Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality

PubMed Central

Mehta, Dhwani; Siddiqui, Mohammad Faridul Haque

2018-01-01

Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human–Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam. PMID:29389845

Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality.

PubMed

Mehta, Dhwani; Siddiqui, Mohammad Faridul Haque; Javaid, Ahmad Y

2018-02-01

Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human-Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam.

Deep learning based hand gesture recognition in complex scenes

NASA Astrophysics Data System (ADS)

Ni, Zihan; Sang, Nong; Tan, Cheng

2018-03-01

Recently, region-based convolutional neural networks(R-CNNs) have achieved significant success in the field of object detection, but their accuracy is not too high for small objects and similar objects, such as the gestures. To solve this problem, we present an online hard example testing(OHET) technology to evaluate the confidence of the R-CNNs' outputs, and regard those outputs with low confidence as hard examples. In this paper, we proposed a cascaded networks to recognize the gestures. Firstly, we use the region-based fully convolutional neural network(R-FCN), which is capable of the detection for small object, to detect the gestures, and then use the OHET to select the hard examples. To enhance the accuracy of the gesture recognition, we re-classify the hard examples through VGG-19 classification network to obtain the final output of the gesture recognition system. Through the contrast experiments with other methods, we can see that the cascaded networks combined with the OHET reached to the state-of-the-art results of 99.3% mAP on small and similar gestures in complex scenes.

Autonomous learning in gesture recognition by using lobe component analysis

NASA Astrophysics Data System (ADS)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

PubMed

Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

2015-10-01

Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.

Finger tips detection for two handed gesture recognition

NASA Astrophysics Data System (ADS)

Bhuyan, M. K.; Kar, Mithun Kumar; Neog, Debanga Raj

2011-10-01

In this paper, a novel algorithm is proposed for fingertips detection in view of two-handed static hand pose recognition. In our method, finger tips of both hands are detected after detecting hand regions by skin color-based segmentation. At first, the face is removed in the image by using Haar classifier and subsequently, the regions corresponding to the gesturing hands are isolated by a region labeling technique. Next, the key geometric features characterizing gesturing hands are extracted for two hands. Finally, for all possible/allowable finger movements, a probabilistic model is developed for pose recognition. Proposed method can be employed in a variety of applications like sign language recognition and human-robot-interactions etc.

MGRA: Motion Gesture Recognition via Accelerometer.

PubMed

Hong, Feng; You, Shujuan; Wei, Meiyu; Zhang, Yongtuo; Guo, Zhongwen

2016-04-13

Accelerometers have been widely embedded in most current mobile devices, enabling easy and intuitive operations. This paper proposes a Motion Gesture Recognition system (MGRA) based on accelerometer data only, which is entirely implemented on mobile devices and can provide users with real-time interactions. A robust and unique feature set is enumerated through the time domain, the frequency domain and singular value decomposition analysis using our motion gesture set containing 11,110 traces. The best feature vector for classification is selected, taking both static and mobile scenarios into consideration. MGRA exploits support vector machine as the classifier with the best feature vector. Evaluations confirm that MGRA can accommodate a broad set of gesture variations within each class, including execution time, amplitude and non-gestural movement. Extensive evaluations confirm that MGRA achieves higher accuracy under both static and mobile scenarios and costs less computation time and energy on an LG Nexus 5 than previous methods.

Gesture Recognition Based on the Probability Distribution of Arm Trajectories

NASA Astrophysics Data System (ADS)

Wan, Khairunizam; Sawada, Hideyuki

The use of human motions for the interaction between humans and computers is becoming an attractive alternative to verbal media, especially through the visual interpretation of the human body motion. In particular, hand gestures are used as non-verbal media for the humans to communicate with machines that pertain to the use of the human gestures to interact with them. This paper introduces a 3D motion measurement of the human upper body for the purpose of the gesture recognition, which is based on the probability distribution of arm trajectories. In this study, by examining the characteristics of the arm trajectories given by a signer, motion features are selected and classified by using a fuzzy technique. Experimental results show that the use of the features extracted from arm trajectories effectively works on the recognition of dynamic gestures of a human, and gives a good performance to classify various gesture patterns.

Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

NASA Astrophysics Data System (ADS)

Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

2014-09-01

Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

[Neural mechanisms of facial recognition].

PubMed

Nagai, Chiyoko

2007-01-01

We review recent researches in neural mechanisms of facial recognition in the light of three aspects: facial discrimination and identification, recognition of facial expressions, and face perception in itself. First, it has been demonstrated that the fusiform gyrus has a main role of facial discrimination and identification. However, whether the FFA (fusiform face area) is really a special area for facial processing or not is controversial; some researchers insist that the FFA is related to 'becoming an expert' for some kinds of visual objects, including faces. Neural mechanisms of prosopagnosia would be deeply concerned to this issue. Second, the amygdala seems to be very concerned to recognition of facial expressions, especially fear. The amygdala, connected with the superior temporal sulcus and the orbitofrontal cortex, appears to operate the cortical function. The amygdala and the superior temporal sulcus are related to gaze recognition, which explains why a patient with bilateral amygdala damage could not recognize only a fear expression; the information from eyes is necessary for fear recognition. Finally, even a newborn infant can recognize a face as a face, which is congruent with the innate hypothesis of facial recognition. Some researchers speculate that the neural basis of such face perception is the subcortical network, comprised of the amygdala, the superior colliculus, and the pulvinar. This network would relate to covert recognition that prosopagnosic patients have.

