directory of Open Access Journals (Sweden)

    Marguerite Mendell

    2008-12-01

    Full Text Available C’est avec grand plaisir que je contribue la préface de ce numéro d’Interventions économiques dédié à la pertinence de la pensée de Karl Polanyi au début du 21ème siècle. Je suis très reconnaissante aux éditeurs, Diane Gabrielle Tremblay, Jean-Marc Fontan et Jean Louis Laville d’avoir pris l’initiative de préparer ce numéro pour le 11ème colloque international de l’Institut Karl Polanyi, qui correspond aussi au 20ème anniversaire de l’Institut, établi à l’Université Concordia en 1988. Interve...

  10. Spatial attention modulates early face processing.

    Science.gov (United States)

    Feng, Wenfeng; Martinez, Antigona; Pitts, Michael; Luo, Yue-Jia; Hillyard, Steven A

    2012-12-01

    It is widely reported that inverting a face dramatically affects its recognition. Previous studies have shown that face inversion increases the amplitude and delays the latency of the face-specific N170 component of the event-related potential (ERP) and also enhances the amplitude of the occipital P1 component (latency 100-132 ms). The present study investigates whether these effects of face inversion can be modulated by visual spatial attention. Participants viewed two streams of visual stimuli, one to the left and one to the right of fixation. One stream consisted of a sequence of alphanumeric characters at 6.67 Hz, and the other stream consisted of a series of upright and inverted images of faces and houses presented in randomized order. The participants' task was to attend selectively to one or the other of the streams (during different blocks) in order to detect infrequent target stimuli. ERPs elicited by inverted faces showed larger P1 amplitudes compared to upright faces, but only when the faces were attended. In contrast, the N170 amplitude was larger to inverted than to upright faces only when the faces were not attended. The N170 peak latency was delayed to inverted faces regardless of attention condition. These inversion effects were face specific, as similar effects were absent for houses. These results suggest that early stages of face-specific processing can be enhanced by attention, but when faces are not attended the onset of face-specific processing is delayed until the latency range of the N170.

  11. Pilgrims Face Recognition Dataset -- HUFRD

    OpenAIRE

    Aly, Salah A.

    2012-01-01

    In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such dataset will be used to test our developed facial recognition and detection algorithms, as well as assess in the missing and found recognition system \\cite{crowdsensing}.

  12. [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.

  13. 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.

  14. 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...

  15. 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

  16. Elektronická komunikace vs. komunikace face to face

    OpenAIRE

    Pipková, Zuzana

    2009-01-01

    This thesis deals with new forms of communication particularly electronic ones. The main goal is to distinguish electronic communication from face to face communication in a way that differs from traditional media theories. By using examples of the most important medium in electronic communication, Internet, it is shown that nowadays we have such forms of electronic communication that surpass the traditional classification of oral/written communication, immediate/mediate communication, face t...

  17. Holistic crowding of Mooney faces.

    Science.gov (United States)

    Farzin, Faraz; Rivera, Susan M; Whitney, David

    2009-06-29

    An object or feature is generally more difficult to identify when other objects are presented nearby, an effect referred to as crowding. Here, we used Mooney faces to examine whether crowding can also occur within and between holistic face representations (C. M. Mooney, 1957). Mooney faces are ideal stimuli for this test because no cues exist to distinguish facial features in a Mooney face; to find any facial feature, such as an eye or a nose, one must first holistically perceive the image as a face. Through a series of six experiments we tested the effect of crowding on Mooney face recognition. Our results demonstrate crowding between and within Mooney faces and fulfill the diagnostic criteria for crowding, including eccentricity dependence and lack of crowding in the fovea, critical flanker spacing consistent with less than half the eccentricity of the target, and inner-outer flanker asymmetry. Further, our results show that recognition of an upright Mooney face is more strongly impaired by upright Mooney face flankers than inverted ones. Taken together, these results suggest crowding can occur selectively between high-level representations of faces and that crowding must occur at multiple levels in the visual system.

  18. [A review of face illusions].

    Science.gov (United States)

    Kitaoka, Akiyoshi

    2012-07-01

    A variety of "face illusions," including the gaze illusion, face inversion effects, geometrical illusions, reversible figures, and other interesting phenomena related to face perception, are reviewed in the present report, with many sample images. The "gaze illusion" or the illusion of eye direction includes the Wollaston illusion, the luminance-induced gaze shift, the Bogart illusion, the eye-shadow-dependent gaze illusion, the Mona Lisa effect, etc. "Face inversion effects" refer to the Thatcher illusion, the fat face-thin illusion, underestimation of the upright face, the nose-shortening illusion of the inverted face, etc. "Geometrical illusions" include the Lee-Freire illusion, Yang's iris illusion, overestimation of the farther eye, the eye-shadow-dependent eye-size illusion, etc. "Reversible figures" contain the whole-part reversible figure, Rubin's vase-face illusion, or hybrid images. "Other interesting phenomena" include the flashed face distortion effect, the presidential illusion, predominance of the mouth or eyebrows over eye expression, the eye direction aftereffect, etc. It is suggested that some of these phenomena are highly specific to face perception.

  19. The effect of familiarity on face adaptation

    OpenAIRE

    Laurence, Sarah

    2013-01-01

    Face adaptation techniques have been used extensively to investigate how faces are processed. It has even been suggested that face adaptation is functional in calibrating the visual system to the diet of faces to which an observer is exposed. Yet most adaptation studies to date have used unfamiliar faces: few have used faces with real world familiarity. Familiar faces have more abstractive representations than unfamiliar faces. The experiments in this thesis therefore examined face adaptation...

  20. Adaptation improves face trustworthiness discrimination

    Science.gov (United States)

    Keefe, B. D.; Dzhelyova, M.; Perrett, D. I.; Barraclough, N. E.

    2013-01-01

    Adaptation to facial characteristics, such as gender and viewpoint, has been shown to both bias our perception of faces and improve facial discrimination. In this study, we examined whether adapting to two levels of face trustworthiness improved sensitivity around the adapted level. Facial trustworthiness was manipulated by morphing between trustworthy and untrustworthy prototypes, each generated by morphing eight trustworthy and eight untrustworthy faces, respectively. In the first experiment, just-noticeable differences (JNDs) were calculated for an untrustworthy face after participants adapted to an untrustworthy face, a trustworthy face, or did not adapt. In the second experiment, the three conditions were identical, except that JNDs were calculated for a trustworthy face. In the third experiment we examined whether adapting to an untrustworthy male face improved discrimination to an untrustworthy female face. In all experiments, participants completed a two-interval forced-choice (2-IFC) adaptive staircase procedure, in which they judged which face was more untrustworthy. JNDs were derived from a psychometric function fitted to the data. Adaptation improved sensitivity to faces conveying the same level of trustworthiness when compared to no adaptation. When adapting to and discriminating around a different level of face trustworthiness there was no improvement in sensitivity and JNDs were equivalent to those in the no adaptation condition. The improvement in sensitivity was found to occur even when adapting to a face with different gender and identity. These results suggest that adaptation to facial trustworthiness can selectively enhance mechanisms underlying the coding of facial trustworthiness to improve perceptual sensitivity. These findings have implications for the role of our visual experience in the decisions we make about the trustworthiness of other individuals. PMID:23801979

  1. Adaptation improves face trustworthiness discrimination.

    Science.gov (United States)

    Keefe, B D; Dzhelyova, M; Perrett, D I; Barraclough, N E

    2013-01-01

    Adaptation to facial characteristics, such as gender and viewpoint, has been shown to both bias our perception of faces and improve facial discrimination. In this study, we examined whether adapting to two levels of face trustworthiness improved sensitivity around the adapted level. Facial trustworthiness was manipulated by morphing between trustworthy and untrustworthy prototypes, each generated by morphing eight trustworthy and eight untrustworthy faces, respectively. In the first experiment, just-noticeable differences (JNDs) were calculated for an untrustworthy face after participants adapted to an untrustworthy face, a trustworthy face, or did not adapt. In the second experiment, the three conditions were identical, except that JNDs were calculated for a trustworthy face. In the third experiment we examined whether adapting to an untrustworthy male face improved discrimination to an untrustworthy female face. In all experiments, participants completed a two-interval forced-choice (2-IFC) adaptive staircase procedure, in which they judged which face was more untrustworthy. JNDs were derived from a psychometric function fitted to the data. Adaptation improved sensitivity to faces conveying the same level of trustworthiness when compared to no adaptation. When adapting to and discriminating around a different level of face trustworthiness there was no improvement in sensitivity and JNDs were equivalent to those in the no adaptation condition. The improvement in sensitivity was found to occur even when adapting to a face with different gender and identity. These results suggest that adaptation to facial trustworthiness can selectively enhance mechanisms underlying the coding of facial trustworthiness to improve perceptual sensitivity. These findings have implications for the role of our visual experience in the decisions we make about the trustworthiness of other individuals.

  2. Adaptation improves face trustworthiness discrimination

    Directory of Open Access Journals (Sweden)

    Bruce D Keefe

    2013-06-01

    Full Text Available Adaptation to facial characteristics, such as gender and viewpoint, has been shown to both bias our perception of faces and improve facial discrimination. In this study, we examined whether adapting to two levels of face trustworthiness improved sensitivity around the adapted level. Facial trustworthiness was manipulated by morphing between trustworthy and untrustworthy prototypes, each generated by morphing eight trustworthy and eight untrustworthy faces respectively. In the first experiment, just-noticeable differences (JNDs were calculated for an untrustworthy face after participants adapted to an untrustworthy face, a trustworthy face, or did not adapt. In the second experiment, the three conditions were identical, except that JNDs were calculated for a trustworthy face. In the third experiment we examined whether adapting to an untrustworthy male face improved discrimination to an untrustworthy female face. In all experiments, participants completed a two-interval forced-choice adaptive staircase procedure, in which they judged which face was more untrustworthy. JNDs were derived from a psychometric function fitted to the data. Adaptation improved sensitivity to faces conveying the same level of trustworthiness when compared to no adaptation. When adapting to and discriminating around a different level of face trustworthiness there was no improvement in sensitivity and JNDs were equivalent to those in the no adaptation condition. The improvement in sensitivity was found to occur even when adapting to a face with different gender and identity. These results suggest that adaptation to facial trustworthiness can selectively enhance mechanisms underlying the coding of facial trustworthiness to improve perceptual sensitivity. These findings have implications for the role of our visual experience in the decisions we make about the trustworthiness of other individuals.

  3. Face-n-Food: Gender Differences in Tuning to Faces

    Science.gov (United States)

    Pavlova, Marina A.; Scheffler, Klaus; Sokolov, Alexander N.

    2015-01-01

    Faces represent valuable signals for social cognition and non-verbal communication. A wealth of research indicates that women tend to excel in recognition of facial expressions. However, it remains unclear whether females are better tuned to faces. We presented healthy adult females and males with a set of newly created food-plate images resembling faces (slightly bordering on the Giuseppe Arcimboldo style). In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Females not only more readily recognized the images as a face (they reported resembling a face on images, on which males still did not), but gave on overall more face responses. The findings are discussed in the light of gender differences in deficient face perception. As most neuropsychiatric, neurodevelopmental and psychosomatic disorders characterized by social brain abnormalities are sex specific, the task may serve as a valuable tool for uncovering impairments in visual face processing. PMID:26154177

  4. 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

  5. Facing the Crises

    Directory of Open Access Journals (Sweden)

    Moira Baker

    2014-12-01

    Full Text Available Timely, provocative, and theoretically sophisticated, the essays comprising In the Face of Crises: Anglophone Literature in the Postmodern World situate their work amid several critical global concerns: the devastation wreaked by global capitalism following the worldwide financial crash, the financial sector’s totalizing grip upon the world economy, the challenge to traditional definitions of “human nature” and identity posed by technologies of the body and of warfare, the quest of indigenous communities for healing from the continuing traumatic effects of colonization, and the increasing corporatization of the academy as an apparatus of the neo-liberal state – to specify only a few. Edited by Professors Ljubica Matek and Jasna Poljak Rehlicki, these essays deploy a broad range of contemporary theories, representing recent developments in cultural studies, the new economic criticism, postcolonial film studies, feminism and gender studies, and the new historicism. The eleven essays selected by Matek and Rehlicki offer convincing support for their claim that humanistic research delving into Anglophone literature, far from being a “non-profitable” pursuit in an increasingly technologized society, affords clarifying insights into contemporary “economic, cultural, and social processes in the globalizing and globalized culture of the West” (ix.

  6. Face au risque

    CERN Document Server

    Grosse, Christian; November, Valérie

    2007-01-01

    Ce volume collectif sur le risque inaugure la collection L'ÉQUINOXE. Ancré dans l'histoire pour mesurer les continuités et les ruptures, il illustre la manière dont les sciences humaines évaluent et mesurent les enjeux collectifs du risque sur les plans politiques, scientifiques, énergétiques, juridiques et éthiques. Puisse-t-il nourrir la réflexion sur la culture et la prévention du risque. Ses formes épidémiques, écologiques, sociales, terroristes et militaires nourrissent les peurs actuelles, structurent les projets sécuritaires et constituent - sans doute - les défis majeurs à notre modernité. Dans la foulée de la richesse scientifique d'Equinoxe, L'ÉQUINOXE hérite de son esprit en prenant à son tour le pari de contribuer - non sans risque - à enrichir en Suisse romande et ailleurs le champ éditorial des sciences humaines dont notre société a besoin pour forger ses repères. Après Face au risque suivra cet automne Du sens des Lumières. (MICHEL PORRET Professeur Ordinaire à la F...

  7. Face adaptation improves gender discrimination.

    Science.gov (United States)

    Yang, Hua; Shen, Jianhong; Chen, Juan; Fang, Fang

    2011-01-01

    Adaptation to a visual pattern can alter the sensitivities of neuronal populations encoding the pattern. However, the functional roles of adaptation, especially in high-level vision, are still equivocal. In the present study, we performed three experiments to investigate if face gender adaptation could affect gender discrimination. Experiments 1 and 2 revealed that adapting to a male/female face could selectively enhance discrimination for male/female faces. Experiment 3 showed that the discrimination enhancement induced by face adaptation could transfer across a substantial change in three-dimensional face viewpoint. These results provide further evidence suggesting that, similar to low-level vision, adaptation in high-level vision could calibrate the visual system to current inputs of complex shapes (i.e. face) and improve discrimination at the adapted characteristic.

  8. Holistic face training enhances face processing in developmental prosopagnosia.

    Science.gov (United States)

    DeGutis, Joseph; Cohan, Sarah; Nakayama, Ken

    2014-06-01

    Prosopagnosia has largely been regarded as an untreatable disorder. However, recent case studies using cognitive training have shown that it is possible to enhance face recognition abilities in individuals with developmental prosopagnosia. Our goal was to determine if this approach could be effective in a larger population of developmental prosopagnosics. We trained 24 developmental prosopagnosics using a 3-week online face-training program targeting holistic face processing. Twelve subjects with developmental prosopagnosia were assessed before and after training, and the other 12 were assessed before and after a waiting period, they then performed the training, and were then assessed again. The assessments included measures of front-view face discrimination, face discrimination with view-point changes, measures of holistic face processing, and a 5-day diary to quantify potential real-world improvements. Compared with the waiting period, developmental prosopagnosics showed moderate but significant overall training-related improvements on measures of front-view face discrimination. Those who reached the more difficult levels of training ('better' trainees) showed the strongest improvements in front-view face discrimination and showed significantly increased holistic face processing to the point of being similar to that of unimpaired control subjects. Despite challenges in characterizing developmental prosopagnosics' everyday face recognition and potential biases in self-report, results also showed modest but consistent self-reported diary improvements. In summary, we demonstrate that by using cognitive training that targets holistic processing, it is possible to enhance face perception across a group of developmental prosopagnosics and further suggest that those who improved the most on the training task received the greatest benefits.

  9. Real Time Implementation Of Face Recognition System

    Directory of Open Access Journals (Sweden)

    Megha Manchanda

    2014-10-01

    Full Text Available This paper proposes face recognition method using PCA for real time implementation. Nowadays security is gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such implementations however, are becoming less secure and practical, also is becoming more problematic thus leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst important subjects in biometrics systems. This system is very useful for security in particular and has been widely used and developed in many countries. This study aims to achieve face recognition successfully by detecting human face in real time, based on Principal Component Analysis (PCA algorithm.

  10. Holistic processing predicts face recognition.

    Science.gov (United States)

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  11. Winning Faces Vary By Ideology

    DEFF Research Database (Denmark)

    Laustsen, Lasse; Petersen, Michael Bang

    2016-01-01

    for others. Utilizing research on ideological stereotypes and the determinants of facial preferences, we focus on the relationship between the facial dominance of the source and the ideology of the receiver. Across five studies, we demonstrate that a dominant face is a winning face when the audience...... is conservative but backfires and decreases success when the audience is liberal. On the other hand, a non-dominant face constitutes a winning face among liberal audiences but backfires among conservatives. These effects seemingly stem from deep-seated psychological responses and shape both the election...

  12. A Novel Face Segmentation Algorithm from a Video Sequence for Real-Time Face Recognition

    Directory of Open Access Journals (Sweden)

    Sudhaker Samuel RD

    2007-01-01

    Full Text Available The first step in an automatic face recognition system is to localize the face region in a cluttered background and carefully segment the face from each frame of a video sequence. In this paper, we propose a fast and efficient algorithm for segmenting a face suitable for recognition from a video sequence. The cluttered background is first subtracted from each frame, in the foreground regions, a coarse face region is found using skin colour. Then using a dynamic template matching approach the face is efficiently segmented. The proposed algorithm is fast and suitable for real-time video sequence. The algorithm is invariant to large scale and pose variation. The segmented face is then handed over to a recognition algorithm based on principal component analysis and linear discriminant analysis. The online face detection, segmentation, and recognition algorithms take an average of 0.06 second on a 3.2 GHz P4 machine.

  13. Teaching On-Line versus Face-to-Face.

    Science.gov (United States)

    Smith, Glenn Gordon; Ferguson, David; Caris, Mieke

    2002-01-01

    Investigates and describes the current instructor experience of teaching college courses over the Web versus in face-to-face formats in terms of teaching strategies, social issues, and media effects. Discusses communication styles, relationship between students and instructors, instructor workload, and discussion patterns, and proposes a model…

  14. Effects of aging on face identification and holistic face processing.

    Science.gov (United States)

    Konar, Yaroslav; Bennett, Patrick J; Sekuler, Allison B

    2013-08-09

    Several studies have shown that face identification accuracy is lower in older than younger adults. This effect of aging might be due to age differences in holistic processing, which is thought to be an important component of human face processing. Currently, however, there is conflicting evidence as to whether holistic face processing is impaired in older adults. The current study therefore re-examined this issue by measuring response accuracy in a 1-of-4 face identification task and the composite face effect (CFE), a common index of holistic processing, in older adults. Consistent with previous reports, we found that face identification accuracy was lower in older adults than in younger adults tested in the same task. We also found a significant CFE in older adults that was similar in magnitude to the CFE measured in younger subjects with the same task. Finally, we found that there was a significant positive correlation between the CFE and face identification accuracy. This last result differs from the results obtained in a previous study that used the same tasks and which found no evidence of an association between the CFE and face identification accuracy in younger adults. Furthermore, the age difference was found with subtraction-, regression-, and ratio-based estimates of the CFE. The current findings are consistent with previous claims that older adults rely more heavily on holistic processing to identify objects in conditions of limited processing resources.

  15. Registration of 3D Face Scans with Average Face Models

    NARCIS (Netherlands)

    Salah, A.A.; Alyuz, N.; Akarun, L.

    2008-01-01

    The accuracy of a 3D face recognition system depends on a correct registration that aligns the facial surfaces and makes a comparison possible. The best results obtained so far use a costly one-to-all registration approach, which requires the registration of each facial surface to all faces in the g

  16. Addressee Identification In Face-to-Face Meetings

    NARCIS (Netherlands)

    Jovanovic, N.; op den Akker, Hendrikus J.A.; Nijholt, Antinus; McCarthy, D.; Wintner, S.

    We present results on addressee identification in four-participants face-to-face meetings using Bayesian Network and Naive Bayes classifiers. First, we investigate how well the addressee of a dialogue act can be predicted based on gaze, utterance and conversational context features. Then, we explore

  17. Cyber- and Face-to-Face Bullying: Who Crosses Over?

    Science.gov (United States)

    Shin, Hwayeon Helene; Braithwaite, Valerie; Ahmed, Eliza

    2016-01-01

    A total of 3956 children aged 12-13 years who completed the Longitudinal Study of Australian Children (LSAC Wave 5) were studied about their experiences of traditional face-to-face bullying and cyberbullying in the last month. In terms of prevalence, sixty percent of the sample had been involved in traditional bullying as the victim and/or the…

  18. Finding Hope in the Face-to-Face.

    Science.gov (United States)

    Edgoose, Jennifer Y C; Edgoose, Julian M

    2017-05-01

    What does it mean to look into the face of a patient who looks back? Face-to-face encounters are at the heart of the patient-clinician relationship but their singular significance is often lost amid the demands of today's high-tech, metric-driven health care systems. Using the framework provided by the philosopher and Holocaust survivor Emmanuel Levinas, the authors explore the unique responsibility and potential for hope found only in face-to-face encounters. Revisiting this most fundamental attribute of medicine is likely our greatest chance to reclaim who we are as clinicians and why we do what we do. © 2017 Annals of Family Medicine, Inc.

  19. Infant Face Preferences after Binocular Visual Deprivation

    Science.gov (United States)

    Mondloch, Catherine J.; Lewis, Terri L.; Levin, Alex V.; Maurer, Daphne

    2013-01-01

    Early visual deprivation impairs some, but not all, aspects of face perception. We investigated the possible developmental roots of later abnormalities by using a face detection task to test infants treated for bilateral congenital cataract within 1 hour of their first focused visual input. The seven patients were between 5 and 12 weeks old…

  20. 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.

  1. 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.

  2. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Veldhuis, Raymond; Spreeuwers, Luuk

    2010-01-01

    Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is t

  3. Age-invariant face recognition.

    Science.gov (United States)

    Park, Unsang; Tong, Yiying; Jain, Anil K

    2010-05-01

    One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.

  4. PrimeFaces beginner's guide

    CERN Document Server

    Reddy, K Siva Prasad

    2013-01-01

    A guide for beginner's with step-by-step instructions and an easy-to-follow approach.PrimeFaces Beginners Guide is a simple and effective guide for beginners, wanting to learn and implement PrimeFaces in their JSF-based applications. Some basic JSF and jQuery skills are required before you start working through the book.

  5. Parallel Processing in Face Perception

    Science.gov (United States)

    Martens, Ulla; Leuthold, Hartmut; Schweinberger, Stefan R.

    2010-01-01

    The authors examined face perception models with regard to the functional and temporal organization of facial identity and expression analysis. Participants performed a manual 2-choice go/no-go task to classify faces, where response hand depended on facial familiarity (famous vs. unfamiliar) and response execution depended on facial expression…

  6. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N.J.; Biggelaar , van den Olivier

    2011-01-01

    As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss th

  7. 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

  8. 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.

  9. Emotion-independent face recognition

    Science.gov (United States)

    De Silva, Liyanage C.; Esther, Kho G. P.

    2000-12-01

    Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

  10. Genetic specificity of face recognition.

    Science.gov (United States)

    Shakeshaft, Nicholas G; Plomin, Robert

    2015-10-13

    Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

  11. Learning faces: similar comparator faces do not improve performance.

    Directory of Open Access Journals (Sweden)

    Scott P Jones

    Full Text Available Recent evidence indicates that comparison of two similar faces can aid subsequent discrimination between them. However, the fact that discrimination between two faces is facilitated by comparing them directly does not demonstrate that comparison produces a general improvement in the processing of faces. It remains an open question whether the opportunity to compare a "target" face to similar faces can facilitate the discrimination of the exposed target face from other nonexposed faces. In Experiment 1, selection of a target face from an array of novel foils was not facilitated by intermixed exposure to the target and comparators of the same sex. Experiment 2 also found no advantage for similar comparators (morphed towards the target over unmorphed same sex comparators, or over repeated target exposure alone. But all repeated exposure conditions produced better performance than a single brief presentation of the target. Experiment 3 again demonstrated that repeated exposure produced equivalent learning in same sex and different sex comparator conditions, and also showed that increasing the number of same sex or different sex comparators failed to improve identification. In all three experiments, exposure to a target alongside similar comparators failed to support selection of the target from novel test stimuli to a greater degree than exposure alongside dissimilar comparators or repeated target exposure alone. The current results suggest that the facilitatory effects of comparison during exposure may be limited to improving discrimination between exposed stimuli, and thus our results do not support the idea that providing the opportunity for comparison is a practical means for improving face identification.

  12. 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.

  13. Modeling human dynamics of face-to-face interaction networks

    CERN Document Server

    Starnini, Michele; Pastor-Satorras, Romualdo

    2013-01-01

    Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents which perform a random walk in a two dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

  14. Temporal networks of face-to-face human interactions

    CERN Document Server

    Barrat, Alain

    2013-01-01

    The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface ...

  15. Ethical considerations in face transplantation.

    Science.gov (United States)

    Brown, Charles S; Gander, Brian; Cunningham, Michael; Furr, Allen; Vasilic, Dalibor; Wiggins, Osborne; Banis, Joseph C; Vossen, Marieke; Maldonado, Claudio; Perez-Abadia, Gustavo; Barker, John H

    2007-10-01

    Human face transplantation is now a clinical reality. The surgical techniques necessary to perform these procedures have been used routinely in reconstructive microsurgery for many years. From an immunological standpoint since face and hand contain mostly the same tissues it is reasonable to assume that the same immunosuppressive regimen found to be effective in human hand transplants should also work in face transplantation. It is the ethical issues associated with the risks and benefits of performing facial transplantation that have posed the greatest challenges leading up to performing this new procedure. In this editorial, we will review some of the main events that have led to the recently performed human face transplants, specifically focusing on the key ethical issues at the center of this debate. We will discuss how the research and clinical experience in human hand transplantation laid the foundation for performing face transplantation and describe the research and the ethical guidelines upon which a team at the University of Louisville based their position "to move ahead" in spite of much criticism. Finally we will outline some of the key arguments against face transplantation, and conclude with a discussion on what comes next now that the first human face transplants have been performed.

  16. Multithread Face Recognition in Cloud

    Directory of Open Access Journals (Sweden)

    Dakshina Ranjan Kisku

    2016-01-01

    Full Text Available Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods.

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. Applying Artificial Neural Networks for Face Recognition

    Directory of Open Access Journals (Sweden)

    Thai Hoang Le

    2011-01-01

    Full Text Available This paper introduces some novel models for all steps of a face recognition system. In the step of face detection, we propose a hybrid model combining AdaBoost and Artificial Neural Network (ABANN to solve the process efficiently. In the next step, labeled faces detected by ABANN will be aligned by Active Shape Model and Multi Layer Perceptron. In this alignment step, we propose a new 2D local texture model based on Multi Layer Perceptron. The classifier of the model significantly improves the accuracy and the robustness of local searching on faces with expression variation and ambiguous contours. In the feature extraction step, we describe a methodology for improving the efficiency by the association of two methods: geometric feature based method and Independent Component Analysis method. In the face matching step, we apply a model combining many Neural Networks for matching geometric features of human face. The model links many Neural Networks together, so we call it Multi Artificial Neural Network. MIT + CMU database is used for evaluating our proposed methods for face detection and alignment. Finally, the experimental results of all steps on CallTech database show the feasibility of our proposed model.

  2. How fast is famous face recognition?

    Directory of Open Access Journals (Sweden)

    Gladys eBarragan-Jason

    2012-10-01

    Full Text Available The rapid recognition of familiar faces is crucial for social interactions. However the actual speed with which recognition can be achieved remains largely unknown as most studies have been carried out without any speed constraints. Different paradigms have been used, leading to conflicting results, and although many authors suggest that face recognition is fast, the speed of face recognition has not been directly compared to fast visual tasks. In this study, we sought to overcome these limitations. Subjects performed three tasks, a familiarity categorization task (famous faces among unknown faces, a superordinate categorization task (human faces among animal ones and a gender categorization task. All tasks were performed under speed constraints. The results show that, despite the use of speed constraints, subjects were slow when they had to categorize famous faces: minimum reaction time was 467 ms, which is 180 ms more than during superordinate categorization and 160 ms more than in the gender condition. Our results are compatible with a hierarchy of face processing from the superordinate level to the familiarity level. The processes taking place between detection and recognition need to be investigated in detail.

  3. Autism and the development of face processing.

    Science.gov (United States)

    Golarai, Golijeh; Grill-Spector, Kalanit; Reiss, Allan L

    2006-10-01

    Autism is a pervasive developmental condition, characterized by impairments in non-verbal communication, social relationships and stereotypical patterns of behavior. A large body of evidence suggests that several aspects of face processing are impaired in autism, including anomalies in gaze processing, memory for facial identity and recognition of facial expressions of emotion. In search of neural markers of anomalous face processing in autism, much interest has focused on a network of brain regions that are implicated in social cognition and face processing. In this review, we will focus on three such regions, namely the STS for its role in processing gaze and facial movements, the FFA in face detection and identification and the amygdala in processing facial expressions of emotion. Much evidence suggests that a better understanding of the normal development of these specialized regions is essential for discovering the neural bases of face processing anomalies in autism. Thus, we will also examine the available literature on the normal development of face processing. Key unknowns in this research area are the neuro-developmental processes, the role of experience and the interactions among components of the face processing system in shaping each of the specialized regions for processing faces during normal development and in autism.

  4. Component-Based Cartoon Face Generation

    Directory of Open Access Journals (Sweden)

    Saman Sepehri Nejad

    2016-11-01

    Full Text Available In this paper, we present a cartoon face generation method that stands on a component-based facial feature extraction approach. Given a frontal face image as an input, our proposed system has the following stages. First, face features are extracted using an extended Active Shape Model. Outlines of the components are locally modified using edge detection, template matching and Hermit interpolation. This modification enhances the diversity of output and accuracy of the component matching required for cartoon generation. Second, to bring cartoon-specific features such as shadows, highlights and, especially, stylish drawing, an array of various face photographs and corresponding hand-drawn cartoon faces are collected. These cartoon templates are automatically decomposed into cartoon components using our proposed method for parameterizing cartoon samples, which is fast and simple. Then, using shape matching methods, the appropriate cartoon component is selected and deformed to fit the input face. Finally, a cartoon face is rendered in a vector format using the rendering rules of the selected template. Experimental results demonstrate effectiveness of our approach in generating life-like cartoon faces.

  5. Bracing Zonohedra With Special Faces

    Directory of Open Access Journals (Sweden)

    Nagy Gyula

    2015-12-01

    Full Text Available The analysis of simpler preliminary design gives useful input for more complicated three-dimensional building frame structure. A zonohedron, as a preliminary structure of design, is a convex polyhedron for which each face possesses central symmetry. We considered zonohedron as a special framework with the special assumption that the polygonal faces can be deformed in such a way that faces remain planar and centrally symmetric, moreover the length of all edges remains unchanged. Introducing some diagonal braces we got a new mechanism. This paper deals with the flexibility of this kind of mechanisms, and investigates the rigidity of the braced framework. The flexibility of the framework can be characterized by some vectors, which represent equivalence classes of the edges. A necessary and sufficient condition for the rigidity of the braced rhombic face zonohedra is posed. A real mechanical construction, based on two simple elements, provides a CAD prototype of these new mechanisms.

  6. Face Recognition in Various Illuminations

    Directory of Open Access Journals (Sweden)

    Saurabh D. Parmar,

    2014-05-01

    Full Text Available Face Recognition (FR under various illuminations is very challenging. Normalization technique is useful for removing the dimness and shadow from the facial image which reduces the effect of illumination variations still retaining the necessary information of the face. The robust local feature extractor which is the gray-scale invariant texture called Local Binary Pattern (LBP is helpful for feature extraction. K-Nearest Neighbor classifier is utilized for the purpose of classification and to match the face images from the database. Experimental results were based on Yale-B database with three different sub categories. The proposed method has been tested to robust face recognition in various illumination conditions. Extensive experiment shows that the proposed system can achieve very encouraging performance in various illumination environments.

  7. Similarity measures for face recognition

    CERN Document Server

    Vezzetti, Enrico

    2015-01-01

    Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

  8. Covert Face Recognition without Prosopagnosia

    Directory of Open Access Journals (Sweden)

    H. D. Ellis

    1993-01-01

    Full Text Available An experiment is reported where subjects were presented with familiar or unfamiliar faces for supraliminal durations or for durations individually assessed as being below the threshold for recognition. Their electrodermal responses to each stimulus were measured and the results showed higher peak amplitude skin conductance responses for familiar than for unfamiliar faces, regardless of whether they had been displayed supraliminally or subliminally. A parallel is drawn between elevated skin conductance responses to subliminal stimuli and findings of covert recognition of familiar faces in prosopagnosic patients, some of whom show increased electrodermal activity (EDA to previously familiar faces. The supraliminal presentation data also served to replicate similar work by Tranel et al (1985. The results are considered alongside other data indicating the relation between non-conscious, “automatic” aspects of normal visual information processing and abilities which can be found to be preserved without awareness after brain injury.

  9. More Than a Pretty Face

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The various facial make up designs in the Sichuan Opera are Chinese art treasures With the flick of a wrist,the intricate patterns painted on the opera performer’s face magically shift;the audience,awed

  10. Face recognition using Krawtchouk moment

    Indian Academy of Sciences (India)

    J Sheeba Rani; D Devaraj

    2012-08-01

    Feature extraction is one of the important tasks in face recognition. Moments are widely used feature extractor due to their superior discriminatory power and geometrical invariance. Moments generally capture the global features of the image. This paper proposes Krawtchouk moment for feature extraction in face recognition system, which has the ability to extract local features from any region of interest. Krawtchouk moment is used to extract both local features and global features of the face. The extracted features are fused using summed normalized distance strategy. Nearest neighbour classifier is employed to classify the faces. The proposed method is tested using ORL and Yale databases. Experimental results show that the proposed method is able to recognize images correctly, even if the images are corrupted with noise and possess change in facial expression and tilt.

  11. 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.

  12. 3D Face Apperance Model

    DEFF Research Database (Denmark)

    Lading, Brian; Larsen, Rasmus; Astrom, K

    2006-01-01

    We build a 3D face shape model, including inter- and intra-shape variations, derive the analytical Jacobian of its resulting 2D rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations......We build a 3D face shape model, including inter- and intra-shape variations, derive the analytical Jacobian of its resulting 2D rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations...

  13. 3D Face Appearance Model

    DEFF Research Database (Denmark)

    Lading, Brian; Larsen, Rasmus; Åström, Kalle

    2006-01-01

    We build a 3d face shape model, including inter- and intra-shape variations, derive the analytical jacobian of its resulting 2d rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations.}......We build a 3d face shape model, including inter- and intra-shape variations, derive the analytical jacobian of its resulting 2d rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations.}...

  14. Carbon-Type Analysis and Comparison of Original and Reblended FACE Diesel Fuels (FACE 2, FACE 4, and FACE 7)

    Energy Technology Data Exchange (ETDEWEB)

    Bays, J. Timothy; King, David L.; O' Hagan, Molly J.

    2012-10-01

    This report summarizes the carbon-type analysis from 1H and 13C{1H} nuclear magnetic resonance spectroscopy (NMR) of Fuels for Advanced Combustion Engines (FACE) diesel blends, FD-2B, FD 4B, and FD-7B, and makes comparison of the new blends with the original FACE diesel blends, FD 2A, FD 4A, and FD-7A, respectively. Generally, FD-2A and FD-2B are more similar than the A and B blends of FD-4 and FD-7. The aromatic carbon content is roughly equivalent, although the new FACE blends have decreased monoaromatic content and increased di- and tri-cycloaromatic content, as well as a higher overall aromatic content, than the original FACE blends. The aromatic components of the new FACE blends generally have a higher alkyl substitution with longer alkyl substituents. The naphthenic and paraffinic contents remained relatively consistent. Based on aliphatic methyl and methylene carbon ratios, cetane numbers for FD-2A and -2B, and FD-7A and -7B are predicted to be consistent, while the cetane number for FD-4B is predicted to be higher than FD-4A. Overall, the new FACE fuel blends are fairly consistent with the original FACE fuel blends, but there are observable differences. In addition to providing important comparative compositional information on reformulated FACE diesel blends, this report also provides important information about the capabilities of the team at Pacific Northwest National Laboratory in the use of NMR spectroscopy for the detailed characterization and comparison of fuels and fuel blends.

  15. Face activated neurodynamic cortical networks.

    Science.gov (United States)

    Susac, Ana; Ilmoniemi, Risto J; Ranken, Doug; Supek, Selma

    2011-05-01

    Previous neuroimaging studies have shown that complex visual stimuli, such as faces, activate multiple brain regions, yet little is known on the dynamics and complexity of the activated cortical networks during the entire measurable evoked response. In this study, we used simulated and face-evoked empirical MEG data from an oddball study to investigate the feasibility of accurate, efficient, and reliable spatio-temporal tracking of cortical pathways over prolonged time intervals. We applied a data-driven, semiautomated approach to spatio-temporal source localization with no prior assumptions on active cortical regions to explore non-invasively face-processing dynamics and their modulation by task. Simulations demonstrated that the use of multi-start downhill simplex and data-driven selections of time intervals submitted to the Calibrated Start Spatio-Temporal (CSST) algorithm resulted in improved accuracy of the source localization and the estimation of the onset of their activity. Locations and dynamics of the identified sources indicated a distributed cortical network involved in face processing whose complexity was task dependent. This MEG study provided the first non-invasive demonstration, agreeing with intracranial recordings, of an early onset of the activity in the fusiform face gyrus (FFG), and that frontal activation preceded parietal for responses elicited by target faces.

  16. Statistical Model-Based Face Pose Estimation

    Institute of Scientific and Technical Information of China (English)

    GE Xinliang; YANG Jie; LI Feng; WANG Huahua

    2007-01-01

    A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.

  17. RGB-D-T based Face Recognition

    DEFF Research Database (Denmark)

    Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris

    2014-01-01

    Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But......, such analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...

  18. Cross-correlation in face discrimination

    NARCIS (Netherlands)

    Simpson, William A.; Loffler, Gunter; Tucha, Lara

    2013-01-01

    An extensive body of literature suggests that face perception depends critically upon specialised face processing mechanisms. Although it seems clear that specialised face processing is required to explain face recognition, face discrimination is a simpler task that could possibly be solved with a g

  19. 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.

  20. 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%。

  1. 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。

  2. Holistic face processing of own- and other-age faces in young and older adults: ERP evidence from the composite face task.