Static hand gesture recognition from a video

NASA Astrophysics Data System (ADS)

Rokade, Rajeshree S.; Doye, Dharmpal

2011-10-01

A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

Hand gesture recognition by analysis of codons

NASA Astrophysics Data System (ADS)

Ramachandra, Poornima; Shrikhande, Neelima

2007-09-01

The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

Facial recognition in education system

NASA Astrophysics Data System (ADS)

Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

2017-11-01

Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

Composite Artistry Meets Facial Recognition Technology: Exploring the Use of Facial Recognition Technology to Identify Composite Images

DTIC Science & Technology

2011-09-01

be submitted into a facial recognition program for comparison with millions of possible matches, offering abundant opportunities to identify the...to leverage the robust number of comparative opportunities associated with facial recognition programs. This research investigates the efficacy of...combining composite forensic artistry with facial recognition technology to create a viable investigative tool to identify suspects, as well as better

Biometrics: A Look at Facial Recognition

DTIC Science & Technology

a facial recognition system in the city’s Oceanfront tourist area. The system has been tested and has recently been fully implemented. Senator...Kenneth W. Stolle, the Chairman of the Virginia State Crime Commission, established a Facial Recognition Technology Sub-Committee to examine the issue of... facial recognition technology. This briefing begins by defining biometrics and discussing examples of the technology. It then explains how biometrics

Two Ways to Facial Expression Recognition? Motor and Visual Information Have Different Effects on Facial Expression Recognition.

PubMed

de la Rosa, Stephan; Fademrecht, Laura; Bülthoff, Heinrich H; Giese, Martin A; Curio, Cristóbal

2018-06-01

Motor-based theories of facial expression recognition propose that the visual perception of facial expression is aided by sensorimotor processes that are also used for the production of the same expression. Accordingly, sensorimotor and visual processes should provide congruent emotional information about a facial expression. Here, we report evidence that challenges this view. Specifically, the repeated execution of facial expressions has the opposite effect on the recognition of a subsequent facial expression than the repeated viewing of facial expressions. Moreover, the findings of the motor condition, but not of the visual condition, were correlated with a nonsensory condition in which participants imagined an emotional situation. These results can be well accounted for by the idea that facial expression recognition is not always mediated by motor processes but can also be recognized on visual information alone.

Facial recognition in children after perinatal stroke.

PubMed

Ballantyne, A O; Trauner, D A

1999-04-01

To examine the effects of prenatal or perinatal stroke on the facial recognition skills of children and young adults. It was hypothesized that the nature and extent of facial recognition deficits seen in patients with early-onset lesions would be different from that seen in adults with later-onset neurologic impairment. Numerous studies with normal and neurologically impaired adults have found a right-hemisphere superiority for facial recognition. In contrast, little is known about facial recognition in children after early focal brain damage. Forty subjects had single, unilateral brain lesions from pre- or perinatal strokes (20 had left-hemisphere damage, and 20 had right-hemisphere damage), and 40 subjects were controls who were individually matched to the lesion subjects on the basis of age, sex, and socioeconomic status. Each subject was given the Short-Form of Benton's Test of Facial Recognition. Data were analyzed using the Wilcoxon matched-pairs signed-rank test and multiple regression. The lesion subjects performed significantly more poorly than did matched controls. There was no clear-cut lateralization effect, with the left-hemisphere group performing significantly more poorly than matched controls and the right-hemisphere group showing a trend toward poorer performance. Parietal lobe involvement, regardless of lesion side, adversely affected facial recognition performance in the lesion group. Results could not be accounted for by IQ differences between lesion and control groups, nor was lesion severity systematically related to facial recognition performance. Pre- or perinatal unilateral brain damage results in a subtle disturbance in facial recognition ability, independent of the side of the lesion. Parietal lobe involvement, in particular, has an adverse effect on facial recognition skills. These findings suggest that the parietal lobes may be involved in the acquisition of facial recognition ability from a very early point in brain development, but

Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect

NASA Astrophysics Data System (ADS)

Artyukhin, S. G.; Mestetskiy, L. M.

2015-05-01

This paper presents an efficient framework for solving the problem of static gesture recognition based on data obtained from the web cameras and depth sensor Kinect (RGB-D - data). Each gesture given by a pair of images: color image and depth map. The database store gestures by it features description, genereated by frame for each gesture of the alphabet. Recognition algorithm takes as input a video sequence (a sequence of frames) for marking, put in correspondence with each frame sequence gesture from the database, or decide that there is no suitable gesture in the database. First, classification of the frame of the video sequence is done separately without interframe information. Then, a sequence of successful marked frames in equal gesture is grouped into a single static gesture. We propose a method combined segmentation of frame by depth map and RGB-image. The primary segmentation is based on the depth map. It gives information about the position and allows to get hands rough border. Then, based on the color image border is specified and performed analysis of the shape of the hand. Method of continuous skeleton is used to generate features. We propose a method of skeleton terminal branches, which gives the opportunity to determine the position of the fingers and wrist. Classification features for gesture is description of the position of the fingers relative to the wrist. The experiments were carried out with the developed algorithm on the example of the American Sign Language. American Sign Language gesture has several components, including the shape of the hand, its orientation in space and the type of movement. The accuracy of the proposed method is evaluated on the base of collected gestures consisting of 2700 frames.