    Science.gov (United States)

    Wiese, Holger; Kachel, Ulrike; Schweinberger, Stefan R

    2013-07-01

    Participants more accurately remember own-age relative to other-age faces (own-age bias, OAB). The present study tested whether this effect is related to more efficient holistic processing of own-age faces. Young adult and older participants performed a composite face task with young and old faces, in which they indicated whether the upper half of two subsequent composite faces was identical or not. The lower half of the second face was always different, and face halves were horizontally misaligned in 50% of the trials. Both participant groups were more efficient to correctly identify same upper halves in the misaligned relative to the aligned condition, and this composite face effect (CFE), a marker of holistic face processing, was stronger for young faces. Analysis of event-related potentials revealed strong misalignment effects in the N170, which were more pronounced for young faces in both groups. Critically, in the subsequent N250r a stronger misalignment effect for young faces was detected in young participants only. Since N250r may reflect the facilitated access of a perceptual representation of a previously presented face, this finding is interpreted to reflect young participants' more efficient representation of own-age faces as a whole, which may contribute to their OAB in memory.

  3. Ethnicity identification from face images

    Science.gov (United States)

    Lu, Xiaoguang; Jain, Anil K.

    2004-08-01

    Human facial images provide the demographic information, such as ethnicity and gender. Conversely, ethnicity and gender also play an important role in face-related applications. Image-based ethnicity identification problem is addressed in a machine learning framework. The Linear Discriminant Analysis (LDA) based scheme is presented for the two-class (Asian vs. non-Asian) ethnicity classification task. Multiscale analysis is applied to the input facial images. An ensemble framework, which integrates the LDA analysis for the input face images at different scales, is proposed to further improve the classification performance. The product rule is used as the combination strategy in the ensemble. Experimental results based on a face database containing 263 subjects (2,630 face images, with equal balance between the two classes) are promising, indicating that LDA and the proposed ensemble framework have sufficient discriminative power for the ethnicity classification problem. The normalized ethnicity classification scores can be helpful in the facial identity recognition. Useful as a "soft" biometric, face matching scores can be updated based on the output of ethnicity classification module. In other words, ethnicity classifier does not have to be perfect to be useful in practice.

  4. Atypical face gaze in autism.

    Science.gov (United States)

    Trepagnier, Cheryl; Sebrechts, Marc M; Peterson, Rebecca

    2002-06-01

    An eye-tracking study of face and object recognition was conducted to clarify the character of face gaze in autistic spectrum disorders. Experimental participants were a group of individuals diagnosed with Asperger's disorder or high-functioning autistic disorder according to their medical records and confirmed by the Autism Diagnostic Interview-Revised (ADI-R). Controls were selected on the basis of age, gender, and educational level to be comparable to the experimental group. In order to maintain attentional focus, stereoscopic images were presented in a virtual reality (VR) headset in which the eye-tracking system was installed. Preliminary analyses show impairment in face recognition, in contrast with equivalent and even superior performance in object recognition among participants with autism-related diagnoses, relative to controls. Experimental participants displayed less fixation on the central face than did control-group participants. The findings, within the limitations of the small number of subjects and technical difficulties encountered in utilizing the helmet-mounted display, suggest an impairment in face processing on the part of the individuals in the experimental group. This is consistent with the hypothesis of disruption in the first months of life, a period that may be critical to typical social and cognitive development, and has important implications for selection of appropriate targets of intervention.

  5. 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。

  6. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-03-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authors minimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  7. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-04-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authorsminimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  8. Eye-tracking analysis of face observing and face recognition

    Directory of Open Access Journals (Sweden)

    Andrej Iskra

    2016-07-01

    Full Text Available Images are one of the key elements of the content of the World Wide Web. One group of web images are also photos of people. When various institutions (universities, research organizations, companies, associations, etc. present their staff, they should include photos of people for the purpose of more informative presentation. The fact is, that there are many specifies how people see face images and how do they remember them. Several methods to investigate person’s behavior during use of web content can be performed and one of the most reliable method among them is eye tracking. It is very common technique, particularly when it comes to observing web images. Our research focused on behavior of observing face images in process of memorizing them. Test participants were presented with face images shown at different time scale. We focused on three main face elements: eyes, mouth and nose. The results of our analysis can help not only in web presentation, which are, in principle, not limited by time observation, but especially in public presentations (conferences, symposia, and meetings.

  9. Saving Face and Group Identity

    DEFF Research Database (Denmark)

    Eriksson, Tor; Mao, Lei; Villeval, Marie-Claire

    2015-01-01

    their self- but also other group members' image. This behavior is frequent even in the absence of group identity. When group identity is more salient, individuals help regardless of whether the least performer is an in-group or an out-group. This suggests that saving others' face is a strong social norm.......Are people willing to sacrifice resources to save one's and others' face? In a laboratory experiment, we study whether individuals forego resources to avoid the public exposure of the least performer in their group. We show that a majority of individuals are willing to pay to preserve not only...

  10. [Endoscopy and face-lift].

    Science.gov (United States)

    Dardour, J C; Abbou, R

    2017-08-02

    For many years, the face-lift has not been the only intervention for facial rejuvenation. It is necessary today to specify the type of face-lift, cervico-facial lifting, frontal lifting or facelift. We will consider in this article the frontal lift and centro-facial lift and its possible execution assisted by endoscopy with therefore minimal scars, hidden in the scalp. We will consider successively its technique, its indications and its results highlighting a very long hold over time. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  11. Instant PrimeFaces starter

    CERN Document Server

    Hlavats, Ian

    2013-01-01

    Get to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks. Instant Primefaces Starter is a fast-paced, introductory guide designed to give you all the information you need to start using Primfaces, instantly.Instant PrimeFaces Starter is great for developers looking to get started quickly with PrimeFaces. It's assumed that you have some JSF experience already, as well as familiarity with other Java technologies such as CDI and JPA and an understanding of MVC principles, object-relational mapping (ORM),

  12. Face Recognition in Uncontrolled Environment

    Directory of Open Access Journals (Sweden)

    Radhey Shyam

    2016-08-01

    Full Text Available This paper presents a novel method of facial image representation for face recognition in uncontrolled environment. It is named as augmented local binary patterns (A-LBP that works on both, uniform and non-uniform patterns. It replaces the central non-uniform pattern with a majority value of the neighbouring uniform patterns obtained after processing all neighbouring non-uniform patterns. These patterns are finally combined with the neighbouring uniform patterns, in order to extract discriminatory information from the local descriptors. The experimental results indicate the vitality of the proposed method on particular face datasets, where the images are prone to extreme variations of illumination.

  13. A Survey: Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Muhammad Sharif

    2012-12-01

    Full Text Available In this study, the existing techniques of face recognition are to be encountered along with their pros and cons to conduct a brief survey. The most general methods include Eigenface (Eigenfeatures, Hidden Markov Model (HMM, geometric based and template matching approaches. This survey actually performs analysis on these approaches in order to constitute face representations which will be discussed as under. In the second phase of the survey, factors affecting the recognition rates and processes are also discussed along with the solutions provided by different authors.

  14. A Real-Time Face Recognition System Using Eigenfaces

    Directory of Open Access Journals (Sweden)

    Daniel Georgescu

    2011-12-01

    Full Text Available A real-time system for recognizing faces in a video stream provided by a surveillance camera was implemented, having real-time face detection. Thus, both face detection and face recognition techniques are summary presented, without skipping the important technical aspects. The proposed approach essentially was to implement and verify the algorithm Eigenfaces for Recognition, which solves the recognition problem for two dimensional representations of faces, using the principal component analysis. The snapshots, representing input images for the proposed system, are projected in to a face space (feature space which best defines the variation for the face images training set. The face space is defined by the ‘eigenfaces’ which are the eigenvectors of the set of faces. These eigenfaces contribute in face reconstruction of a new face image projected onto face space with a meaningful (named weight.The projection of the new image in this feature space is then compared to the available projections of training set to identify the person using the Euclidian distance.  The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions.

  15. Incorporating Online Discussion in Face to Face Classroom Learning: A New Blended Learning Approach

    Science.gov (United States)

    Chen, Wenli; Looi, Chee-Kit

    2007-01-01

    This paper discusses an innovative blended learning strategy which incorporates online discussion in both in-class face to face, and off-classroom settings. Online discussion in a face to face class is compared with its two counterparts, off-class online discussion as well as in-class, face to face oral discussion, to examine the advantages and…

  16. A Comparison of Online and Face-to-Face Approaches to Teaching Introduction to American Government

    Science.gov (United States)

    Bolsen, Toby; Evans, Michael; Fleming, Anna McCaghren

    2016-01-01

    This article reports results from a large study comparing four different approaches to teaching Introduction to American Government: (1) traditional, a paper textbook with 100% face-to-face lecture-style teaching; (2) breakout, a paper textbook with 50% face-to-face lecture-style teaching and 50% face-to-face small-group breakout discussion…

  17. 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...

  18. 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.

  19. Artificial faces are harder to remember.

    Science.gov (United States)

    Balas, Benjamin; Pacella, Jonathan

    2015-11-01

    Observers interact with artificial faces in a range of different settings and in many cases must remember and identify computer-generated faces. In general, however, most adults have heavily biased experience favoring real faces over synthetic faces. It is well known that face recognition abilities are affected by experience such that faces belonging to "out-groups" defined by race or age are more poorly remembered and harder to discriminate from one another than faces belonging to the "in-group." Here, we examine the extent to which artificial faces form an "out-group" in this sense when other perceptual categories are matched. We rendered synthetic faces using photographs of real human faces and compared performance in a memory task and a discrimination task across real and artificial versions of the same faces. We found that real faces were easier to remember, but only slightly more discriminable than artificial faces. Artificial faces were also equally susceptible to the well-known face inversion effect, suggesting that while these patterns are still processed by the human visual system in a face-like manner, artificial appearance does compromise the efficiency of face processing.

  20. Interpretative challenges in face analysis

    DEFF Research Database (Denmark)

    de Oliveira, Sandi Michele; Hernández-Flores, Nieves

    2015-01-01

    In current research on face analysis questions of who and what should be interpreted, as well as how, are of central interest. In English language research, this question has led to a debate on the concepts of P1 (laypersons, representing the “emic” perspective) and P2 (researchers, representing ...

  1. Saving Face and Group Identity

    DEFF Research Database (Denmark)

    Eriksson, Tor; Mao, Lei; Villeval, Marie-Claire

    2015-01-01

    Are people willing to sacrifice resources to save one's and others' face? In a laboratory experiment, we study whether individuals forego resources to avoid the public exposure of the least performer in their group. We show that a majority of individuals are willing to pay to preserve not only th...

  2. Face-Sealing Butterfly Valve

    Science.gov (United States)

    Tervo, John N.

    1992-01-01

    Valve plate made to translate as well as rotate. Valve opened and closed by turning shaft and lever. Interactions among lever, spring, valve plate, and face seal cause plate to undergo combination of translation and rotation so valve plate clears seal during parts of opening and closing motions.

  3. Facing a dark winter. Albania

    Energy Technology Data Exchange (ETDEWEB)

    Truijen, A.

    2007-11-15

    Albania is once again facing a dark winter. The country has already been suffering power cuts lasting a couple of hours a day for the past seventeen years, Drought, increased power consumption and political maladministration are the factors underlying the electricity problems that have now mushroomed into a national crisis.

  4. Quantitative Analysis of Face Symmetry.

    Science.gov (United States)

    Tamir, Abraham

    2015-06-01

    The major objective of this article was to report quantitatively the degree of human face symmetry for reported images taken from the Internet. From the original image of a certain person that appears in the center of each triplet, 2 symmetric combinations were constructed that are based on the left part of the image and its mirror image (left-left) and on the right part of the image and its mirror image (right-right). By applying a computer software that enables to determine length, surface area, and perimeter of any geometric shape, the following measurements were obtained for each triplet: face perimeter and area; distance between the pupils; mouth length; its perimeter and area; nose length and face length, usually below the ears; as well as the area and perimeter of the pupils. Then, for each of the above measurements, the value C, which characterizes the degree of symmetry of the real image with respect to the combinations right-right and left-left, was calculated. C appears on the right-hand side below each image. A high value of C indicates a low symmetry, and as the value is decreasing, the symmetry is increasing. The magnitude on the left relates to the pupils and compares the difference between the area and perimeter of the 2 pupils. The major conclusion arrived at here is that the human face is asymmetric to some degree; the degree of asymmetry is reported quantitatively under each portrait.

  5. The Face of the Moon

    Institute of Scientific and Technical Information of China (English)

    张保

    2001-01-01

    Have you ever seen the man in the moon?If you look closelyat the moon on some nights, you can see the face of the man in themoon. Some people say that they can see an old man carryingsticks. Others see a girl reading a book. These pictures are madeby the mountains (山脉) and plains (平原) of the moon.

  6. Repetition priming from moving faces.

    Science.gov (United States)

    Lander, Karen; Bruce, Vicki

    2004-06-01

    Recent experiments have suggested that seeing a familiar face move provides additional dynamic information to the viewer, useful in the recognition of identity. In four experiments, repetition priming was used to investigate whether dynamic information is intrinsic to the underlying face representations. The results suggest that a moving image primes more effectively than a static image, even when the same static image is shown in the prime and the test phases (Experiment 1). Furthermore, when moving images are presented in the test phase (Experiment 2), there is an advantage for moving prime images. The most priming advantage is found with naturally moving faces, rather than with those shown in slow motion (Experiment 3). Finally, showing the same moving sequence at prime and test produced more priming than that found when different moving sequences were shown (Experiment 4). The results suggest that dynamic information is intrinsic to the face representations and that there is an advantage to viewing the same moving sequence at prime and test.

  7. Continuing Education: Facing the Issues.

    Science.gov (United States)

    Broadbent, Marianne

    1986-01-01

    Examines a number of issues facing the Australian library and information services community in the area of continuing education, including recommendations of the Library Association of Australia, the cost of continuing education activities, the role and responsibility of schools of library and information studies, and notions of coordination.…

  8. Towards automatic forensic face recognition

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond

    2011-01-01

    In this paper we present a methodology and experimental results for evidence evaluation in the context of forensic face recognition. In forensic applications, the matching score (hereafter referred to as similarity score) from a biometric system must be represented as a Likelihood Ratio (LR). In our

  9. The Two Faces of Micropolitics.

    Science.gov (United States)

    Hoyle, Eric

    1999-01-01

    Demystifies the two "faces" of micropolitics. "Policy micropolitics" distinguishes between micropolitics and management and focuses on the relationship between school micropolitics and the wider macropolitical context. "Management micropolitics" makes no clear micropolitics/management distinction and focuses on educators' strategies to pursue…

  10. Cool Styles for Your Face

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    GLASSES are a part of modern fashion. The right spectacle frames can not only add some demureness to you, but also perfect your face. To choose suitable frames for yourself, you must first know your own features. Comb all your hair backwards to show your entire features clearly in front of the

  11. Face Recognition With Neural Networks

    Science.gov (United States)

    1992-12-01

    Ninth Annual Cognitive Science Society Conference, Volume unknown:461-473 (1987). 8. Damasio , Antonio R. "Prosopagnosia," Trends in Neuroscience, 8:132...is also supported by the work of J. C. Meadows and A. R. Damasio in their studies of individuals who have lost the ability to recognize faces, a

  12. Interpretative challenges in face analysis

    DEFF Research Database (Denmark)

    de Oliveira, Sandi Michele; Hernández-Flores, Nieves

    2015-01-01

    In current research on face analysis questions of who and what should be interpreted, as well as how, are of central interest. In English language research, this question has led to a debate on the concepts of P1 (laypersons, representing the “emic” perspective) and P2 (researchers, representing ...

  13. 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.

  14. Learning Race from Face: A Survey.

    Science.gov (United States)

    Fu, Siyao; He, Haibo; Hou, Zeng-Guang

    2014-12-01

    Faces convey a wealth of social signals, including race, expression, identity, age and gender, all of which have attracted increasing attention from multi-disciplinary research, such as psychology, neuroscience, computer science, to name a few. Gleaned from recent advances in computer vision, computer graphics, and machine learning, computational intelligence based racial face analysis has been particularly popular due to its significant potential and broader impacts in extensive real-world applications, such as security and defense, surveillance, human computer interface (HCI), biometric-based identification, among others. These studies raise an important question: How implicit, non-declarative racial category can be conceptually modeled and quantitatively inferred from the face? Nevertheless, race classification is challenging due to its ambiguity and complexity depending on context and criteria. To address this challenge, recently, significant efforts have been reported toward race detection and categorization in the community. This survey provides a comprehensive and critical review of the state-of-the-art advances in face-race perception, principles, algorithms, and applications. We first discuss race perception problem formulation and motivation, while highlighting the conceptual potentials of racial face processing. Next, taxonomy of feature representational models, algorithms, performance and racial databases are presented with systematic discussions within the unified learning scenario. Finally, in order to stimulate future research in this field, we also highlight the major opportunities and challenges, as well as potentially important cross-cutting themes and research directions for the issue of learning race from face.

  15. Face to Face : The Perception of Automotive Designs.

    Science.gov (United States)

    Windhager, Sonja; Slice, Dennis E; Schaefer, Katrin; Oberzaucher, Elisabeth; Thorstensen, Truls; Grammer, Karl

    2008-12-01

    Over evolutionary time, humans have developed a selective sensitivity to features in the human face that convey information on sex, age, emotions, and intentions. This ability might not only be applied to our conspecifics nowadays, but also to other living objects (i.e., animals) and even to artificial structures, such as cars. To investigate this possibility, we asked people to report the characteristics, emotions, personality traits, and attitudes they attribute to car fronts, and we used geometric morphometrics (GM) and multivariate statistical methods to determine and visualize the corresponding shape information. Automotive features and proportions are found to covary with trait perception in a manner similar to that found with human faces. Emerging analogies are discussed. This study should have implications for both our understanding of our prehistoric psyche and its interrelation with the modern world.

  16. Item Nonresponse in Face-to-Face Interviews with Children

    Directory of Open Access Journals (Sweden)

    Haunberger Sigrid

    2014-09-01

    Full Text Available This study examined item nonresponse and its respondent and interviewer correlates by means of a population-based, panel survey of children aged 8 to 11 who were surveyed using standardised, face-to-face interviews. Using multilevel, logistic analyses with cross-level interactions, this article aims to examine which effects of item nonresponse are subject to children as respondents or to the interviewers and the interview setting. Depending on the type of question, we found different effects for respondent and interviewer variables, as well as interaction effects between child age/interviewer age as well as child gender/interviewer gender. However, interviewer variance is for the most part not significant.

  17. Recognizing Faces with Partial Occlusion using Inpainting

    National Research Council Canada - National Science Library

    Vijayalakshmi A

    2017-01-01

    .... In this paper, a hybrid inpainting approach is followed to recover the lost region of a face. This approach increases the recognition rate of faces that are occluded. Experimental result on hybrid inpainting proves that the recognition rate on faces increases on comparison with existing methods on occluded faces.

  18. Holistic Processing of Static and Moving Faces

    Science.gov (United States)

    Zhao, Mintao; Bülthoff, Isabelle

    2017-01-01

    Humans' face ability develops and matures with extensive experience in perceiving, recognizing, and interacting with faces that move most of the time. However, how facial movements affect 1 core aspect of face ability--holistic face processing--remains unclear. Here we investigated the influence of rigid facial motion on holistic and part-based…

  19. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  20. 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。

  1. 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.

  2. Unconstrained Face Verification using Deep CNN Features

    OpenAIRE

    Chen, Jun-Cheng; Patel, Vishal M.; Chellappa, Rama

    2015-01-01

    In this paper, we present an algorithm for unconstrained face verification based on deep convolutional features and evaluate it on the newly released IARPA Janus Benchmark A (IJB-A) dataset. The IJB-A dataset includes real-world unconstrained faces from 500 subjects with full pose and illumination variations which are much harder than the traditional Labeled Face in the Wild (LFW) and Youtube Face (YTF) datasets. The deep convolutional neural network (DCNN) is trained using the CASIA-WebFace ...

  3. Perceptual load effects on processing distractor faces indicate face-specific capacity limits

    OpenAIRE

    Thoma, Volker; Lavie, Nilli

    2013-01-01

    The claim that face perception is mediated by a specialized ‘face module’ that proceeds automatically, independently of attention (e.g., Kanwisher, 2000) can be reconciled with load theory claims that visual perception has limited capacity (e.g., Lavie, 1995) by hypothesizing that face perception has face-specific capacity limits. We tested this hypothesis by comparing the effects of face and non-face perceptual load on distractor face processing. Participants searched a central array of eith...

  4. The Thatcher Illusion and Face Processing in Infancy

    Science.gov (United States)

    Bertin, Evelin; Bhatt, Ramesh S.

    2004-01-01

    Adults readily detect changes in face patterns brought about by the inversion of eyes and mouth when the faces are viewed upright but not when they are viewed upside down. Research suggests that this illusion (the Thatcher illusion) is caused by the interfering effects of face inversion on the processing of second-order relational information…

  5. Social Cognition in Williams Syndrome: Face Tuning.

    Science.gov (United States)

    Pavlova, Marina A; Heiz, Julie; Sokolov, Alexander N; Barisnikov, Koviljka

    2016-01-01

    Many neurological, neurodevelopmental, neuropsychiatric, and psychosomatic disorders are characterized by impairments in visual social cognition, body language reading, and facial assessment of a social counterpart. Yet a wealth of research indicates that individuals with Williams syndrome exhibit remarkable concern for social stimuli and face fascination. Here individuals with Williams syndrome were presented with a set of Face-n-Food images composed of food ingredients and in different degree resembling a face (slightly bordering on the Giuseppe Arcimboldo style). The primary advantage of these images is that single components do not explicitly trigger face-specific processing, whereas in face images commonly used for investigating face perception (such as photographs or depictions), the mere occurrence of typical cues already implicates face presence. In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Strikingly, individuals with Williams syndrome exhibited profound deficits in recognition of the Face-n-Food images as a face: they did not report seeing a face on the images, which typically developing controls effortlessly recognized as a face, and gave overall fewer face responses. This suggests atypical face tuning in Williams syndrome. The outcome is discussed in the light of a general pattern of social cognition in Williams syndrome and brain mechanisms underpinning face processing.

  6. Social cognition in Williams syndrome: face tuning

    Directory of Open Access Journals (Sweden)

    Marina A Pavlova

    2016-08-01

    Full Text Available Many neurological, neurodevelopmental, neuropsychiatric and psychosomatic disorders are characterized by impairments in visual social cognition, body language reading, and facial assessment of a social counterpart. Yet a wealth of research indicates that individuals with Williams syndrome exhibit remarkable concern for social stimuli and face fascination. Here individuals with Williams syndrome were presented with a set of Face-n-Food images composed of food ingredients and in different degree resembling a face (slightly bordering on the Giuseppe Arcimboldo style. The primary advantage of these images is that single components do not explicitly trigger face-specific processing, whereas in face images commonly used for investigating face perception (such as photographs or depictions, the mere occurrence of typical cues already implicates face presence. In a spontaneous recognition task, participants were shown a set of images in a predetermined order from the least to most resembling a face. Strikingly, individuals with Williams syndrome exhibited profound deficits in recognition of the Face-n-Food images as a face: they did not report seeing a face on the images, which typically developing controls effortlessly recognized as a face, and gave overall fewer face responses. This suggests atypical face tuning in Williams syndrome. The outcome is discussed in the light of a general pattern of social cognition in Williams syndrome and brain mechanisms underpinning face processing.

  7. Markerless 3D Face Tracking

    DEFF Research Database (Denmark)

    Walder, Christian; Breidt, Martin; Bulthoff, Heinrich

    2009-01-01

    We present a novel algorithm for the markerless tracking of deforming surfaces such as faces. We acquire a sequence of 3D scans along with color images at 40Hz. The data is then represented by implicit surface and color functions, using a novel partition-of-unity type method of efficiently...... combining local regressors using nearest neighbor searches. Both these functions act on the 4D space of 3D plus time, and use temporal information to handle the noise in individual scans. After interactive registration of a template mesh to the first frame, it is then automatically deformed to track...... the scanned surface, using the variation of both shape and color as features in a dynamic energy minimization problem. Our prototype system yields high-quality animated 3D models in correspondence, at a rate of approximately twenty seconds per timestep. Tracking results for faces and other objects...

  8. Processing faces and facial expressions.

    Science.gov (United States)

    Posamentier, Mette T; Abdi, Hervé

    2003-09-01

    This paper reviews processing of facial identity and expressions. The issue of independence of these two systems for these tasks has been addressed from different approaches over the past 25 years. More recently, neuroimaging techniques have provided researchers with new tools to investigate how facial information is processed in the brain. First, findings from "traditional" approaches to identity and expression processing are summarized. The review then covers findings from neuroimaging studies on face perception, recognition, and encoding. Processing of the basic facial expressions is detailed in light of behavioral and neuroimaging data. Whereas data from experimental and neuropsychological studies support the existence of two systems, the neuroimaging literature yields a less clear picture because it shows considerable overlap in activation patterns in response to the different face-processing tasks. Further, activation patterns in response to facial expressions support the notion of involved neural substrates for processing different facial expressions.

  9. The IMM Frontal Face Database

    DEFF Research Database (Denmark)

    Fagertun, Jens; Stegmann, Mikkel Bille

    2005-01-01

    This note describes a data set consisting of 120 annotated monocular images of 12 different frontal human faces. Points of correspondence are placed on each image so the data set can be readily used for building statistical models of shape. Format specifications and terms of use are also given in...... in this note. The data set is available in two versions: i) low resolution, given in the zip-file electronic version, ii) high, given in the publication link....

  10. 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…

  11. Human Face Recognition Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Răzvan-Daniel Albu

    2009-10-01

    Full Text Available In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. The convolutional network extracts successively larger features in a hierarchical set of layers. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.

  12. Online or Face to Face? A Comparison of Two Methods of Training Professionals

    Science.gov (United States)

    Dillon, Kristin; Dworkin, Jodi; Gengler, Colleen; Olson, Kathleen

    2008-01-01

    Online courses offer benefits over face-to-face courses such as accessibility, affordability, and flexibility. Literature assessing the effectiveness of face-to-face and online courses is growing, but findings remain inconclusive. This study compared evaluations completed by professionals who had taken a research update short course either face to…

  13. Familiar Face Recognition in Children with Autism: The Differential Use of Inner and Outer Face Parts

    Science.gov (United States)

    Wilson, Rebecca; Pascalis, Olivier; Blades, Mark

    2007-01-01

    We investigated whether children with autistic spectrum disorders (ASD) have a deficit in recognising familiar faces. Children with ASD were given a forced choice familiar face recognition task with three conditions: full faces, inner face parts and outer face parts. Control groups were children with developmental delay (DD) and typically…

  14. [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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Face-to-face or not-to-face: A technology preference for communication.

    Science.gov (United States)

    Jaafar, Noor Ismawati; Darmawan, Bobby; Mohamed Ariffin, Mohd Yahya

    2014-11-01

    This study employed the Model of Technology Preference (MTP) to explain the relationship of the variables as the antecedents of behavioral intention to adopt a social networking site (SNS) for communication. Self-administered questionnaires were distributed to SNS account users using paper-based and web-based surveys that led to 514 valid responses. The data were analyzed using structural equation modeling (SEM). The results show that two out of three attributes of the attribute-based preference (ATRP) affect attitude-based preference (ATTP). The data support the hypotheses that perceived enjoyment and social presence are predictors of ATTP. In this study, the findings further indicated that ATTP has no relationship with the behavioral intention of using SNS, but it has a relationship with the attitude of using SNS. SNS development should provide features that ensure enjoyment and social presence for users to communicate instead of using the traditional face-to-face method of communication.

  2. 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.

  3. Human face processing is tuned to sexual age preferences

    DEFF Research Database (Denmark)

    Ponseti, J; Granert, O; van Eimeren, T

    2014-01-01

    . In paedophilia, sexual attraction is directed to sexually immature children. Therefore, we hypothesized that brain networks that normally are tuned to mature faces of the preferred gender show an abnormal tuning to sexual immature faces in paedophilia. Here, we use functional magnetic resonance imaging (f......Human faces can motivate nurturing behaviour or sexual behaviour when adults see a child or an adult face, respectively. This suggests that face processing is tuned to detecting age cues of sexual maturity to stimulate the appropriate reproductive behaviour: either caretaking or mating......MRI) to test directly for the existence of a network which is tuned to face cues of sexual maturity. During fMRI, participants sexually attracted to either adults or children were exposed to various face images. In individuals attracted to adults, adult faces activated several brain regions significantly more...

  4. 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.

  5. 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.

  6. The MUSE project face to face with reality

    Science.gov (United States)

    Caillier, P.; Accardo, M.; Adjali, L.; Anwand, H.; Bacon, Roland; Boudon, D.; Brotons, L.; Capoani, L.; Daguisé, E.; Dupieux, M.; Dupuy, C.; François, M.; Glindemann, A.; Gojak, D.; Hansali, G.; Hahn, T.; Jarno, A.; Kelz, A.; Koehler, C.; Kosmalski, J.; Laurent, F.; Le Floch, M.; Lizon, J.-L.; Loupias, M.; Manescau, A.; Migniau, J. E.; Monstein, C.; Nicklas, H.; Parès, L.; Pécontal-Rousset, A.; Piqueras, L.; Reiss, R.; Remillieux, A.; Renault, E.; Rupprecht, G.; Streicher, O.; Stuik, R.; Valentin, H.; Vernet, J.; Weilbacher, P.; Zins, G.

    2012-09-01

    MUSE (Multi Unit Spectroscopic Explorer) is a second generation instrument built for ESO (European Southern Observatory) to be installed in Chile on the VLT (Very Large Telescope). The MUSE project is supported by a European consortium of 7 institutes. After the critical turning point of shifting from the design to the manufacturing phase, the MUSE project has now completed the realization of its different sub-systems and should finalize its global integration and test in Europe. To arrive to this point many challenges had to be overcome, many technical difficulties, non compliances or procurements delays which seemed at the time overwhelming. Now is the time to face the results of our organization, of our strategy, of our choices. Now is the time to face the reality of the MUSE instrument. During the design phase a plan was provided by the project management in order to achieve the realization of the MUSE instrument in specification, time and cost. This critical moment in the project life when the instrument takes shape and reality is the opportunity to look not only at the outcome but also to see how well we followed the original plan, what had to be changed or adapted and what should have been.

  7. Women are better at seeing faces where there are none: an ERP study of face pareidolia.

    Science.gov (United States)

    Proverbio, Alice M; Galli, Jessica

    2016-09-01

    Event-related potentials (ERPs) were recorded in 26 right-handed students while they detected pictures of animals intermixed with those of familiar objects, faces and faces-in-things (FITs). The face-specific N170 ERP component over the right hemisphere was larger in response to faces and FITs than to objects. The vertex positive potential (VPP) showed a difference in FIT encoding processes between males and females at frontal sites; while for men, the FIT stimuli elicited a VPP of intermediate amplitude (between that for faces and objects), for women, there was no difference in VPP responses to faces or FITs, suggesting a marked anthropomorphization of objects in women. SwLORETA source reconstructions carried out to estimate the intracortical generators of ERPs in the 150-190 ms time window showed how, in the female brain, FIT perception was associated with the activation of brain areas involved in the affective processing of faces (right STS, BA22; posterior cingulate cortex, BA22; and orbitofrontal cortex, BA10) in addition to regions linked to shape processing (left cuneus, BA18/30). Conversely, in the men, the activation of occipito/parietal regions was prevalent, with a considerably smaller activation of BA10. The data suggest that the female brain is more inclined to anthropomorphize perfectly real objects compared to the male brain.

  8. 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.

  9. 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.

  10. Seeing a haptically explored face: visual facial-expression aftereffect from haptic adaptation to a face.

    Science.gov (United States)

    Matsumiya, Kazumichi

    2013-10-01

    Current views on face perception assume that the visual system receives only visual facial signals. However, I show that the visual perception of faces is systematically biased by adaptation to a haptically explored face. Recently, face aftereffects (FAEs; the altered perception of faces after adaptation to a face) have been demonstrated not only in visual perception but also in haptic perception; therefore, I combined the two FAEs to examine whether the visual system receives face-related signals from the haptic modality. I found that adaptation to a haptically explored facial expression on a face mask produced a visual FAE for facial expression. This cross-modal FAE was not due to explicitly imaging a face, response bias, or adaptation to local features. Furthermore, FAEs transferred from vision to haptics. These results indicate that visual face processing depends on substrates adapted by haptic faces, which suggests that face processing relies on shared representation underlying cross-modal interactions.

  11. Normal composite face effects in developmental prosopagnosia.

    Science.gov (United States)

    Biotti, Federica; Wu, Esther; Yang, Hua; Jiahui, Guo; Duchaine, Bradley; Cook, Richard

    2017-08-10

    Upright face perception is thought to involve holistic processing, whereby local features are integrated into a unified whole. Consistent with this view, the top half of one face appears to fuse perceptually with the bottom half of another, when aligned spatially and presented upright. This 'composite face effect' reveals a tendency to integrate information from disparate regions when faces are presented canonically. In recent years, the relationship between susceptibility to the composite effect and face recognition ability has received extensive attention both in participants with normal face recognition and participants with developmental prosopagnosia. Previous results suggest that individuals with developmental prosopagnosia may show reduced susceptibility to the effect suggestive of diminished holistic face processing. Here we describe two studies that examine whether developmental prosopagnosia is associated with reduced composite face effects. Despite using independent samples of developmental prosopagnosics and different composite procedures, we find no evidence for reduced composite face effects. The experiments yielded similar results; highly significant composite effects in both prosopagnosic groups that were similar in magnitude to the effects found in participants with normal face processing. The composite face effects exhibited by both samples and the controls were greatly diminished when stimulus arrangements were inverted. Our finding that the whole-face binding process indexed by the composite effect is intact in developmental prosopagnosia indicates that other factors are responsible for developmental prosopagnosia. These results are also inconsistent with suggestions that susceptibility to the composite face effect and face recognition ability are tightly linked. While the holistic process revealed by the composite face effect may be necessary for typical face perception, it is not sufficient; individual differences in face recognition ability

  12. Robust Face Image Matching under Illumination Variations

    Directory of Open Access Journals (Sweden)

    Yang Chyuan-Huei Thomas

    2004-01-01

    Full Text Available Face image matching is an essential step for face recognition and face verification. It is difficult to achieve robust face matching under various image acquisition conditions. In this paper, a novel face image matching algorithm robust against illumination variations is proposed. The proposed image matching algorithm is motivated by the characteristics of high image gradient along the face contours. We define a new consistency measure as the inner product between two normalized gradient vectors at the corresponding locations in two images. The normalized gradient is obtained by dividing the computed gradient vector by the corresponding locally maximal gradient magnitude. Then we compute the average consistency measures for all pairs of the corresponding face contour pixels to be the robust matching measure between two face images. To alleviate the problem due to shadow and intensity saturation, we introduce an intensity weighting function for each individual consistency measure to form a weighted average of the consistency measure. This robust consistency measure is further extended to integrate multiple face images of the same person captured under different illumination conditions, thus making our robust face matching algorithm. Experimental results of applying the proposed face image matching algorithm on some well-known face datasets are given in comparison with some existing face recognition methods. The results show that the proposed algorithm consistently outperforms other methods and achieves higher than 93% recognition rate with three reference images for different datasets under different lighting conditions.

  13. 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.

  14. PCA Based Rapid and Real Time Face Recognition Technique

    Directory of Open Access Journals (Sweden)

    T R Chandrashekar

    2013-12-01

    Full Text Available Economical and efficient that is used in various applications is face Biometric which has been a popular form biometric system. Face recognition system is being a topic of research for last few decades. Several techniques are proposed to improve the performance of face recognition system. Accuracy is tested against intensity, distance from camera, and pose variance. Multiple face recognition is another subtopic which is under research now a day. Speed at which the technique works is a parameter under consideration to evaluate a technique. As an example a support vector machine performs really well for face recognition but the computational efficiency degrades significantly with increase in number of classes. Eigen Face technique produces quality features for face recognition but the accuracy is proved to be comparatively less to many other techniques. With increase in use of core processors in personal computers and application demanding speed in processing and multiple face detection and recognition system (for example an entry detection system in shopping mall or an industry, demand for such systems are cumulative as there is a need for automated systems worldwide. In this paper we propose a novel system of face recognition developed with C# .Net that can detect multiple faces and can recognize the faces parallel by utilizing the system resources and the core processors. The system is built around Haar Cascade based face detection and PCA based face recognition system with C#.Net. Parallel library designed for .Net is used to aide to high speed detection and recognition of the real time faces. Analysis of the performance of the proposed technique with some of the conventional techniques reveals that the proposed technique is not only accurate, but also is fast in comparison to other techniques.

  15. Facing Tomorrow's Challenges - An Overview

    Science.gov (United States)

    ,

    2008-01-01

    In 2007, the U.S. Geological Survey (USGS) developed a science strategy outlining the major natural-science issues facing the Nation in the next decade. The science strategy consists of six science directions of critical importance, focusing on areas where natural science can make a substantial contribution to the well-being of the Nation and the world. This fact sheet is an overview of the science strategy and describes how USGS research can strengthen the Nation with information needed to meet the challenges of the 21st century.

  16. Urbanize or Face the Consequences

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    China’s complex economic situation has been unprecedentedly challenged since the reform and opening-up policy adopted three decades ago. In an article published in the May 14 issue of Caijing magazine, Guo Shuqing,President of China Construction Bank, one of China’s four state-owned commercial lenders, stressed that the issues of agriculture, rural areas and farmers are the biggest challenges facing the country’s economic stability.Guo says only through an exceptional urbanization process can rapidly advancing social development be maintained. Excerpts:

  17. REAL TIME FACE RECOGNITION USING ADABOOST IMPROVED FAST PCA ALGORITHM

    Directory of Open Access Journals (Sweden)

    K. Susheel Kumar

    2011-08-01

    Full Text Available This paper presents an automated system for human face recognition in a real time background world fora large homemade dataset of persons face. The task is very difficult as the real time backgroundsubtraction in an image is still a challenge. Addition to this there is a huge variation in human face imagein terms of size, pose and expression. The system proposed collapses most of this variance. To detect realtime human face AdaBoost with Haar cascade is used and a simple fast PCA and LDA is used torecognize the faces detected. The matched face is then used to mark attendance in the laboratory, in ourcase. This biometric system is a real time attendance system based on the human face recognition with asimple and fast algorithms and gaining a high accuracy rate..

  18. 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

  19. Real-Time Gender Classification by Face

    Directory of Open Access Journals (Sweden)

    Eman Fares Al Mashagba

    2016-03-01

    Full Text Available The identification of human beings based on their biometric body parts, such as face, fingerprint, gait, iris, and voice, plays an important role in electronic applications and has become a popular area of research in image processing. It is also one of the most successful applications of computer–human interaction and understanding. Out of all the abovementioned body parts,the face is one of most popular traits because of its unique features.In fact, individuals can process a face in a variety of ways to classify it by its identity, along with a number of other characteristics, such as gender, ethnicity, and age. Specifically, recognizing human gender is important because people respond differently according to gender. In this paper, we present a robust method that uses global geometry-based features to classify gender and identify age and human beings from video sequences. The features are extracted based on face detection using skin color segmentation and the computed geometric features of the face ellipse region. These geometric features are then used to form the face vector trajectories, which are inputted to a time delay neural network and are trained using the Broyden–Fletcher–Goldfarb–Shanno (BFGS function. Results show that using the suggested method with our own dataset under an unconstrained condition achieves a 100% classification rate in the training set for all application, as well as 91.2% for gender classification, 88% for age identification, and 83% for human identification in the testing set. In addition, the proposed method establishes the real-time system to be used in three applications with a simple computation for feature extraction.