[Measuring impairment of facial affects recognition in schizophrenia. Preliminary study of the facial emotions recognition task (TREF)].

PubMed

Gaudelus, B; Virgile, J; Peyroux, E; Leleu, A; Baudouin, J-Y; Franck, N

2015-06-01

The impairment of social cognition, including facial affects recognition, is a well-established trait in schizophrenia, and specific cognitive remediation programs focusing on facial affects recognition have been developed by different teams worldwide. However, even though social cognitive impairments have been confirmed, previous studies have also shown heterogeneity of the results between different subjects. Therefore, assessment of personal abilities should be measured individually before proposing such programs. Most research teams apply tasks based on facial affects recognition by Ekman et al. or Gur et al. However, these tasks are not easily applicable in a clinical exercise. Here, we present the Facial Emotions Recognition Test (TREF), which is designed to identify facial affects recognition impairments in a clinical practice. The test is composed of 54 photos and evaluates abilities in the recognition of six universal emotions (joy, anger, sadness, fear, disgust and contempt). Each of these emotions is represented with colored photos of 4 different models (two men and two women) at nine intensity levels from 20 to 100%. Each photo is presented during 10 seconds; no time limit for responding is applied. The present study compared the scores of the TREF test in a sample of healthy controls (64 subjects) and people with stabilized schizophrenia (45 subjects) according to the DSM IV-TR criteria. We analysed global scores for all emotions, as well as sub scores for each emotion between these two groups, taking into account gender differences. Our results were coherent with previous findings. Applying TREF, we confirmed an impairment in facial affects recognition in schizophrenia by showing significant differences between the two groups in their global results (76.45% for healthy controls versus 61.28% for people with schizophrenia), as well as in sub scores for each emotion except for joy. Scores for women were significantly higher than for men in the population

[Neurological disease and facial recognition].

PubMed

Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

2012-07-01

To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

Dynamic gesture recognition using neural networks: a fundament for advanced interaction construction

NASA Astrophysics Data System (ADS)

Boehm, Klaus; Broll, Wolfgang; Sokolewicz, Michael A.

1994-04-01

Interaction in virtual reality environments is still a challenging task. Static hand posture recognition is currently the most common and widely used method for interaction using glove input devices. In order to improve the naturalness of interaction, and thereby decrease the user-interface learning time, there is a need to be able to recognize dynamic gestures. In this paper we describe our approach to overcoming the difficulties of dynamic gesture recognition (DGR) using neural networks. Backpropagation neural networks have already proven themselves to be appropriate and efficient for posture recognition. However, the extensive amount of data involved in DGR requires a different approach. Because of features such as topology preservation and automatic-learning, Kohonen Feature Maps are particularly suitable for the reduction of the high dimensional data space that is the result of a dynamic gesture, and are thus implemented for this task.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Using a social robot to teach gestural recognition and production in children with autism spectrum disorders.

PubMed

So, Wing-Chee; Wong, Miranda Kit-Yi; Lam, Carrie Ka-Yee; Lam, Wan-Yi; Chui, Anthony Tsz-Fung; Lee, Tsz-Lok; Ng, Hoi-Man; Chan, Chun-Hung; Fok, Daniel Chun-Wing

2017-07-04

While it has been argued that children with autism spectrum disorders are responsive to robot-like toys, very little research has examined the impact of robot-based intervention on gesture use. These children have delayed gestural development. We used a social robot in two phases to teach them to recognize and produce eight pantomime gestures that expressed feelings and needs. Compared to the children in the wait-list control group (N = 6), those in the intervention group (N = 7) were more likely to recognize gestures and to gesture accurately in trained and untrained scenarios. They also generalized the acquired recognition (but not production) skills to human-to-human interaction. The benefits and limitations of robot-based intervention for gestural learning were highlighted. Implications for Rehabilitation Compared to typically-developing children, children with autism spectrum disorders have delayed development of gesture comprehension and production. Robot-based intervention program was developed to teach children with autism spectrum disorders recognition (Phase I) and production (Phase II) of eight pantomime gestures that expressed feelings and needs. Children in the intervention group (but not in the wait-list control group) were able to recognize more gestures in both trained and untrained scenarios and generalize the acquired gestural recognition skills to human-to-human interaction. Similar findings were reported for gestural production except that there was no strong evidence showing children in the intervention group could produce gestures accurately in human-to-human interaction.

Gesture Recognition for Educational Games: Magic Touch Math

NASA Astrophysics Data System (ADS)

Kye, Neo Wen; Mustapha, Aida; Azah Samsudin, Noor

2017-08-01

Children nowadays are having problem learning and understanding basic mathematical operations because they are not interested in studying or learning mathematics. This project proposes an educational game called Magic Touch Math that focuses on basic mathematical operations targeted to children between the age of three to five years old using gesture recognition to interact with the game. Magic Touch Math was developed in accordance to the Game Development Life Cycle (GDLC) methodology. The prototype developed has helped children to learn basic mathematical operations via intuitive gestures. It is hoped that the application is able to get the children motivated and interested in mathematics.