  20. Validity, Sensitivity, and Responsiveness of the 11-Face Faces Pain Scale to Postoperative Pain in Adult Orthopedic Surgery Patients.

    Science.gov (United States)

    Van Giang, Nguyen; Chiu, Hsiao-Yean; Thai, Duong Hong; Kuo, Shu-Yu; Tsai, Pei-Shan

    2015-10-01

    Pain is common in patients after orthopedic surgery. The 11-face Faces Pain Scale has not been validated for use in adult patients with postoperative pain. To assess the validity of the 11-face Faces Pain Scale and its ability to detect responses to pain medications, and to determine whether the sensitivity of the 11-face Faces Pain Scale for detecting changes in pain intensity over time is associated with gender differences in adult postorthopedic surgery patients. The 11-face Faces Pain Scale was translated into Vietnamese using forward and back translation. Postoperative pain was assessed using an 11-point numerical rating scale and the 11-face Faces Pain Scale on the day of surgery, and before (Time 1) and every 30 minutes after (Times 2-5) the patients had taken pain medications on the first postoperative day. The 11-face Faces Pain Scale highly correlated with the numerical rating scale (r = 0.78, p pain intensity, but not gender-time interaction effect, over the five time points was significant (F = 182.03, p Pain Scale is appropriate for measuring acute postoperative pain in adults.

  1. Attractive faces temporally modulate visual attention

    Directory of Open Access Journals (Sweden)

    Koyo eNakamura

    2014-06-01

    Full Text Available Facial attractiveness is an important biological and social signal on social interaction. Recent research has demonstrated that an attractive face captures greater spatial attention than an unattractive face does. Little is known, however, about the temporal characteristics of visual attention for facial attractiveness. In this study, we investigated the temporal modulation of visual attention induced by facial attractiveness by using a rapid serial visual presentation (RSVP. Fourteen male faces and two female faces were successively presented for 160 ms respectively, and participants were asked to identify two female faces embedded among a series of multiple male distractor faces. Identification of a second female target (T2 was impaired when a first target (T1 was attractive compared to neutral or unattractive faces, at 320 ms SOA; identification was improved when T1 was attractive compared to unattractive faces at 640 ms SOA. These findings suggest that the spontaneous appraisal of facial attractiveness modulates temporal attention.

  2. Facing Diabetes: What You Need to Know

    Science.gov (United States)

    ... of this page please turn Javascript on. Feature: Diabetes Facing Diabetes: What You Need to Know Past Issues / Fall ... your loved ones. Photos: AP The Faces of Diabetes Diabetes strikes millions of Americans, young and old, ...

  3. Robust multi-camera view face recognition

    CERN Document Server

    Kisku, Dakshina Ranjan; Gupta, Phalguni; Sing, Jamuna Kanta

    2010-01-01

    This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recognition (verification) system. The generalization of LDA has been extended to establish correlations between the face classes in the transformed representation and this is called canonical covariate. The proposed system uses Gabor filter banks for characterization of facial features by spatial frequency, spatial locality and orientation to make compensate to the variations of face instances occurred due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images produces Gabor face representations with high dimensional feature vectors. PCA and canonical covariate are then applied on the Gabor face representations to reduce the high dimensional feature spaces into low dimensional Gabor eigenfaces and Gabor canonical faces. Reduced eigenface vector and canonical face vector are fused together usi...

  4. A ROBUST EYE LOCALIZATION ALGORITHM FOR FACE RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    Zhang Wencong; Li Xin; Yao Peng; Li Bin; Zhuang Zhenquan

    2008-01-01

    The accuracy of face alignment affects greatly the performance of a face recognition system.Since the face alignment is usually conducted using eye positions, the algorithm for accurate eye localization is essential for the accurate face recognition. In this paper, an algorithm is proposed for eye localization. First, the proper AdaBoost detection is adaptively trained to segment the region based on the special gray distribution in the region. After that, a fast radial symmetry operator is used to precisely locate the center of eyes. Experimental results show that the method can accurately locate the eyes, and it is robust to the variations of face poses, illuminations, expressions, and accessories.

  5. Misaligned and Polarity-Reversed Faces Determine Face-specific Capacity Limits

    Science.gov (United States)

    Thoma, Volker; Ward, Neil; de Fockert, Jan W.

    2016-01-01

    Previous research using flanker paradigms suggests that peripheral distracter faces are automatically processed when participants have to classify a single central familiar target face. These distracter interference effects disappear when the central task contains additional anonymous (non-target) faces that load the search for the face target, but not when the central task contains additional non-face stimuli, suggesting there are face-specific capacity limits in visual processing. Here we tested whether manipulating the format of non-target faces in the search task affected face-specific capacity limits. Experiment 1 replicated earlier findings that a distracter face is processed even in high load conditions when participants looked for a target name of a famous person among additional names (non-targets) in a central search array. Two further experiments show that when targets and non-targets were faces (instead of names), however, distracter interference was eliminated under high load—adding non-target faces to the search array exhausted processing capacity for peripheral faces. The novel finding was that replacing non-target faces with images that consisted of two horizontally misaligned face-parts reduced distracter processing. Similar results were found when the polarity of a non-target face image was reversed. These results indicate that face-specific capacity limits are not determined by the configural properties of face processing, but by face parts. PMID:27729889

  6. 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.

  7. Prevalence of face recognition deficits in middle childhood.

    Science.gov (United States)

    Bennetts, Rachel J; Murray, Ebony; Boyce, Tian; Bate, Sarah

    2017-02-01

    Approximately 2-2.5% of the adult population is believed to show severe difficulties with face recognition, in the absence of any neurological injury-a condition known as developmental prosopagnosia (DP). However, to date no research has attempted to estimate the prevalence of face recognition deficits in children, possibly because there are very few child-friendly, well-validated tests of face recognition. In the current study, we examined face and object recognition in a group of primary school children (aged 5-11 years), to establish whether our tests were suitable for children and to provide an estimate of face recognition difficulties in children. In Experiment 1 (n = 184), children completed a pre-existing test of child face memory, the Cambridge Face Memory Test-Kids (CFMT-K), and a bicycle test with the same format. In Experiment 2 (n = 413), children completed three-alternative forced-choice matching tasks with faces and bicycles. All tests showed good psychometric properties. The face and bicycle tests were well matched for difficulty and showed a similar developmental trajectory. Neither the memory nor the matching tests were suitable to detect impairments in the youngest groups of children, but both tests appear suitable to screen for face recognition problems in middle childhood. In the current sample, 1.2-5.2% of children showed difficulties with face recognition; 1.2-4% showed face-specific difficulties-that is, poor face recognition with typical object recognition abilities. This is somewhat higher than previous adult estimates: It is possible that face matching tests overestimate the prevalence of face recognition difficulties in children; alternatively, some children may "outgrow" face recognition difficulties.

  8. [Face rejuvenation with tensor threads].

    Science.gov (United States)

    Cornette de Saint Cyr, B; Benouaiche, L

    2017-08-25

    The last decades has seen new priorities in treatment of a flabby, ageing face towards minimally invasive aesthetic surgery, to be accompanied and followed by the requirements to perform such interventions with the maximally reduced health hazards, with inconsiderable injury, without cuts and, respectively, to be followed by no resulting scars, as well as a short postoperative period. We propose a new reviewing presentation of the tensor threads. After having explained the technology of the threads, we will discuss the good patient indication, the criteria which determine the choice of the threads and methods for each type of patient. There are many techniques, which we will present. Then, we will discuss the results, unsatisfactory outcomes obtained and complications encountered, as well as how to improve the cosmetic outcomes to be obtained. To conclude, we will propose a strategy for the long-term treatment of the neck and the face, preventing surgical management of the aging process. Copyright © 2017. Published by Elsevier Masson SAS.

  9. Facing sound – voicing art

    Directory of Open Access Journals (Sweden)

    Ansa Lønstrup

    2013-12-01

    Full Text Available This article is based on examples of contemporary audiovisual art with a primary focus on the Tony Oursler solo exhibition Face to Face in Aarhus Art Museum ARoS, 2012. My investigation involves a combination of qualitative interviews with visitors, observations of the audience’s interactions with the exhibition and the artwork in the museum space, and short analyses of individual works of art based on reception aesthetics, phenomenology, and newer writings on sound, voice and listening. The focus of the investigation is the quality and possible perspectives of the interaction with audiovisual works of art, articulating and sounding out their own ‘voices’. This methodological combination has been chosen to transgress the dichotomy between the aesthetic or hermeneutic artwork ‘text’ analysis and cultural theory, which focuses on the context understood as the framing, the cultural acts and agendas around the aesthetic ‘text’. The article will include experiences with another exhibition, David Lynch: The Air is on Fire (Fondation Cartier pour l’art contemporain, Paris, 2007 and Kunstforeningen Gl. Strand, Copenhagen, 2010- 2011. The two exhibitions are fundamentally different in their integration of sound. My field of interest concerns the exploration of sound as artistic material in audiovisual combinations and those audiovisual works of art that might cause a change in the participatory strategy of the art museum towards the audience.

  10. Age Dependent Face Recognition using Eigenface

    OpenAIRE

    Hlaing Htake Khaung Tin

    2013-01-01

    Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human comp...

  11. Trustworthy-Looking Face Meets Brown Eyes

    OpenAIRE

    Karel Kleisner; Lenka Priplatova; Peter Frost; Jaroslav Flegr

    2013-01-01

    We tested whether eye color influences perception of trustworthiness. Facial photographs of 40 female and 40 male students were rated for perceived trustworthiness. Eye color had a significant effect, the brown-eyed faces being perceived as more trustworthy than the blue-eyed ones. Geometric morphometrics, however, revealed significant correlations between eye color and face shape. Thus, face shape likewise had a significant effect on perceived trustworthiness but only for male faces, the eff...

  12. 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.

  13. 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.

  14. Face identification in videos from mobile cameras

    NARCIS (Netherlands)

    Mu, Meiru; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2014-01-01

    It is still challenging to recognize faces reliably in videos from mobile camera, although mature automatic face recognition technology for still images has been available for quite some time. Suppose we want to be alerted when suspects appear in the recording of a police Body-Cam, even a good face

  15. The improved relative entropy for face recognition

    Directory of Open Access Journals (Sweden)

    Zhang Qi Rong

    2016-01-01

    Full Text Available The relative entropy is least sensitive to noise. In this paper, we propose the improved relative entropy for face recognition (IRE. The IRE method of recognition rate is far higher than the LDA, LPP method, by experimental results on CMU PIE face database and YALE B face database.

  16. 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...

  17. AN ADVANCED SCALE INVARIANT FEATURE TRANSFORM ALGORITHM FOR FACE RECOGNITION

    OpenAIRE

    Mohammad Mohsen Ahmadinejad; Elizabeth Sherly

    2016-01-01

    In computer vision, Scale-invariant feature transform (SIFT) algorithm is widely used to describe and detect local features in images due to its excellent performance. But for face recognition, the implementation of SIFT was complicated because of detecting false key-points in the face image due to irrelevant portions like hair style and other background details. This paper proposes an algorithm for face recognition to improve recognition accuracy by selecting relevant SIFT key-points only th...

  18. SPECFACE - A Dataset of Human Faces Wearing Spectacles

    OpenAIRE

    2015-01-01

    This paper presents a database of human faces for persons wearing spectacles. The database consists of images of faces having significant variations with respect to illumination, head pose, skin color, facial expressions and sizes, and nature of spectacles. The database contains data of 60 subjects. This database is expected to be a precious resource for the development and evaluation of algorithms for face detection, eye detection, head tracking, eye gaze tracking, etc., for subjects wearing...

  19. The special status of sad infant faces: age and valence differences in adults' cortical face processing.

    Science.gov (United States)

    Colasante, Tyler; Mossad, Sarah I; Dudek, Joanna; Haley, David W

    2016-12-20

    Understanding the relative and joint prioritization of age- and valence-related face characteristics in adults' cortical face processing remains elusive because these two characteristics have not been manipulated in a single study of neural face processing. We used electroencephalography to investigate adults' P1, N170, P2 and LPP responses to infant and adult faces with happy and sad facial expressions. Viewing infant vs adult faces was associated with significantly larger P1, N170, P2 and LPP responses, with hemisphere and/or participant gender moderating this effect in select cases. Sad faces were associated with significantly larger N170 responses than happy faces. Sad infant faces were associated with significantly larger N170 responses in the right hemisphere than all other combinations of face age and face valence characteristics. We discuss the relative and joint neural prioritization of infant face characteristics and negative facial affect, and their biological value as distinct caregiving and social cues.

  20. Sex-contingent face after-effects suggest distinct neural populations code male and female faces.

    Science.gov (United States)

    Little, Anthony C; DeBruine, Lisa M; Jones, Benedict C

    2005-11-01

    Exposure to faces biases perceptions of subsequently viewed faces. Faces similar to those seen previously are judged more normal and attractive than they were prior to exposure. Here we show sex-contingent after-effects following adaptation to eye-spacing (experiment 1), facial identity (experiment 2) and masculinity (experiment 3). Viewing faces of one sex with increased eye-spacing and faces of the other sex with decreased eye-spacing simultaneously induced opposite after-effects for male and female faces (assessed by normality judgments). Viewing faces transformed in identity or masculinity increased preferences for novel faces with characteristics similar to those viewed only when the sex of the faces presented in the adaptation phase and in post-adaptation preference tests were congruent. Because after-effects reflect changes in responses of neural populations that code faces, our findings indicate that distinct neural populations code male and female faces.

  1. 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.

  2. What’s in a Face? How Face Gender and Current Affect Influence Perceived Emotion

    Science.gov (United States)

    Harris, Daniel A.; Hayes-Skelton, Sarah A.; Ciaramitaro, Vivian M.

    2016-01-01

    Faces drive our social interactions. A vast literature suggests an interaction between gender and emotional face perception, with studies using different methodologies demonstrating that the gender of a face can affect how emotions are processed. However, how different is our perception of affective male and female faces? Furthermore, how does our current affective state when viewing faces influence our perceptual biases? We presented participants with a series of faces morphed along an emotional continuum from happy to angry. Participants judged each face morph as either happy or angry. We determined each participant’s unique emotional ‘neutral’ point, defined as the face morph judged to be perceived equally happy and angry, separately for male and female faces. We also assessed how current state affect influenced these perceptual neutral points. Our results indicate that, for both male and female participants, the emotional neutral point for male faces is perceptually biased to be happier than for female faces. This bias suggests that more happiness is required to perceive a male face as emotionally neutral, i.e., we are biased to perceive a male face as more negative. Interestingly, we also find that perceptual biases in perceiving female faces are correlated with current mood, such that positive state affect correlates with perceiving female faces as happier, while we find no significant correlation between negative state affect and the perception of facial emotion. Furthermore, we find reaction time biases, with slower responses for angry male faces compared to angry female faces. PMID:27733839

  3. 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.

  4. 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.

  5. Examplers based image fusion features for face recognition

    CERN Document Server

    James, Alex Pappachen

    2012-01-01

    Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on CALTECH face databases. In addition to face recognition, the method also detects the natural variability in the face images which can find application in automatic tagging of face images.

  6. Face pose tracking using the four-point algorithm

    Science.gov (United States)

    Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

    2017-06-01

    In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

  7. Traditional facial tattoos disrupt face recognition processes.

    Science.gov (United States)

    Buttle, Heather; East, Julie

    2010-01-01

    Factors that are important to successful face recognition, such as features, configuration, and pigmentation/reflectance, are all subject to change when a face has been engraved with ink markings. Here we show that the application of facial tattoos, in the form of spiral patterns (typically associated with the Maori tradition of a Moko), disrupts face recognition to a similar extent as face inversion, with recognition accuracy little better than chance performance (2AFC). These results indicate that facial tattoos can severely disrupt our ability to recognise a face that previously did not have the pattern.

  8. Anatomic considerations in the aging face.

    Science.gov (United States)

    Zoumalan, Richard A; Larrabee, Wayne F

    2011-02-01

    A thorough knowledge of the anatomy of the aging face is essential to a safe and effective operation. Over time, the face undergoes changes in skin and subcutaneous tissues evidenced by rhytides and thinning. There are also changes in the tone and character of facial muscles. Changes in fat structures in the face cause aesthetic changes that can be addressed surgically. Knowledge of the anatomy of the face and neck will aid in understanding the changes that occur with aging and will allow for a more complete strategy in rejuvenating the aging face.

  9. 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。

  10. Neural markers of opposite-sex bias in face processing

    Directory of Open Access Journals (Sweden)

    Alice Mado eProverbio

    2010-10-01

    Full Text Available Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (ORE; Caldara et al., 2004, little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women who were engaged in a secondary perceptual task (landscape detection. The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP to same-sex faces. Analysis of intra-cortical neural generators (swLORETA showed that facial processing-related (FG, BA37, BA20/21 and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24 had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

  11. Quality labeled faces in the wild (QLFW): a database for studying face recognition in real-world environments

    Science.gov (United States)

    Karam, Lina J.; Zhu, Tong

    2015-03-01

    The varying quality of face images is an important challenge that limits the effectiveness of face recognition technology when applied in real-world applications. Existing face image databases do not consider the effect of distortions that commonly occur in real-world environments. This database (QLFW) represents an initial attempt to provide a set of labeled face images spanning the wide range of quality, from no perceived impairment to strong perceived impairment for face detection and face recognition applications. Types of impairment include JPEG2000 compression, JPEG compression, additive white noise, Gaussian blur and contrast change. Subjective experiments are conducted to assess the perceived visual quality of faces under different levels and types of distortions and also to assess the human recognition performance under the considered distortions. One goal of this work is to enable automated performance evaluation of face recognition technologies in the presence of different types and levels of visual distortions. This will consequently enable the development of face recognition systems that can operate reliably on real-world visual content in the presence of real-world visual distortions. Another goal is to enable the development and assessment of visual quality metrics for face images and for face detection and recognition applications.

  12. Prosopagnosia when all faces look the same

    CERN Document Server

    Rivolta, Davide

    2014-01-01

    This book provides readers with a simplified and comprehensive account of the cognitive and neural bases of face perception in humans. Faces are ubiquitous in our environment and we rely on them during social interactions. The human face processing system allows us to extract information about the identity, gender, age, mood, race, attractiveness and approachability of other people in about a fraction of a second, just by glancing at their faces.  By introducing readers to the most relevant research on face recognition, this book seeks to answer the questions: “Why are humans so fast at recognizing faces?”, “Why are humans so efficient at recognizing faces?”, “Do faces represent a particular category for the human visual system?”, What makes face perception in humans so special?, “Can our face recognition system fail”?  This book presents the author’s findings on face perception during his research studies on both normal subjects and subjects with prosopagnosia, a neurological disorder cha...

  13. Evaluating face trustworthiness: a model based approach.

    Science.gov (United States)

    Todorov, Alexander; Baron, Sean G; Oosterhof, Nikolaas N

    2008-06-01

    Judgments of trustworthiness from faces determine basic approach/avoidance responses and approximate the valence evaluation of faces that runs across multiple person judgments. Here, based on trustworthiness judgments and using a computer model for face representation, we built a model for representing face trustworthiness (study 1). Using this model, we generated novel faces with an increased range of trustworthiness and used these faces as stimuli in a functional Magnetic Resonance Imaging study (study 2). Although participants did not engage in explicit evaluation of the faces, the amygdala response changed as a function of face trustworthiness. An area in the right amygdala showed a negative linear response-as the untrustworthiness of faces increased so did the amygdala response. Areas in the left and right putamen, the latter area extended into the anterior insula, showed a similar negative linear response. The response in the left amygdala was quadratic--strongest for faces on both extremes of the trustworthiness dimension. The medial prefrontal cortex and precuneus also showed a quadratic response, but their response was strongest to faces in the middle range of the trustworthiness dimension.

  14. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  15. Extraversion predicts individual differences in face recognition.

    Science.gov (United States)

    Li, Jingguang; Tian, Moqian; Fang, Huizhen; Xu, Miao; Li, He; Liu, Jia

    2010-07-01

    In daily life, one of the most common social tasks we perform is to recognize faces. However, the relation between face recognition ability and social activities is largely unknown. Here we ask whether individuals with better social skills are also better at recognizing faces. We found that extraverts who have better social skills correctly recognized more faces than introverts. However, this advantage was absent when extraverts were asked to recognize non-social stimuli (e.g., flowers). In particular, the underlying facet that makes extraverts better face recognizers is the gregariousness facet that measures the degree of inter-personal interaction. In addition, the link between extraversion and face recognition ability was independent of general cognitive abilities. These findings provide the first evidence that links face recognition ability to our daily activity in social communication, supporting the hypothesis that extraverts are better at decoding social information than introverts.

  16. Face Recognition using Eigenfaces and Neural Networks

    Directory of Open Access Journals (Sweden)

    Mohamed Rizon

    2006-01-01

    Full Text Available In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by using the backpropagation neural network that utilized euclidean distance for classification and recognition. The ORL database for this investigation consists of 40 people with various 400 face images had been used for the learning. The eigenfaces including implemented Jacobi’s method for eigenvalues and eigenvectors has been performed. The classification and recognition using backpropagation neural network showed impressive positive result to classify face images.

  17. Processing of emotional faces in social phobia

    Directory of Open Access Journals (Sweden)

    Nicole Kristjansen Rosenberg

    2011-02-01

    Full Text Available Previous research has found that individuals with social phobia differ from controls in their processing of emotional faces. For instance, people with social phobia show increased attention to briefly presented threatening faces. However, when exposure times are increased, the direction of this attentional bias is more unclear. Studies investigating eye movements have found both increased as well as decreased attention to threatening faces in socially anxious participants. The current study investigated eye movements to emotional faces in eight patients with social phobia and 34 controls. Three different tasks with different exposure durations were used, which allowed for an investigation of the time course of attention. At the early time interval, patients showed a complex pattern of both vigilance and avoidance of threatening faces. At the longest time interval, patients avoided the eyes of sad, disgust, and neutral faces more than controls, whereas there were no group differences for angry faces.

  18. Social Psychological Face Perception: Why Appearance Matters

    Science.gov (United States)

    Zebrowitz, Leslie A.; Montepare, Joann M.

    2009-01-01

    We form first impressions from faces despite warnings not to do so. Moreover, there is considerable agreement in our impressions, which carry significant social outcomes. Appearance matters because some facial qualities are so useful in guiding adaptive behavior that even a trace of those qualities can create an impression. Specifically, the qualities revealed by facial cues that characterize low fitness, babies, emotion, and identity are overgeneralized to people whose facial appearance resembles the unfit (anomalous face overgeneralization), babies (babyface overgeneralization), a particular emotion (emotion face overgeneralization), or a particular identity (familiar face overgeneralization). We review studies that support the overgeneralization hypotheses and recommend research that incorporates additional tenets of the ecological theory from which these hypotheses are derived: the contribution of dynamic and multi-modal stimulus information to face perception; bidirectional relationships between behavior and face perception; perceptual learning mechanisms and social goals that sensitize perceivers to particular information in faces. PMID:20107613

  19. Aging and attentional biases for emotional faces.

    Science.gov (United States)

    Mather, Mara; Carstensen, Laura L

    2003-09-01

    We examined age differences in attention to and memory for faces expressing sadness, anger, and happiness. Participants saw a pair of faces, one emotional and one neutral, and then a dot probe that appeared in the location of one of the faces. In two experiments, older adults responded faster to the dot if it was presented on the same side as a neutral face than if it was presented on the same side as a negative face. Younger adults did not exhibit this attentional bias. Interactions of age and valence were also found for memory for the faces, with older adults remembering positive better than negative faces. These findings reveal that in their initial attention, older adults avoid negative information. This attentional bias is consistent with older adults' generally better emotional well-being and their tendency to remember negative less well than positive information.

  20. Culture shapes how we look at faces.

    Directory of Open Access Journals (Sweden)

    Caroline Blais

    Full Text Available BACKGROUND: Face processing, amongst many basic visual skills, is thought to be invariant across all humans. From as early as 1965, studies of eye movements have consistently revealed a systematic triangular sequence of fixations over the eyes and the mouth, suggesting that faces elicit a universal, biologically-determined information extraction pattern. METHODOLOGY/PRINCIPAL FINDINGS: Here we monitored the eye movements of Western Caucasian and East Asian observers while they learned, recognized, and categorized by race Western Caucasian and East Asian faces. Western Caucasian observers reproduced a scattered triangular pattern of fixations for faces of both races and across tasks. Contrary to intuition, East Asian observers focused more on the central region of the face. CONCLUSIONS/SIGNIFICANCE: These results demonstrate that face processing can no longer be considered as arising from a universal series of perceptual events. The strategy employed to extract visual information from faces differs across cultures.

  1. Web-Based vs. Face-to-Face MBA Classes: A Comparative Assessment Study

    Science.gov (United States)

    Brownstein, Barry; Brownstein, Deborah; Gerlowski, Daniel A.

    2008-01-01

    The challenges of online learning include ensuring that the learning outcomes are at least as robust as in the face-to-face sections of the same course. At the University of Baltimore, both online sections and face-to-face sections of core MBA courses are offered. Once admitted to the MBA, students are free to enroll in any combination of…

  2. The Use of Computer-Mediated Communication To Enhance Subsequent Face-to-Face Discussions.

    Science.gov (United States)

    Dietz-Uhler, Beth; Bishop-Clark, Cathy

    2001-01-01

    Describes a study of undergraduate students that assessed the effects of synchronous (Internet chat) and asynchronous (Internet discussion board) computer-mediated communication on subsequent face-to-face discussions. Results showed that face-to-face discussions preceded by computer-mediated communication were perceived to be more enjoyable.…

  3. 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…

  4. Face to Face or E-Learning in Turkish EFL Context

    Science.gov (United States)

    Solak, Ekrem; Cakir, Recep

    2014-01-01

    This purpose of this study was to understand e-learners and face to face learners' views towards learning English through e-learning in vocational higher school context and to determine the role of academic achievement and gender in e-learning and face to face learning. This study was conducted at a state-run university in 2012-2013 academic year…

  5. Moodle: A Way for Blending VLE and Face-to-Face Instruction in the ELT Context?

    Science.gov (United States)

    Ilin, Gulden

    2013-01-01

    This classroom research explores the probable consequences of a blended Teaching English to Young Learners (TEYLs) course comprised of Moodle applications and face to face instruction in the English Language Teaching (ELT) context. Contrary to previous face to face only procedure, the course was divided into two segments: traditional classroom…

  6. Can Face-to-Face Mobilization Boost Student Voter Turnout? Results of a Campus Field Experiment

    Science.gov (United States)

    Hill, David; Lachelier, Paul

    2014-01-01

    American colleges and universities have an expanding role to play in nurturing political engagement as more youth attend college. Given low voter turnout among college students yet growing experimental evidence that face-to-face mobilization can boost turnout, the experiment reported in this article examined the impact of a face-to-face college…

  7. Examining the Roles of the Facilitator in Online and Face-to-Face PD Contexts

    Science.gov (United States)

    Park, Gina; Johnson, Heather; Vath, Richard; Kubitskey, Beth; Fishman, Barry

    2013-01-01

    Online teacher professional development has become an alternative to face-to-face professional development. Such a shift from face-to-face to online professional development, however, brings new challenges for professional development facilitators, whose roles are crucial in orchestrating teacher learning. This paper is motivated by the need to…

  8. "No Significant Distance" between Face-to-Face and Online Instruction: Evidence from Principles of Economics

    Science.gov (United States)

    Coates, Dennis; Humphreys, Brad, R.; Kane, John; Vachris, Michelle, A.

    2004-01-01

    This paper describes an experiment focused on measuring and explaining differences in students learning between online and face-to-face modes of instruction in college level principles of economics courses. Our results indicate that students in face-to-face sections scored better on the Test of Understanding College Economics (TUCE) than students…

  9. Why Use the Online Environment with Face-to-Face Students? Insights from Early Adopters.

    Science.gov (United States)

    Bunker, Alison; Vardi, Iris

    This study illustrates the convergence of two teaching and learning media, face-to-face and online, as reflective lecturers seek to address the limitations of a single medium. Innovative university lecturers at a large Western Australia university were interviewed about their use of online environments with face-to-face students. The interview…

  10. Recognition of Face and Emotional Facial Expressions in Autism

    Directory of Open Access Journals (Sweden)

    Muhammed Tayyib Kadak

    2013-03-01

    Full Text Available Autism is a genetically transferred neurodevelopmental disorder characterized by severe and permanent deficits in many interpersonal relation areas like communication, social interaction and emotional responsiveness. Patients with autism have deficits in face recognition, eye contact and recognition of emotional expression. Both recognition of face and expression of facial emotion carried on face processing. Structural and functional impairment in fusiform gyrus, amygdala, superior temporal sulcus and other brain regions lead to deficits in recognition of face and facial emotion. Therefore studies suggest that face processing deficits resulted in problems in areas of social interaction and emotion in autism. Studies revealed that children with autism had problems in recognition of facial expression and used mouth region more than eye region. It was also shown that autistic patients interpreted ambiguous expressions as negative emotion. In autism, deficits related in various stages of face processing like detection of gaze, face identity, recognition of emotional expression were determined, so far. Social interaction impairments in autistic spectrum disorders originated from face processing deficits during the periods of infancy, childhood and adolescence. Recognition of face and expression of facial emotion could be affected either automatically by orienting towards faces after birth, or by “learning” processes in developmental periods such as identity and emotion processing. This article aimed to review neurobiological basis of face processing and recognition of emotional facial expressions during normal development and in autism.

  11. Privileged access to awareness for faces and objects of expertise.

    Science.gov (United States)

    Stein, Timo; Reeder, Reshanne R; Peelen, Marius V

    2016-06-01

    Access to visual awareness for human faces is strongly influenced by spatial orientation: Under continuous flash suppression (CFS), upright faces break into awareness more quickly than inverted faces. This effect of inversion for faces is larger than for a wide range of other animate and inanimate objects. Here we asked whether this apparently specific sensitivity to upright faces reflects face-specific detection mechanisms or whether it reflects perceptual expertise more generally. We tested car experts who varied in their degree of car and face expertise and measured the time upright and inverted faces, cars, and chairs needed to overcome CFS and break into awareness. Results showed that greater car expertise was correlated with larger car inversion effects under CFS. A similar relation between better discrimination performance and larger CFS inversion effects was found for faces. CFS inversion effects are thus modulated by perceptual expertise for both faces and cars. These results demonstrate that inversion effects in conscious access are not unique to faces but similarly exist for other objects of expertise. More generally, we interpret these findings as suggesting that access to awareness and exemplar-level discrimination rely on partially shared perceptual mechanisms. (PsycINFO Database Record

  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. Lost in Translation: Adapting a Face-to-Face Course Into an Online Learning Experience.

    Science.gov (United States)

    Kenzig, Melissa J

    2015-09-01

    Online education has grown dramatically over the past decade. Instructors who teach face-to-face courses are being called on to adapt their courses to the online environment. Many instructors do not have sufficient training to be able to effectively move courses to an online format. This commentary discusses the growth of online learning, common challenges faced by instructors adapting courses from face-to-face to online, and best practices for translating face-to-face courses into online learning opportunities. © 2015 Society for Public Health Education.

  14. EEG power spectral measurements comparing normal and "thatcherized" faces.

    Science.gov (United States)

    Gersenowies, Jorge; Marosi, Erzsebet; Cansino, Selene; Rodriguez, Mario

    2010-08-01

    In this paper we have made a broadband analysis to detect the electroencephalogram (EEG) frequencies that change selectively during the presentation of normal and "thatcherized" faces. Referential recordings to linked ears were obtained in 21 leads in 48 right-handed healthy male volunteers. Increase of delta power (1.75-3.91 Hz) was observed, related to the detection of distortion in faces at bifrontal and left temporoparietal cortex. The other bands had no contribution, when normal and modified faces were compared. These results support our hypothesis that a change in EEG power spectral may be related to discrimination between normal and thatcherized faces.

  15. Face Synthesis (FASY) System for Determining the Characteristics of a Face Image

    CERN Document Server

    Halder, Santanu; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

    2010-01-01

    This paper aims at determining the characteristics of a face image by extracting its components. The FASY (FAce SYnthesis) System is a Face Database Retrieval and new Face generation System that is under development. One of its main features is the generation of the requested face when it is not found in the existing database, which allows a continuous growing of the database also. To generate the new face image, we need to store the face components in the database. So we have designed a new technique to extract the face components by a sophisticated method. After extraction of the facial feature points we have analyzed the components to determine their characteristics. After extraction and analysis we have stored the components along with their characteristics into the face database for later use during the face construction.

  16. Face Synthesis (FASY) System for Generation of a Face Image from Human Description

    CERN Document Server

    Halder, Santanu; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

    2010-01-01

    This paper aims at generating a new face based on the human like description using a new concept. The FASY (FAce SYnthesis) System is a Face Database Retrieval and new Face generation System that is under development. One of its main features is the generation of the requested face when it is not found in the existing database, which allows a continuous growing of the database also.

  17. Anger Superiority in Single-Face Judgements

    Directory of Open Access Journals (Sweden)

    Hiroshi Ashida

    2011-05-01

    Full Text Available We investigated “anger superiority” in single-face judgements. Angry, or threatening, faces are easier to find than smiling ones (Hansen & Hansen, 1988 but it remains controversial whether this reflects emotional effects on the basis of the whole face or rather perceptual effects on the basis of parts. We sought this question differently from most previous studies that used the visual search paradigm. We presented a picture of angry, smiling, or neutral face (extracted from ATR DB99 database that has been confirmed for emotional strength either to the left or to the right of the fixation mark, which was followed by a mask, and the participants were asked to make a forced-choice judgement of anger or smile. The results showed that neutral faces were significantly biased towards anger with upright presentation but not with inverted presentation. Angry and smiling faces were judged equally well with upright presentation, while there was notable reduction of correct responses only for angry face with inverted presentation. Difference between hemifields was not clear. The results suggest that angry faces are judged on the basis of configural processing of the whole face, while smiling faces may be judged more locally on the basis of parts.

  18. Face-to-face or Face-to-screen? Undergraduates’ opinions and test performance in classroom versus online learning

    Directory of Open Access Journals (Sweden)

    Nenagh eKemp

    2014-11-01

    Full Text Available As electronic communication becomes increasingly common, and as students juggle study, work, and family life, many universities are offering their students more flexible learning opportunities. Classes once delivered face-to-face are often replaced by online activities and discussions. However, there is little research comparing students’ experience and learning in these two modalities. The aim of this study was to compare undergraduates’ preference for, and academic performance on, class material and assessment presented online versus in traditional classrooms. Psychology students (N = 71 at an Australian university completed written exercises, a class discussion, and a written test on two academic topics. The activities for one topic were conducted face-to-face, and the other online, with topics counterbalanced across two groups. The results showed that students preferred to complete activities face-to-face rather than online, but there was no significant difference in their test performance in the two modalities. In their written responses, students expressed a strong preference for class discussions to be conducted face-to-face, reporting that they felt more engaged, and received more immediate feedback, than in online discussion. A follow-up study with a separate group confirmed that although students appreciated the convenience of completing written activities online in their own time, they also strongly preferred to discuss course content with peers in the classroom rather than online. It is concluded that online and face-to-face activities can lead to similar levels of academic performance, but that students would rather do written activities online but engage in discussion in person. Course developers could aim to structure classes so that students can benefit from both the flexibility of online learning, and the greater engagement experienced in face-to-face discussion.

  19. Dissociation between face perception and face memory in adults, but not children, with developmental prosopagnosia.

    Science.gov (United States)

    Dalrymple, Kirsten A; Garrido, Lúcia; Duchaine, Brad

    2014-10-01

    Cognitive models propose that face recognition is accomplished through a series of discrete stages, including perceptual representation of facial structure, and encoding and retrieval of facial information. This implies that impaired face recognition can result from failures of face perception, face memory, or both. Studies of acquired prosopagnosia, autism spectrum disorders, and the development of normal face recognition support the idea that face perception and face memory are distinct processes, yet this distinction has received little attention in developmental prosopagnosia (DP). To address this issue, we tested the face perception and face memory of children and adults with DP. By definition, face memory is impaired in DP, so memory deficits were present in all participants. However, we found that all children, but only half of the adults had impaired face perception. Thus, results from adults indicate that face perception and face memory are dissociable, while the results from children provide no evidence for this division. Importantly, our findings raise the possibility that DP is qualitatively different in childhood versus adulthood. We discuss theoretical explanations for this developmental pattern and conclude that longitudinal studies are necessary to better understand the developmental trajectory of face perception and face memory deficits in DP.

  20. Dissociation between face perception and face memory in adults, but not children, with developmental prosopagnosia

    Directory of Open Access Journals (Sweden)

    Kirsten A. Dalrymple

    2014-10-01

    Full Text Available Cognitive models propose that face recognition is accomplished through a series of discrete stages, including perceptual representation of facial structure, and encoding and retrieval of facial information. This implies that impaired face recognition can result from failures of face perception, face memory, or both. Studies of acquired prosopagnosia, autism spectrum disorders, and the development of normal face recognition support the idea that face perception and face memory are distinct processes, yet this distinction has received little attention in developmental prosopagnosia (DP. To address this issue, we tested the face perception and face memory of children and adults with DP. By definition, face memory is impaired in DP, so memory deficits were present in all participants. However, we found that all children, but only half of the adults had impaired face perception. Thus, results from adults indicate that face perception and face memory are dissociable, while the results from children provide no evidence for this division. Importantly, our findings raise the possibility that DP is qualitatively different in childhood versus adulthood. We discuss theoretical explanations for this developmental pattern and conclude that longitudinal studies are necessary to better understand the developmental trajectory of face perception and face memory deficits in DP.

  1. Self-face recognition in social context.

    Science.gov (United States)

    Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2012-06-01

    The concept of "social self" is often described as a representation of the self-reflected in the eyes or minds of others. Although the appearance of one's own face has substantial social significance for humans, neuroimaging studies have failed to link self-face recognition and the likely neural substrate of the social self, the medial prefrontal cortex (MPFC). We assumed that the social self is recruited during self-face recognition under a rich social context where multiple other faces are available for comparison of social values. Using functional magnetic resonance imaging (fMRI), we examined the modulation of neural responses to the faces of the self and of a close friend in a social context. We identified an enhanced response in the ventral MPFC and right occipitoparietal sulcus in the social context specifically for the self-face. Neural response in the right lateral parietal and inferior temporal cortices, previously claimed as self-face-specific, was unaffected for the self-face but unexpectedly enhanced for the friend's face in the social context. Self-face-specific activation in the pars triangularis of the inferior frontal gyrus, and self-face-specific reduction of activation in the left middle temporal gyrus and the right supramarginal gyrus, replicating a previous finding, were not subject to such modulation. Our results thus demonstrated the recruitment of a social self during self-face recognition in the social context. At least three brain networks for self-face-specific activation may be dissociated by different patterns of response-modulation in the social context, suggesting multiple dynamic self-other representations in the human brain.