Full-body gestures and movements recognition: user descriptive and unsupervised learning approaches in GDL classifier

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Ogiela, Marek R.

2014-09-01

Gesture Description Language (GDL) is a classifier that enables syntactic description and real time recognition of full-body gestures and movements. Gestures are described in dedicated computer language named Gesture Description Language script (GDLs). In this paper we will introduce new GDLs formalisms that enable recognition of selected classes of movement trajectories. The second novelty is new unsupervised learning method with which it is possible to automatically generate GDLs descriptions. We have initially evaluated both proposed extensions of GDL and we have obtained very promising results. Both the novel methodology and evaluation results will be described in this paper.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

[Emotional facial expression recognition impairment in Parkinson disease].

PubMed

Lachenal-Chevallet, Karine; Bediou, Benoit; Bouvard, Martine; Thobois, Stéphane; Broussolle, Emmanuel; Vighetto, Alain; Krolak-Salmon, Pierre

2006-03-01

some behavioral disturbances observed in Parkinson's disease (PD) could be related to impaired recognition of various social messages particularly emotional facial expressions. facial expression recognition was assessed using morphed faces (five emotions: happiness, fear, anger, disgust, neutral), and compared to gender recognition and general cognitive assessment in 12 patients with Parkinson's disease and 14 controls subjects. facial expression recognition was impaired among patients, whereas gender recognitions, visuo-perceptive capacities and total efficiency were preserved. Post hoc analyses disclosed a deficit for fear and disgust recognition compared to control subjects. the impairment of emotional facial expression recognition in PD appears independent of other cognitive deficits. This impairment may be related to the dopaminergic depletion in basal ganglia and limbic brain regions. They could take a part in psycho-behavioral disorders and particularly in communication disorders observed in Parkinson's disease patients.

Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli

PubMed Central

Wingenbach, Tanja S. H.; Brosnan, Mark; Pfaltz, Monique C.; Plichta, Michael M.; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed. PMID:29928240

Incongruence Between Observers' and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli.

PubMed

Wingenbach, Tanja S H; Brosnan, Mark; Pfaltz, Monique C; Plichta, Michael M; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others' facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others' facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others' faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions' order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.

Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

NASA Astrophysics Data System (ADS)

Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun

2014-05-01

With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.

A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

PubMed

Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

2014-01-01

Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition.

Effect of Dialogue on Demonstrations: Direct Quotations, Facial Portrayals, Hand Gestures, and Figurative References

ERIC Educational Resources Information Center

Bavelas, Janet; Gerwing, Jennifer; Healing, Sara

2014-01-01

"Demonstrations" (e.g., direct quotations, conversational facial portrayals, conversational hand gestures, and figurative references) lack conventional meanings, relying instead on a resemblance to their referent. Two experiments tested our theory that demonstrations are a class of communicative acts that speakers are more likely to use…

Using virtual data for training deep model for hand gesture recognition

NASA Astrophysics Data System (ADS)

Nikolaev, E. I.; Dvoryaninov, P. V.; Lensky, Y. Y.; Drozdovsky, N. S.

2018-05-01

Deep learning has shown real promise for the classification efficiency for hand gesture recognition problems. In this paper, the authors present experimental results for a deeply-trained model for hand gesture recognition through the use of hand images. The authors have trained two deep convolutional neural networks. The first architecture produces the hand position as a 2D-vector by input hand image. The second one predicts the hand gesture class for the input image. The first proposed architecture produces state of the art results with an accuracy rate of 89% and the second architecture with split input produces accuracy rate of 85.2%. In this paper, the authors also propose using virtual data for training a supervised deep model. Such technique is aimed to avoid using original labelled images in the training process. The interest of this method in data preparation is motivated by the need to overcome one of the main challenges of deep supervised learning: using a copious amount of labelled data during training.

Facial Recognition Training: Improving Intelligence Collection by Soldiers

DTIC Science & Technology

2008-01-01

Facial Recognition Training: Improving Intelligence Collection by Soldiers By: 2LT Michael Mitchell, MI, ALARNG “In combat, you don’t rise to...technology, but on patrol a Soldier cannot use a device as quickly as simply looking at the subject. Why is Facial Recognition Difficult? Soldiers...00-2008 to 00-00-2008 4. TITLE AND SUBTITLE Facial Recognition Training: Improving Intelligence Collection by Soldiers 5a. CONTRACT NUMBER 5b

Impaired recognition of happy facial expressions in bipolar disorder.

PubMed

Lawlor-Savage, Linette; Sponheim, Scott R; Goghari, Vina M

2014-08-01

The ability to accurately judge facial expressions is important in social interactions. Individuals with bipolar disorder have been found to be impaired in emotion recognition; however, the specifics of the impairment are unclear. This study investigated whether facial emotion recognition difficulties in bipolar disorder reflect general cognitive, or emotion-specific, impairments. Impairment in the recognition of particular emotions and the role of processing speed in facial emotion recognition were also investigated. Clinically stable bipolar patients (n = 17) and healthy controls (n = 50) judged five facial expressions in two presentation types, time-limited and self-paced. An age recognition condition was used as an experimental control. Bipolar patients' overall facial recognition ability was unimpaired. However, patients' specific ability to judge happy expressions under time constraints was impaired. Findings suggest a deficit in happy emotion recognition impacted by processing speed. Given the limited sample size, further investigation with a larger patient sample is warranted.