  2. Own-race and own-age biases facilitate visual awareness of faces under interocular suppression

    Directory of Open Access Journals (Sweden)

    Timo eStein

    2014-08-01

    Full Text Available 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. Here, we qualify this notion by showing that face detection mechanisms are also sensitive to face shape and facial surface reflectance properties. We used continuous flash suppression (CFS to render faces invisible at the beginning of a trial and measured the time upright and inverted faces needed to break into awareness. Young Caucasian adult observers were presented with faces from their own race or from another race (race experiment and with faces from their own age group or from another age group (age experiment. Faces matching the observers’ own race and age group were detected more quickly. Moreover, the advantage of upright over inverted faces in overcoming CFS, i.e. the face inversion effect, was larger for own-race and own-age faces. These results demonstrate that differences in face shape and surface reflectance influence access to awareness and configural face processing at the initial detection stage. Although we did not collect data from observers of another race or age group, these findings are a first indication that face detection mechanisms are shaped by visual experience with faces from one’s own social group. Such experience-based fine-tuning of face detection mechanisms may equip in-group faces with a competitive advantage for access to conscious awareness.

  3. 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.

  4. A Sparse-Feature-Based Face Detector

    Institute of Scientific and Technical Information of China (English)

    LUXiaofeng; ZHENGNanning; ZHENGSongfeng

    2003-01-01

    Local features and global features are two kinds of important statistical features used to distinguish faces from nonfaces. They are both special cases of sparse features. A final classifier can be considered as a combination of a set of selected weak classiflers, and each weak classifier uses a sparse feature to classify samples. Motivated by this thought, we construct an over complete set of weak classifiers using LPSVM (Linear proximal support vector machine) algorithm, and then we select part of them using AdaBoost algorithm and combine the selected weak classifiers to form a strong classifier. And duringthe course of feature extraction and selection, our method can minimize the classification error directly, whereas most previous works cannot do this. The main difference from other methods is that the local features are learned from the training set instead of being arbitrarily defined. We applied our method to face detection; the test result shows that this method performs well.

  5. Fetal diprosopus (Double face: A case report

    Directory of Open Access Journals (Sweden)

    Onankpa BO, Ukwu E, Singh S, Adoke AU, Tahir A

    2014-04-01

    Full Text Available Diprosopus is an extremely rare form of congenital anomaly that results in partial or total duplication of the face. Most cases of diprosopus are delivered as stillborn or die few moments after delivery. The aim of this report is to alert clinicians that the antenatal finding of polyhydramnious may be strongly associated with fetal diprosopus, this routine high resolution anomaly scans should be recommended to help detect such anomaly early in pregnancy. We report a case of a female neonate with partial duplication of the face (diprosopus delivered by a 39 year old booked multipara. Baby’s condition deteriorated within 24hrs with worsening respiratory distress and died on the 2nd day of life.

  6. Face Recognition using Segmental Euclidean Distance

    Directory of Open Access Journals (Sweden)

    Farrukh Sayeed

    2011-09-01

    Full Text Available In this paper an attempt has been made to detect the face using the combination of integral image along with the cascade structured classifier which is built using Adaboost learning algorithm. The detected faces are then passed through a filtering process for discarding the non face regions. They are individually split up into five segments consisting of forehead, eyes, nose, mouth and chin. Each segment is considered as a separate image and Eigenface also called principal component analysis (PCA features of each segment is computed. The faces having a slight pose are also aligned for proper segmentation. The test image is also segmented similarly and its PCA features are found. The segmental Euclidean distance classifier is used for matching the test image with the stored one. The success rate comes out to be 88 per cent on the CG(full database created from the databases of California Institute and Georgia Institute. However the performance of this approach on ORL(full database with the same features is only 70 per cent. For the sake of comparison, DCT(full and fuzzy features are tried on CG and ORL databases but using a well known classifier, support vector machine (SVM. Results of recognition rate with DCT features on SVM classifier are increased by 3 per cent over those due to PCA features and Euclidean distance classifier on the CG database. The results of recognition are improved to 96 per cent with fuzzy features on ORL database with SVM.Defence Science Journal, 2011, 61(5, pp.431-442, DOI:http://dx.doi.org/10.14429/dsj.61.1178

  7. 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.

  8. CHALLENGES FACING THE ESP PRACTITIONER

    Directory of Open Access Journals (Sweden)

    SIMION MINODORA OTILIA

    2015-12-01

    Full Text Available The ESP teacher has to face certain challenges in his profession: One of the biggest challenges of the ESP teacher is the fact that he/she lacks the necessary knowledge of the subject to teach Business English, for instance, some researchers believing that such courses should be taught by subject teachers. The task of teaching ESP by ESL teachers is not an easy one. Dudley- Evans and St. John pointed out its complexity, identifying five key roles of the ESP practitioner: teacher, course designer and materials provider, collaborator, researcher and evaluator and this is probably the biggest challenge of the profession. The ESP practitioner has also to be aware of the fact that using a foreign language for workplace or study purposes requires not only linguistic proficiency and knowledge but also knowledge of work –related and disciplinary concepts.Last but not least, another challenge for the ESP practitioner is the use of technology in class, a valuable tool for helping with traditional forms of teaching and for creating new forms of communicating.Thus, the ESP practitioner has many things in common with the teacher of general English: he has to be familiar with linguistic development and teaching theories ,he has to be aware of contemporary ideas related to his position and role and he has to become familiar with the new technologies which can be used to improve his methodology.However,his role is more complex than that of a General English teacher.

  9. Digital 'faces' of synthetic biology.

    Science.gov (United States)

    Friedrich, Kathrin

    2013-06-01

    In silicio design plays a fundamental role in the endeavour to synthesise biological systems. In particular, computer-aided design software enables users to manage the complexity of biological entities that is connected to their construction and reconfiguration. The software's graphical user interface bridges the gap between the machine-readable data on the algorithmic subface of the computer and its human-amenable surface represented by standardised diagrammatic elements. Notations like the Systems Biology Graphical Notation (SBGN), together with interactive operations such as drag & drop, allow the user to visually design and simulate synthetic systems as 'bio-algorithmic signs'. Finally, the digital programming process should be extended to the wet lab to manufacture the designed synthetic biological systems. By exploring the different 'faces' of synthetic biology, I argue that in particular computer-aided design (CAD) is pushing the idea to automatically produce de novo objects. Multifaceted software processes serve mutually aesthetic, epistemic and performative purposes by simultaneously black-boxing and bridging different data sources, experimental operations and community-wide standards. So far, synthetic biology is mainly a product of digital media technologies that structurally mimic the epistemological challenge to take both qualitative as well as quantitative aspects of biological systems into account in order to understand and produce new and functional entities.

  10. Face classification using electronic synapses

    Science.gov (United States)

    Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

    2017-05-01

    Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

  11. The new face of innovation

    Science.gov (United States)

    Bloch, Erich

    2000-05-01

    The rapid changes in technology, the changes in the national and global economy and the emergence of many new nations that acquire an increasing competence to innovate is presenting us with new issues and opportunities. In particular, it affects the innovation system of the country, namely the scientific and technological infrastructure, the workforce and the policy environment in which government, industry, and academia operates. From a sequential or serial model we are moving or have moved to a dynamic, interactive one that encompasses more stakeholders in a realtime way. Of late, the work of the Council on Competitiveness has focused on the capacity for innovation as a pre-requisite for national competitiveness. This talk will discuss the results from its report "Going Global: The New Shape of American Innovation" and its "Findings from the Innovation Index" and assess the forces that affect the future. The main conclusion will be that the changes we have and will be facing are irreversible and require the active and positive participation of the technical professional and technical institutions. It also requires new relationships between the main participants of the innovation system.

  12. South Africa faces coke shortage

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-05-01

    Iscor Vanderbijlpark in South Africa may need to import substantial tonnages of coking coal as a result of increasing quality demands on coke at Vanderbiljpark (to support the recently installed PCI process) as well as the Newcastle works. Availability of coke is not only a problem for the South African steel industry but is a global problem as the production of coke in Western countries has declined over the past three years. A massive expansion in coke-making capacity is happening in China but the Chinese beehive ovens create serious pollution problems. A world shortage of coke of 30 million t/y by 2005 is estimated, rising to over 60 million t/y by 2010 of no new capacity is created. Steelmakers have succeeded in reducing their consumption of coke, by pulverised coal injection by better distribution of components in the furnace shaft and by decline in use of the blast furnace-basic oxygen furnace route, but the industry is still facing serious shortages of coke.

  13. Real-time, face recognition technology

    Energy Technology Data Exchange (ETDEWEB)

    Brady, S.

    1995-11-01

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory recently developed the real-time, face recognition technology KEN. KEN uses novel imaging devices such as silicon retinas developed at Caltech or off-the-shelf CCD cameras to acquire images of a face and to compare them to a database of known faces in a robust fashion. The KEN-Online project makes that recognition technology accessible through the World Wide Web (WWW), an internet service that has recently seen explosive growth. A WWW client can submit face images, add them to the database of known faces and submit other pictures that the system tries to recognize. KEN-Online serves to evaluate the recognition technology and grow a large face database. KEN-Online includes the use of public domain tools such as mSQL for its name-database and perl scripts to assist the uploading of images.

  14. 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.

  15. Robust Face Recognition through Local Graph Matching

    Directory of Open Access Journals (Sweden)

    Ehsan Fazl-Ersi

    2007-09-01

    Full Text Available A novel face recognition method is proposed, in which face images are represented by a set of local labeled graphs, each containing information about the appearance and geometry of a 3-tuple of face feature points, extracted using Local Feature Analysis (LFA technique. Our method automatically learns a model set and builds a graph space for each individual. A two-stage method for optimal matching between the graphs extracted from a probe image and the trained model graphs is proposed. The recognition of each probe face image is performed by assigning it to the trained individual with the maximum number of references. Our approach achieves perfect result on the ORL face set and an accuracy rate of 98.4% on the FERET face set, which shows the superiority of our method over all considered state-of-the-art methods. I

  16. Cyberbullying: the new face of workplace bullying?

    Science.gov (United States)

    Privitera, Carmel; Campbell, Marilyn Anne

    2009-08-01

    While the subject of cyberbullying of children and adolescents has begun to be addressed, less attention and research have focused on cyberbullying in the workplace. Male-dominated workplaces such as manufacturing settings are found to have an increased risk of workplace bullying, but the prevalence of cyberbullying in this sector is not known. This exploratory study investigated the prevalence and methods of face-to-face bullying and cyberbullying of males at work. One hundred three surveys (a modified version of the revised Negative Acts Questionnaire [NAQ-R]) were returned from randomly selected members of the Australian Manufacturing Workers' Union (AMWU). The results showed that 34% of respondents were bullied face-to-face, and 10.7% were cyberbullied. All victims of cyberbullying also experienced face-to-face bullying. The implications for organizations' "duty of care" in regard to this new form of bullying are indicated.

  17. Human face processing is tuned to sexual age preferences.

    Science.gov (United States)

    Ponseti, J; Granert, O; van Eimeren, T; Jansen, O; Wolff, S; Beier, K; Deuschl, G; Bosinski, H; Siebner, H

    2014-05-01

    Human faces can motivate nurturing behaviour or sexual behaviour when adults see a child or an adult face, respectively. This suggests that face processing is tuned to detecting age cues of sexual maturity to stimulate the appropriate reproductive behaviour: either caretaking or mating. In paedophilia, sexual attraction is directed to sexually immature children. Therefore, we hypothesized that brain networks that normally are tuned to mature faces of the preferred gender show an abnormal tuning to sexual immature faces in paedophilia. Here, we use functional magnetic resonance imaging (fMRI) to test directly for the existence of a network which is tuned to face cues of sexual maturity. During fMRI, participants sexually attracted to either adults or children were exposed to various face images. In individuals attracted to adults, adult faces activated several brain regions significantly more than child faces. These brain regions comprised areas known to be implicated in face processing, and sexual processing, including occipital areas, the ventrolateral prefrontal cortex and, subcortically, the putamen and nucleus caudatus. The same regions were activated in paedophiles, but with a reversed preferential response pattern.

  18. Contextual modulation of biases in face recognition.

    Directory of Open Access Journals (Sweden)

    Fatima Maria Felisberti

    Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.

  19. A survey of real face modeling methods

    Science.gov (United States)

    Liu, Xiaoyue; Dai, Yugang; He, Xiangzhen; Wan, Fucheng

    2017-09-01

    The face model has always been a research challenge in computer graphics, which involves the coordination of multiple organs in faces. This article explained two kinds of face modeling method which is based on the data driven and based on parameter control, analyzed its content and background, summarized their advantages and disadvantages, and concluded muscle model which is based on the anatomy of the principle has higher veracity and easy to drive.

  20. Face Recognition in Real-world Images

    OpenAIRE

    Fontaine, Xavier; Achanta, Radhakrishna; Süsstrunk, Sabine

    2017-01-01

    Face recognition systems are designed to handle well-aligned images captured under controlled situations. However real-world images present varying orientations, expressions, and illumination conditions. Traditional face recognition algorithms perform poorly on such images. In this paper we present a method for face recognition adapted to real-world conditions that can be trained using very few training examples and is computationally efficient. Our method consists of performing a novel align...

  1. Personality judgments from everyday images of faces

    OpenAIRE

    Clare AM Sutherland; Rowley, Lauren E.; Amoaku, Unity T.; Ella eDaguzan; Kate A Kidd-Rossiter; Ugne eMaceviciute; Young, Andrew W.

    2015-01-01

    People readily make personality attributions to images of strangers' faces. Here we investigated the basis of these personality attributions as made to everyday, naturalistic face images. In a first study, we used 1000 highly varying “ambient image” face photographs to test the correspondence between personality judgments of the Big Five and dimensions known to underlie a range of facial first impressions: approachability, dominance, and youthful-attractiveness. Interestingly, the facial Big ...

  2. Personality judgments from everyday images of faces

    OpenAIRE

    Clare AM Sutherland; Lauren E Rowley; Unity T Amoaku; Ella eDaguzan; Kate A Kidd-Rossiter; Ugne eMaceviciute; Andrew W Young

    2015-01-01

    People readily make personality attributions to images of strangers' faces. Here we investigated the basis of these personality attributions as made to everyday, naturalistic face images. In a first study, we used 1000 highly varying “ambient image” face photographs to test the correspondence between personality judgments of the Big Five and dimensions known to underlie a range of facial first impressions: approachability, dominance, and youthful-attractiveness. Interestingly, the facial Big ...

  3. DWT BASED HMM FOR FACE RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A novel Discrete Wavelet Transform (DWT) based Hidden Markov Module (HMM) for face recognition is presented in this letter. To improve the accuracy of HMM based face recognition algorithm, DWT is used to replace Discrete Cosine Transform (DCT) for observation sequence extraction. Extensive experiments are conducted on two public databases and the results show that the proposed method can improve the accuracy significantly, especially when the face database is large and only few training images are available.

  4. Neural Correlate of the Thatcher Face Illusion in a Monkey Face-Selective Patch.

    Science.gov (United States)

    Taubert, Jessica; Van Belle, Goedele; Vanduffel, Wim; Rossion, Bruno; Vogels, Rufin

    2015-07-01

    Compelling evidence that our sensitivity to facial structure is conserved across the primate order comes from studies of the "Thatcher face illusion": humans and monkeys notice changes in the orientation of facial features (e.g., the eyes) only when faces are upright, not when faces are upside down. Although it is presumed that face perception in primates depends on face-selective neurons in the inferior temporal (IT) cortex, it is not known whether these neurons respond differentially to upright faces with inverted features. Using microelectrodes guided by functional MRI mapping, we recorded cell responses in three regions of monkey IT cortex. We report an interaction in the middle lateral face patch (ML) between the global orientation of a face and the local orientation of its eyes, a response profile consistent with the perception of the Thatcher illusion. This increased sensitivity to eye orientation in upright faces resisted changes in screen location and was not found among face-selective neurons in other areas of IT cortex, including neurons in another face-selective region, the anterior lateral face patch. We conclude that the Thatcher face illusion is correlated with a pattern of activity in the ML that encodes faces according to a flexible holistic template.

  5. Nation, Face, and Identity: An Initial Investigation of National Face in East Asia

    Science.gov (United States)

    Chen, Rong; Hwang, Kwang-Kuo

    2016-01-01

    This research investigates a key concept in East Asia, face, and represents the first attempt to empirically examine the concept of face at the national level. Controlling for the level of national identification, Study 1 employed the scenario experiment method among samples of native Chinese and Taiwanese populations and revealed that national face exhibits patterns reverse of personal face. Using the experimental method, Study 2 replicated the findings of Study 1 and provided support for the different mechanisms underneath national face and personal face. Study 3 replicated the findings of Study 2 and additionally showed that national face exerts a significant inhibitory effect on face process. Findings are discussed in terms of possible implications for intergroup and international relations. Expanding on extant scholarship on face and across three studies with different experimental paradigms, this research turns our attention from face at the personal level to face at the national level by introducing the construct of national face and examining its manifestations in East Asia. The results advance our understanding of the psychological mechanism driving face concern in East Asia. They make a strong and unique case for the psychological existence of national face as an empirically distinct construct and an important psychological resource for East Asians. PMID:27774081

  6. The fusiform face area is engaged in holistic, not parts-based, representation of faces.

    Directory of Open Access Journals (Sweden)

    Jiedong Zhang

    Full Text Available Numerous studies with functional magnetic resonance imaging have shown that the fusiform face area (FFA in the human brain plays a key role in face perception. Recent studies have found that both the featural information of faces (e.g., eyes, nose, and mouth and the configural information of faces (i.e., spatial relation among features are encoded in the FFA. However, little is known about whether the featural information is encoded independent of or combined with the configural information in the FFA. Here we used multi-voxel pattern analysis to examine holistic representation of faces in the FFA by correlating spatial patterns of activation with behavioral performance in discriminating face parts with face configurations either present or absent. Behaviorally, the absence of face configurations (versus presence impaired discrimination of face parts, suggesting a holistic representation in the brain. Neurally, spatial patterns of activation in the FFA were more similar among correct than incorrect trials only when face parts were presented in a veridical face configuration. In contrast, spatial patterns of activation in the occipital face area, as well as the object-selective lateral occipital complex, were more similar among correct than incorrect trials regardless of the presence of veridical face configurations. This finding suggests that in the FFA faces are represented not on the basis of individual parts but in terms of the whole that emerges from the parts.

  7. 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

  8. Face and object cognition across adult age.

    Science.gov (United States)

    Hildebrandt, Andrea; Wilhelm, Oliver; Herzmann, Grit; Sommer, Werner

    2013-03-01

    We investigated the specificity of face compared with object cognition from an individual differences and aging perspective by determining the amount of overlap between these abilities at the level of latent constructs across age. Confirmatory factor analytic models tested the specificity of speed and accuracy measures for face and object cognition (N = 448; 18 to 88 years). Accuracy measures were distinguishable and slightly dedifferentiated across age, which was not due to loss of visual acuity and contrast sensitivity. There was no face specificity for speed measures. These results support the specificity of face cognition from differential and developmental perspective only for performance accuracy.

  9. Age Dependent Face Recognition using Eigenface

    Directory of Open Access Journals (Sweden)

    Hlaing Htake Khaung Tin

    2013-10-01

    Full Text Available Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human computer interaction and multimedia communication. In this paper proposes an Eigen based age estimation algorithm for estimate an image from the database. Eigenface has proven to be a useful and robust cue for age prediction, age simulation, face recognition, localization and tracking. The scheme is based on an information theory approach that decomposes face images into a small set of characteristic feature images called eigenfaces, which may be thought of as the principal components of the initial training set of face images. The eigenface approach used in this scheme has advantages over other face recognition methods in its speed, simplicity, learning capability and robustness to small changes in the face image.

  10. Face imagery is based on featural representations.

    Science.gov (United States)

    Lobmaier, Janek S; Mast, Fred W

    2008-01-01

    The effect of imagery on featural and configural face processing was investigated using blurred and scrambled faces. By means of blurring, featural information is reduced; by scrambling a face into its constituent parts configural information is lost. Twenty-four participants learned ten faces together with the sound of a name. In following matching-to-sample tasks participants had to decide whether an auditory presented name belonged to a visually presented scrambled or blurred face in two experimental conditions. In the imagery condition, the name was presented prior to the visual stimulus and participants were required to imagine the corresponding face as clearly and vividly as possible. In the perception condition name and test face were presented simultaneously, thus no facilitation via mental imagery was possible. Analyses of the hit values showed that in the imagery condition scrambled faces were recognized significantly better than blurred faces whereas there was no such effect for the perception condition. The results suggest that mental imagery activates featural representations more than configural representations.

  11. 3D face modeling, analysis and recognition

    CERN Document Server

    Daoudi, Mohamed; Veltkamp, Remco

    2013-01-01

    3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application s

  12. Face hallucination using orthogonal canonical correlation analysis

    Science.gov (United States)

    Zhou, Huiling; Lam, Kin-Man

    2016-05-01

    A two-step face-hallucination framework is proposed to reconstruct a high-resolution (HR) version of a face from an input low-resolution (LR) face, based on learning from LR-HR example face pairs using orthogonal canonical correlation analysis (orthogonal CCA) and linear mapping. In the proposed algorithm, face images are first represented using principal component analysis (PCA). Canonical correlation analysis (CCA) with the orthogonality property is then employed, to maximize the correlation between the PCA coefficients of the LR and the HR face pairs to improve the hallucination performance. The original CCA does not own the orthogonality property, which is crucial for information reconstruction. We propose using orthogonal CCA, which is proven by experiments to achieve a better performance in terms of global face reconstruction. In addition, in the residual-compensation process, a linear-mapping method is proposed to include both the inter- and intrainformation about manifolds of different resolutions. Compared with other state-of-the-art approaches, the proposed framework can achieve a comparable, or even better, performance in terms of global face reconstruction and the visual quality of face hallucination. Experiments on images with various parameter settings and blurring distortions show that the proposed approach is robust and has great potential for real-world applications.

  13. Face Recognition Using Kernel Discriminant Analysis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Linear Discrimiant Analysis (LDA) has demonstrated their success in face recognition. But LDA is difficult to handle the high nonlinear problems, such as changes of large viewpoint and illumination in face recognition. In order to overcome these problems, we investigate Kernel Discriminant Analysis (KDA) for face recognition. This approach adopts the kernel functions to replace the dot products of nonlinear mapping in the high dimensional feature space, and then the nonlinear problem can be solved in the input space conveniently without explicit mapping. Two face databases are used to test KDA approach. The results show that our approach outperforms the conventional PCA(Eigenface) and LDA(Fisherface) approaches.

  14. The challenges facing sustainable and adaptive groundwater ...

    African Journals Online (AJOL)

    The challenges facing sustainable and adaptive groundwater management ... provide the capacity to assure effective and sustainable resource regulation and allocation. ... of alternative strategies needed to achieve sustainable management.

  15. The own-age face recognition bias is task dependent.

    Science.gov (United States)

    Proietti, Valentina; Macchi Cassia, Viola; Mondloch, Catherine J

    2015-08-01

    The own-age bias (OAB) in face recognition (more accurate recognition of own-age than other-age faces) is robust among young adults but not older adults. We investigated the OAB under two different task conditions. In Experiment 1 young and older adults (who reported more recent experience with own than other-age faces) completed a match-to-sample task with young and older adult faces; only young adults showed an OAB. In Experiment 2 young and older adults completed an identity detection task in which we manipulated the identity strength of target and distracter identities by morphing each face with an average face in 20% steps. Accuracy increased with identity strength and facial age influenced older adults' (but not younger adults') strategy, but there was no evidence of an OAB. Collectively, these results suggest that the OAB depends on task demands and may be absent when searching for one identity.

  16. Face Identification by SIFT-based Complete Graph Topology

    CERN Document Server

    Kisku, Dakshina Ranjan; Grosso, Enrico; Tistarelli, Massimo

    2010-01-01

    This paper presents a new face identification system based on Graph Matching Technique on SIFT features extracted from face images. Although SIFT features have been successfully used for general object detection and recognition, only recently they were applied to face recognition. This paper further investigates the performance of identification techniques based on Graph matching topology drawn on SIFT features which are invariant to rotation, scaling and translation. Face projections on images, represented by a graph, can be matched onto new images by maximizing a similarity function taking into account spatial distortions and the similarities of the local features. Two graph based matching techniques have been investigated to deal with false pair assignment and reducing the number of features to find the optimal feature set between database and query face SIFT features. The experimental results, performed on the BANCA database, demonstrate the effectiveness of the proposed system for automatic face identifi...

  17. PARTIAL MATCHING FACE RECOGNITION METHOD FOR REHABILITATION NURSING ROBOTS BEDS

    Directory of Open Access Journals (Sweden)

    Dongmei LIANG

    2015-06-01

    Full Text Available In order to establish face recognition system in rehabilitation nursing robots beds and achieve real-time monitor the patient on the bed. We propose a face recognition method based on partial matching Hu moments which apply for rehabilitation nursing robots beds. Firstly we using Haar classifier to detect human faces automatically in dynamic video frames. Secondly we using Otsu threshold method to extract facial features (eyebrows, eyes, mouth in the face image and its Hu moments. Finally, we using Hu moment feature set to achieve the automatic face recognition. Experimental results show that this method can efficiently identify face in a dynamic video and it has high practical value (the accuracy rate is 91% and the average recognition time is 4.3s.

  18. FACE RECOGNITION USING FEATURE EXTRACTION AND NEURO-FUZZY TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Ritesh Vyas

    2012-09-01

    Full Text Available Face is a primary focus of attention in social intercourse, playing a major role in conveying identity and emotion. The human ability to recognize faces is remarkable. People can recognize thousands of faces learned throughout their lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses, beards or changes in hair style. In this work, a system is designed to recognize human faces depending on their facial features. Also to reveal the outline of the face, eyes and nose, edge detection technique has been used. Facial features are extracted in the form of distance between important feature points. After normalization, these feature vectors are learned by artificial neural network and used to recognize facial image.

  19. Interpersonal similarity between body movements in face-to-face communication in daily life.

    Science.gov (United States)

    Higo, Naoki; Ogawa, Ken-ichiro; Minemura, Juichi; Xu, Bujie; Nozawa, Takayuki; Ogata, Taiki; Ara, Koji; Yano, Kazuo; Miyake, Yoshihiro

    2014-01-01

    Individuals are embedded in social networks in which they communicate with others in their daily lives. Because smooth face-to-face communication is the key to maintaining these networks, measuring the smoothness of such communication is an important issue. One indicator of smoothness is the similarity of the body movements of the two individuals concerned. A typical example noted in experimental environments is the interpersonal synchronization of body movements such as nods and gestures during smooth face-to-face communication. It should therefore be possible to estimate quantitatively the smoothness of face-to-face communication in social networks through measurement of the synchronization of body movements. However, this is difficult because social networks, which differ from disciplined experimental environments, are open environments for the face-to-face communication between two individuals. In such open environments, their body movements become complicated by various external factors and may follow unstable and nonuniform patterns. Nevertheless, we consider there to be some interaction during face-to-face communication that leads to the interpersonal synchronization of body movements, which can be seen through the interpersonal similarity of body movements. The present study aims to clarify such interaction in terms of body movements during daily face-to-face communication in real organizations of more than 100 people. We analyzed data on the frequency of body movement for each individual during face-to-face communication, as measured by a wearable sensor, and evaluated the degree of interpersonal similarity of body movements between two individuals as their frequency difference. Furthermore, we generated uncorrelated data by resampling the data gathered and compared these two data sets statistically to distinguish the effects of actual face-to-face communication from those of the activities accompanying the communication. Our results confirm an

  20. 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.

  1. Facing the challenge of multimorbidity

    Directory of Open Access Journals (Sweden)

    Boris Azaïs

    2016-02-01

    Full Text Available Abstract Multimorbidity is a major public health challenge that is rising up the political and health agenda at an accelerated rate. Although the prevalence of multimorbidity increases with age, more than half of the population with multimorbidity are under the age of 65 years [1], with social deprivation a key determinant of multimorbidity in young and middle-aged adults [2,3]. From an individual’s perspective, multimorbidity reduces life expectancy [4–6], decreases physical functioning and quality of life [7], and increases the risk of depression and other mental health disorders [3]. From a healthcare provider’s perspective, multimorbidity is associated with increased health service use, a high risk of emergency and other hospital admissions, high rates of polypharmacy, and spiralling costs [8]. Current health systems, which are typically built around a single-disease framework, are poorly adapted to cope with patients with multimorbidity, who typically experience fragmented healthcare services, leading to potentially inefficient and ineffective care. It is increasingly clear that we need to change our perspective on multimorbidity in order to address it as a specific condition that requires tailored solutions and approaches. The urgent need to tackle multimorbidity in a more strategic, holistic, and cost-effective manner was evident at the 18th European Health Forum Gastein, a leading annual health policy event in the European Union (EU, held in the autumn of 2015. This Forum attracted policymakers, clinicians, health service managers, patients, and a broad range of other stakeholders, all of whom were invited to attend a session entitled “Facing the Challenge of Multimorbidity”. Journal of Comorbidity 2016;6(1:1–3

  2. Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition

    Directory of Open Access Journals (Sweden)

    Rong Wang

    2015-01-01

    Full Text Available In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

  3. Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

    Science.gov (United States)

    Wang, Rong

    2015-01-01

    In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

  4. Covert face priming reveals a 'true face effect' in a case of congenital prosopagnosia.

    Science.gov (United States)

    Striemer, Christopher; Gingerich, Trevor; Striemer, Danielle; Dixon, Mike

    2009-12-01

    Previous research indicates that individuals with congenital prosopagnosia (CP) fail to demonstrate significant priming from faces to related names in covert recognition tasks. The interpretation has been that CP precludes the ability to acquire face representations. In the current study we replicated this important finding. In addition, we also demonstrated significant 'true face effect' in a CP patient, where face primes that matched the probe names facilitated reaction times compared to unrelated face primes. These data suggest that some individuals with CP may possess degraded face representations that facilitate the priming of a person's identity, but not semantic associates.

  5. Perceptual face processing in developmental prosopagnosia is not sensitive to the canonical location of face parts.

    Science.gov (United States)

    Towler, John; Parketny, Joanna; Eimer, Martin

    2016-01-01

    Individuals with developmental prosopagnosia (DP) are strongly impaired in recognizing faces, but it is controversial whether this deficit is linked to atypical visual-perceptual face processing mechanisms. Previous behavioural studies have suggested that face perception in DP might be less sensitive to the canonical spatial configuration of face parts in upright faces. To test this prediction, we recorded event-related brain potentials (ERPs) to intact upright faces and to faces with spatially scrambled parts (eyes, nose, and mouth) in a group of ten participants with DP and a group of ten age-matched control participants with normal face recognition abilities. The face-sensitive N170 component and the vertex positive potential (VPP) were both enhanced and delayed for scrambled as compared to intact faces in the control group. In contrast, N170 and VPP amplitude enhancements to scrambled faces were absent in the DP group. For control participants, the N170 to scrambled faces was also sensitive to feature locations, with larger and delayed N170 components contralateral to the side where all features appeared in a non-canonical position. No such differences were present in the DP group. These findings suggest that spatial templates of the prototypical feature locations within an upright face are selectively impaired in DP.

  6. 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。

  7. The two Faces of Equipartition

    Science.gov (United States)

    Sanchez-Sesma, F. J.; Perton, M.; Rodriguez-Castellanos, A.; Campillo, M.; Weaver, R. L.; Rodriguez, M.; Prieto, G.; Luzon, F.; McGarr, A.

    2008-12-01

    relationship of average autocorrelations with the imaginary part of Green function at the source. Preliminary results are displayed in data sets from Chilpancingo, Mexico, and the Tautona Gold Mine, South Africa, that strongly suggest that equipartition, that guarantees the diffuse nature of seismic fields, has more than one face. Acknowledgements. Partial supports from DGAPA-UNAM, Project IN114706, Mexico; from Proyect MCyT CGL2005-05500-C02/BTE, Spain; from project DyETI of INSU-CNRS, France, and from the Instituto Mexicano del Petróleo are greatly appreciated.

  8. Efficient Facial Expression and Face Recognition using Ranking Method

    Directory of Open Access Journals (Sweden)

    Murali Krishna kanala

    2015-06-01

    Full Text Available Expression detection is useful as a non-invasive method of lie detection and behaviour prediction. However, these facial expressions may be difficult to detect to the untrained eye. In this paper we implements facial expression recognition techniques using Ranking Method. The human face plays an important role in our social interaction, conveying people's identity. Using human face as a key to security, the biometrics face recognition technology has received significant attention in the past several years. Experiments are performed using standard database like surprise, sad and happiness. The universally accepted three principal emotions to be recognized are: surprise, sad and happiness along with neutral.

  9. Biased allocation of faces to social categories

    NARCIS (Netherlands)

    Dotsch, R.; Wigboldus, D.H.J.; Knippenberg, A.F.M. van

    2011-01-01

    Three studies show that social categorization is biased at the level of category allocation. In all studies, participants categorized faces. In Studies 1 and 2, participants overallocated faces with criminal features-a stereotypical negative trait-to the stigmatized Moroccan category, especially if

  10. On the face support of microtunnelling TBMs

    NARCIS (Netherlands)

    Broere, W.

    2014-01-01

    Face stability of microtunnelling TBMs is an important aspect for a safe and controlled project execution. Lack of proper face support can lead to sudden collapse with resulting large settlements. Guidelines for minimal and maximal support pressures in most codes do not take the infiltration of bent

  11. Criteria for face support of microtunneling TBMs

    NARCIS (Netherlands)

    Broere, W.

    2013-01-01

    Face stability of microtunnelling TBMs is an important aspect for a safe and controlled project execution. Lack of proper face support can lead to sudden collapse with resulting large settlements. Guidelines for minimal and maximal support pressures in most codes do not take the infiltration of bent

  12. Tunnel Face Stability & New CPT Applications

    NARCIS (Netherlands)

    Broere, W.

    2001-01-01

    Nearly all tunnels bored in soft soils have encountered problems with the stability of the tunnel face. In several cases these problems led to an extended stand-still of the boring process. A better understanding of the face stability, and of the soil conditions around the tunnel boring machine, can

  13. Are reading and face processing related?

    DEFF Research Database (Denmark)

    Starrfelt, Randi; Klargaard, Solja K.; Petersen, Anders

    . In this light, investigating face processing in dyslexia, and reading in prosopagnosia becomes interesting: Do deficits in the two domains dissociate? We present data from 11 people with developmental prosopagnosia, which is a disorder of face processing in people with no known brain injury, and in the context...

  14. Are reading and face processing related?

    DEFF Research Database (Denmark)

    Starrfelt, Randi; Klargaard, Solja; Petersen, Anders

    2015-01-01

    . In this light, investigating face processing in dyslexia, and reading in prosopagnosia becomes interesting: Do deficits in the two domains dissociate? Developmental prosopagnosia (DP) is a disorder of face processing in the absence of brain injury, and in the context of normal intelligence and general cognitive...

  15. Robust video foreground segmentation and face recognition

    Institute of Scientific and Technical Information of China (English)

    GUAN Ye-peng

    2009-01-01

    Face recognition provides a natural visual interface for human computer interaction (HCI) applications.The process of face recognition,however,is inhibited by variations in the appearance of face images caused by changes in lighting,expression,viewpoint,aging and introduction of occlusion.Although various algorithms have been presented for face recognition,face recognition is still a very challenging topic.A novel approach of real time face recognition for HCI is proposed in the paper.In view of the limits of the popular approaches to foreground segmentation,wavelet multi-scale transform based background subtraction is developed to extract foreground objects.The optimal selection of the threshold is automatically determined,which does not require any complex supervised training or manual experimental calibration.A robust real time face recognition algorithm is presented,which combines the projection matrixes without iteration and kernel Fisher discriminant analysis (KFDA) to overcome some difficulties existing in the real face recognition.Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments.The proposed algorithm can also be applied to the video image sequences of natural HCI.

  16. Perception of faces with and without spectacles.

    Science.gov (United States)

    McKelvie, S J

    1997-04-01

    For 20 faces, 85 subjects selected either a distinctive feature or a distinctive trait. For faces with spectacles, the eyes were judged to be most prominent, and the people were judged to be dull and intelligent. Results are discussed in terms of the physical attractiveness stereotype.

  17. Face Alignment Using Boosting and Evolutionary Search

    NARCIS (Netherlands)

    Zhang, Hua; Liu, Duanduan; Poel, Mannes; Nijholt, Anton; Zha, H.; Taniguchi, R.-I.; Maybank, S.

    2010-01-01

    In this paper, we present a face alignment approach using granular features, boosting, and an evolutionary search algorithm. Active Appearance Models (AAM) integrate a shape-texture-combined morphable face model into an efficient fitting strategy, then Boosting Appearance Models (BAM) consider the f

  18. Rear-facing car seat (image)

    Science.gov (United States)

    A rear-facing car seat position is recommended for a child who is very young. Extreme injury can occur in an accident because ... child. In a frontal crash a rear-facing car seat is best, because it cradles the head, ...

  19. Unconscious Evaluation of Faces on Social Dimensions

    Science.gov (United States)

    Stewart, Lorna H.; Ajina, Sara; Getov, Spas; Bahrami, Bahador; Todorov, Alexander; Rees, Geraint

    2012-01-01

    It has been proposed that two major axes, dominance and trustworthiness, characterize the social dimensions of face evaluation. Whether evaluation of faces on these social dimensions is restricted to conscious appraisal or happens at a preconscious level is unknown. Here we provide behavioral evidence that such preconscious evaluations exist and…

  20. Evaluation of Carburized and Ground Face Gears

    Science.gov (United States)

    Lewicki, David G.; Handschuh, Robert F.; Heath, Gregory F.; Sheth, Vijay

    1999-01-01

    Experimental durability tests were performed on carburized and ground AIS19310 steel face gears. The tests were in support of a Defense Advanced Research Projects Agency (DARPA) Technology Reinvestment Program (TRP) to enhance face-gear technology. The tests were conducted in the NASA Glenn spiral-bevel-gear/face-gear test facility. Tests were run at 2300 rpm face gear speed and at loads of 64, 76, 88, 100, and 112-percent of the design torque of 377 N-m (3340 in-lb). The carburized and ground face gears demonstrated the required durability when run for ten-million cycles at each of the applied loads. Proper installation was critical for the successful operation of the spur pinions and face gears. A large amount of backlash produced tooth contact patterns that approached the inner-diameter edge of the face-gear tooth. Low backlash produced tooth contact patterns that approached the outer-diameter edge of the face-gear tooth. Measured backlashes in the range of 0.178 to 0.254 mm (0.007 to 0.010 in) produced acceptable tooth contact patterns.