The Effect of the Visual Context in the Recognition of Symbolic Gestures

PubMed Central

Villarreal, Mirta F.; Fridman, Esteban A.; Leiguarda, Ramón C.

2012-01-01

Background To investigate, by means of fMRI, the influence of the visual environment in the process of symbolic gesture recognition. Emblems are semiotic gestures that use movements or hand postures to symbolically encode and communicate meaning, independently of language. They often require contextual information to be correctly understood. Until now, observation of symbolic gestures was studied against a blank background where the meaning and intentionality of the gesture was not fulfilled. Methodology/Principal Findings Normal subjects were scanned while observing short videos of an individual performing symbolic gesture with or without the corresponding visual context and the context scenes without gestures. The comparison between gestures regardless of the context demonstrated increased activity in the inferior frontal gyrus, the superior parietal cortex and the temporoparietal junction in the right hemisphere and the precuneus and posterior cingulate bilaterally, while the comparison between context and gestures alone did not recruit any of these regions. Conclusions/Significance These areas seem to be crucial for the inference of intentions in symbolic gestures observed in their natural context and represent an interrelated network formed by components of the putative human neuron mirror system as well as the mentalizing system. PMID:22363406

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

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

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

PubMed

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

2017-10-12

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

Facial emotion recognition and borderline personality pathology.

PubMed

Meehan, Kevin B; De Panfilis, Chiara; Cain, Nicole M; Antonucci, Camilla; Soliani, Antonio; Clarkin, John F; Sambataro, Fabio

2017-09-01

The impact of borderline personality pathology on facial emotion recognition has been in dispute; with impaired, comparable, and enhanced accuracy found in high borderline personality groups. Discrepancies are likely driven by variations in facial emotion recognition tasks across studies (stimuli type/intensity) and heterogeneity in borderline personality pathology. This study evaluates facial emotion recognition for neutral and negative emotions (fear/sadness/disgust/anger) presented at varying intensities. Effortful control was evaluated as a moderator of facial emotion recognition in borderline personality. Non-clinical multicultural undergraduates (n = 132) completed a morphed facial emotion recognition task of neutral and negative emotional expressions across different intensities (100% Neutral; 25%/50%/75% Emotion) and self-reported borderline personality features and effortful control. Greater borderline personality features related to decreased accuracy in detecting neutral faces, but increased accuracy in detecting negative emotion faces, particularly at low-intensity thresholds. This pattern was moderated by effortful control; for individuals with low but not high effortful control, greater borderline personality features related to misattributions of emotion to neutral expressions, and enhanced detection of low-intensity emotional expressions. Individuals with high borderline personality features may therefore exhibit a bias toward detecting negative emotions that are not or barely present; however, good self-regulatory skills may protect against this potential social-cognitive vulnerability. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Ape gestures and language evolution

PubMed Central

Pollick, Amy S.; de Waal, Frans B. M.

2007-01-01

The natural communication of apes may hold clues about language origins, especially because apes frequently gesture with limbs and hands, a mode of communication thought to have been the starting point of human language evolution. The present study aimed to contrast brachiomanual gestures with orofacial movements and vocalizations in the natural communication of our closest primate relatives, bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). We tested whether gesture is the more flexible form of communication by measuring the strength of association between signals and specific behavioral contexts, comparing groups of both the same and different ape species. Subjects were two captive bonobo groups, a total of 13 individuals, and two captive chimpanzee groups, a total of 34 individuals. The study distinguished 31 manual gestures and 18 facial/vocal signals. It was found that homologous facial/vocal displays were used very similarly by both ape species, yet the same did not apply to gestures. Both within and between species gesture usage varied enormously. Moreover, bonobos showed greater flexibility in this regard than chimpanzees and were also the only species in which multimodal communication (i.e., combinations of gestures and facial/vocal signals) added to behavioral impact on the recipient. PMID:17470779

Chair alarm for patient fall prevention based on gesture recognition and interactivity.

PubMed

Knight, Heather; Lee, Jae-Kyu; Ma, Hongshen

2008-01-01

The Gesture Recognition Interactive Technology (GRiT) Chair Alarm aims to prevent patient falls from chairs and wheelchairs by recognizing the gesture of a patient attempting to stand. Patient falls are one of the greatest causes of injury in hospitals. Current chair and bed exit alarm systems are inadequate because of insufficient notification, high false-alarm rate, and long trigger delays. The GRiT chair alarm uses an array of capacitive proximity sensors and pressure sensors to create a map of the patient's sitting position, which is then processed using gesture recognition algorithms to determine when a patient is attempting to stand and to alarm the care providers. This system also uses a range of voice and light feedback to encourage the patient to remain seated and/or to make use of the system's integrated nurse-call function. This system can be seamlessly integrated into existing hospital WiFi networks to send notifications and approximate patient location through existing nurse call systems.

Automatic Facial Expression Recognition and Operator Functional State

NASA Technical Reports Server (NTRS)

Blanson, Nina

2012-01-01

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

Automatic Facial Expression Recognition and Operator Functional State

NASA Technical Reports Server (NTRS)

Blanson, Nina

2011-01-01

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

Static facial expression recognition with convolution neural networks

NASA Astrophysics Data System (ADS)

Zhang, Feng; Chen, Zhong; Ouyang, Chao; Zhang, Yifei

2018-03-01

Facial expression recognition is a currently active research topic in the fields of computer vision, pattern recognition and artificial intelligence. In this paper, we have developed a convolutional neural networks (CNN) for classifying human emotions from static facial expression into one of the seven facial emotion categories. We pre-train our CNN model on the combined FER2013 dataset formed by train, validation and test set and fine-tune on the extended Cohn-Kanade database. In order to reduce the overfitting of the models, we utilized different techniques including dropout and batch normalization in addition to data augmentation. According to the experimental result, our CNN model has excellent classification performance and robustness for facial expression recognition.

Facial expression recognition based on improved deep belief networks

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

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

Laptop Computer - Based Facial Recognition System Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. A. Cain; G. B. Singleton

2001-03-01

The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results.more » After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master

Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

NASA Astrophysics Data System (ADS)

Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

2018-03-01

The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

Enhancement of gesture recognition for contactless interface using a personalized classifier in the operating room.

PubMed

Cho, Yongwon; Lee, Areum; Park, Jongha; Ko, Bemseok; Kim, Namkug

2018-07-01

Contactless operating room (OR) interfaces are important for computer-aided surgery, and have been developed to decrease the risk of contamination during surgical procedures. In this study, we used Leap Motion™, with a personalized automated classifier, to enhance the accuracy of gesture recognition for contactless interfaces. This software was trained and tested on a personal basis that means the training of gesture per a user. We used 30 features including finger and hand data, which were computed, selected, and fed into a multiclass support vector machine (SVM), and Naïve Bayes classifiers and to predict and train five types of gestures including hover, grab, click, one peak, and two peaks. Overall accuracy of the five gestures was 99.58% ± 0.06, and 98.74% ± 3.64 on a personal basis using SVM and Naïve Bayes classifiers, respectively. We compared gesture accuracy across the entire dataset and used SVM and Naïve Bayes classifiers to examine the strength of personal basis training. We developed and enhanced non-contact interfaces with gesture recognition to enhance OR control systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Does Facial Amimia Impact the Recognition of Facial Emotions? An EMG Study in Parkinson’s Disease

PubMed Central

Argaud, Soizic; Delplanque, Sylvain; Houvenaghel, Jean-François; Auffret, Manon; Duprez, Joan; Vérin, Marc; Grandjean, Didier; Sauleau, Paul

2016-01-01

According to embodied simulation theory, understanding other people’s emotions is fostered by facial mimicry. However, studies assessing the effect of facial mimicry on the recognition of emotion are still controversial. In Parkinson’s disease (PD), one of the most distinctive clinical features is facial amimia, a reduction in facial expressiveness, but patients also show emotional disturbances. The present study used the pathological model of PD to examine the role of facial mimicry on emotion recognition by investigating EMG responses in PD patients during a facial emotion recognition task (anger, joy, neutral). Our results evidenced a significant decrease in facial mimicry for joy in PD, essentially linked to the absence of reaction of the zygomaticus major and the orbicularis oculi muscles in response to happy avatars, whereas facial mimicry for expressions of anger was relatively preserved. We also confirmed that PD patients were less accurate in recognizing positive and neutral facial expressions and highlighted a beneficial effect of facial mimicry on the recognition of emotion. We thus provide additional arguments for embodied simulation theory suggesting that facial mimicry is a potential lever for therapeutic actions in PD even if it seems not to be necessarily required in recognizing emotion as such. PMID:27467393

The review and results of different methods for facial recognition

NASA Astrophysics Data System (ADS)

Le, Yifan

2017-09-01

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

Enhanced facial texture illumination normalization for face recognition.

PubMed

Luo, Yong; Guan, Ye-Peng

2015-08-01

An uncontrolled lighting condition is one of the most critical challenges for practical face recognition applications. An enhanced facial texture illumination normalization method is put forward to resolve this challenge. An adaptive relighting algorithm is developed to improve the brightness uniformity of face images. Facial texture is extracted by using an illumination estimation difference algorithm. An anisotropic histogram-stretching algorithm is proposed to minimize the intraclass distance of facial skin and maximize the dynamic range of facial texture distribution. Compared with the existing methods, the proposed method can more effectively eliminate the redundant information of facial skin and illumination. Extensive experiments show that the proposed method has superior performance in normalizing illumination variation and enhancing facial texture features for illumination-insensitive face recognition.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Influence of make-up on facial recognition.

PubMed

Ueda, Sayako; Koyama, Takamasa

2010-01-01

Make-up may enhance or disguise facial characteristics. The influence of wearing make-up on facial recognition could be of two kinds: (i) when women do not wear make-up and then are seen with make-up, and (ii) when women wear make-up and then are seen without make-up. A study is reported which shows that light make-up makes it easier to recognise a face, and heavy make-up makes it more difficult. Seeing initially a made-up face makes any subsequent facial recognition more difficult than initially seeing that face without make-up.

Influences on Facial Emotion Recognition in Deaf Children

ERIC Educational Resources Information Center

Sidera, Francesc; Amadó, Anna; Martínez, Laura

2017-01-01

This exploratory research is aimed at studying facial emotion recognition abilities in deaf children and how they relate to linguistic skills and the characteristics of deafness. A total of 166 participants (75 deaf) aged 3-8 years were administered the following tasks: facial emotion recognition, naming vocabulary and cognitive ability. The…

Facial Emotion Recognition in Bipolar Disorder and Healthy Aging.

PubMed

Altamura, Mario; Padalino, Flavia A; Stella, Eleonora; Balzotti, Angela; Bellomo, Antonello; Palumbo, Rocco; Di Domenico, Alberto; Mammarella, Nicola; Fairfield, Beth

2016-03-01

Emotional face recognition is impaired in bipolar disorder, but it is not clear whether this is specific for the illness. Here, we investigated how aging and bipolar disorder influence dynamic emotional face recognition. Twenty older adults, 16 bipolar patients, and 20 control subjects performed a dynamic affective facial recognition task and a subsequent rating task. Participants pressed a key as soon as they were able to discriminate whether the neutral face was assuming a happy or angry facial expression and then rated the intensity of each facial expression. Results showed that older adults recognized happy expressions faster, whereas bipolar patients recognized angry expressions faster. Furthermore, both groups rated emotional faces more intensely than did the control subjects. This study is one of the first to compare how aging and clinical conditions influence emotional facial recognition and underlines the need to consider the role of specific and common factors in emotional face recognition.

Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

NASA Astrophysics Data System (ADS)

Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

2017-03-01

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

Slowing down presentation of facial movements and vocal sounds enhances facial expression recognition and induces facial-vocal imitation in children with autism.

PubMed

Tardif, Carole; Lainé, France; Rodriguez, Mélissa; Gepner, Bruno

2007-09-01

This study examined the effects of slowing down presentation of facial expressions and their corresponding vocal sounds on facial expression recognition and facial and/or vocal imitation in children with autism. Twelve autistic children and twenty-four normal control children were presented with emotional and non-emotional facial expressions on CD-Rom, under audio or silent conditions, and under dynamic visual conditions (slowly, very slowly, at normal speed) plus a static control. Overall, children with autism showed lower performance in expression recognition and more induced facial-vocal imitation than controls. In the autistic group, facial expression recognition and induced facial-vocal imitation were significantly enhanced in slow conditions. Findings may give new perspectives for understanding and intervention for verbal and emotional perceptive and communicative impairments in autistic populations.

Exploring the Relationship between Gestural Recognition and Imitation: Evidence of Dyspraxia in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Ham, Heidi Stieglitz; Bartolo, Angela; Corley, Martin; Rajendran, Gnanathusharan; Szabo, Aniko; Swanson, Sara

2011-01-01

In this study, the relationship between gesture recognition and imitation was explored. Nineteen individuals with Autism Spectrum Disorder (ASD) were compared to a control group of 23 typically developing children on their ability to imitate and recognize three gesture types (transitive, intransitive, and pantomimes). The ASD group performed more…

Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition

NASA Astrophysics Data System (ADS)

Buciu, Ioan; Pitas, Ioannis

Two main theories exist with respect to face encoding and representation in the human visual system (HVS). The first one refers to the dense (holistic) representation of the face, where faces have "holon"-like appearance. The second one claims that a more appropriate face representation is given by a sparse code, where only a small fraction of the neural cells corresponding to face encoding is activated. Theoretical and experimental evidence suggest that the HVS performs face analysis (encoding, storing, face recognition, facial expression recognition) in a structured and hierarchical way, where both representations have their own contribution and goal. According to neuropsychological experiments, it seems that encoding for face recognition, relies on holistic image representation, while a sparse image representation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expression recognition fall into the same two representation types. Like in Neuroscience, the techniques which perform better for face recognition yield a holistic image representation, while those techniques suitable for facial expression recognition use a sparse or local image representation. The proposed mathematical models of image formation and encoding try to simulate the efficient storing, organization and coding of data in the human cortex. This is equivalent with embedding constraints in the model design regarding dimensionality reduction, redundant information minimization, mutual information minimization, non-negativity constraints, class information, etc. The presented techniques are applied as a feature extraction step followed by a classification method, which also heavily influences the recognition results.

Neuroticism and facial emotion recognition in healthy adults.

PubMed

Andric, Sanja; Maric, Nadja P; Knezevic, Goran; Mihaljevic, Marina; Mirjanic, Tijana; Velthorst, Eva; van Os, Jim

2016-04-01

The aim of the present study was to examine whether healthy individuals with higher levels of neuroticism, a robust independent predictor of psychopathology, exhibit altered facial emotion recognition performance. Facial emotion recognition accuracy was investigated in 104 healthy adults using the Degraded Facial Affect Recognition Task (DFAR). Participants' degree of neuroticism was estimated using neuroticism scales extracted from the Eysenck Personality Questionnaire and the Revised NEO Personality Inventory. A significant negative correlation between the degree of neuroticism and the percentage of correct answers on DFAR was found only for happy facial expression (significant after applying Bonferroni correction). Altered sensitivity to the emotional context represents a useful and easy way to obtain cognitive phenotype that correlates strongly with inter-individual variations in neuroticism linked to stress vulnerability and subsequent psychopathology. Present findings could have implication in early intervention strategies and staging models in psychiatry. © 2015 Wiley Publishing Asia Pty Ltd.

Comparison of emotion recognition from facial expression and music.

PubMed

Gaspar, Tina; Labor, Marina; Jurić, Iva; Dumancić, Dijana; Ilakovac, Vesna; Heffer, Marija

2011-01-01

The recognition of basic emotions in everyday communication involves interpretation of different visual and auditory clues. The ability to recognize emotions is not clearly determined as their presentation is usually very short (micro expressions), whereas the recognition itself does not have to be a conscious process. We assumed that the recognition from facial expressions is selected over the recognition of emotions communicated through music. In order to compare the success rate in recognizing emotions presented as facial expressions or in classical music works we conducted a survey which included 90 elementary school and 87 high school students from Osijek (Croatia). The participants had to match 8 photographs of different emotions expressed on the face and 8 pieces of classical music works with 8 offered emotions. The recognition of emotions expressed through classical music pieces was significantly less successful than the recognition of emotional facial expressions. The high school students were significantly better at recognizing facial emotions than the elementary school students, whereas girls were better than boys. The success rate in recognizing emotions from music pieces was associated with higher grades in mathematics. Basic emotions are far better recognized if presented on human faces than in music, possibly because the understanding of facial emotions is one of the oldest communication skills in human society. Female advantage in emotion recognition was selected due to the necessity of their communication with the newborns during early development. The proficiency in recognizing emotional content of music and mathematical skills probably share some general cognitive skills like attention, memory and motivation. Music pieces were differently processed in brain than facial expressions and consequently, probably differently evaluated as relevant emotional clues.

An Individual Finger Gesture Recognition System Based on Motion-Intent Analysis Using Mechanomyogram Signal

PubMed Central

Ding, Huijun; He, Qing; Zhou, Yongjin; Dan, Guo; Cui, Song

2017-01-01

Motion-intent-based finger gesture recognition systems are crucial for many applications such as prosthesis control, sign language recognition, wearable rehabilitation system, and human–computer interaction. In this article, a motion-intent-based finger gesture recognition system is designed to correctly identify the tapping of every finger for the first time. Two auto-event annotation algorithms are firstly applied and evaluated for detecting the finger tapping frame. Based on the truncated signals, the Wavelet packet transform (WPT) coefficients are calculated and compressed as the features, followed by a feature selection method that is able to improve the performance by optimizing the feature set. Finally, three popular classifiers including naive Bayes (NBC), K-nearest neighbor (KNN), and support vector machine (SVM) are applied and evaluated. The recognition accuracy can be achieved up to 94%. The design and the architecture of the system are presented with full system characterization results. PMID:29167655

Interest and attention in facial recognition.

PubMed

Burgess, Melinda C R; Weaver, George E

2003-04-01

When applied to facial recognition, the levels of processing paradigm has yielded consistent results: faces processed in deep conditions are recognized better than faces processed under shallow conditions. However, there are multiple explanations for this occurrence. The own-race advantage in facial recognition, the tendency to recognize faces from one's own race better than faces from another race, is also consistently shown but not clearly explained. This study was designed to test the hypothesis that the levels of processing findings in facial recognition are a result of interest and attention, not differences in processing. This hypothesis was tested for both own and other faces with 105 Caucasian general psychology students. Levels of processing was manipulated as a between-subjects variable; students were asked to answer one of four types of study questions, e.g., "deep" or "shallow" processing questions, while viewing the study faces. Students' recognition of a subset of previously presented Caucasian and African-American faces from a test-set with an equal number of distractor faces was tested. They indicated their interest in and attention to the task. The typical levels of processing effect was observed with better recognition performance in the deep conditions than in the shallow conditions for both own- and other-race faces. The typical own-race advantage was also observed regardless of level of processing condition. For both own- and other-race faces, level of processing explained a significant portion of the recognition variance above and beyond what was explained by interest in and attention to the task.

Cognitive penetrability and emotion recognition in human facial expressions

PubMed Central

Marchi, Francesco

2015-01-01

Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration (CP) of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on CP, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept CP in some cases of emotion recognition. Finally, we discuss a recently proposed mechanism for CP in the face-based recognition of emotion. PMID:26150796

Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury.

PubMed

Neumann, Dawn; McDonald, Brenna C; West, John; Keiski, Michelle A; Wang, Yang

2016-06-01

The neurobiological mechanisms that underlie facial affect recognition deficits after traumatic brain injury (TBI) have not yet been identified. Using functional magnetic resonance imaging (fMRI), study aims were to 1) determine if there are differences in brain activation during facial affect processing in people with TBI who have facial affect recognition impairments (TBI-I) relative to people with TBI and healthy controls who do not have facial affect recognition impairments (TBI-N and HC, respectively); and 2) identify relationships between neural activity and facial affect recognition performance. A facial affect recognition screening task performed outside the scanner was used to determine group classification; TBI patients who performed greater than one standard deviation below normal performance scores were classified as TBI-I, while TBI patients with normal scores were classified as TBI-N. An fMRI facial recognition paradigm was then performed within the 3T environment. Results from 35 participants are reported (TBI-I = 11, TBI-N = 12, and HC = 12). For the fMRI task, TBI-I and TBI-N groups scored significantly lower than the HC group. Blood oxygenation level-dependent (BOLD) signals for facial affect recognition compared to a baseline condition of viewing a scrambled face, revealed lower neural activation in the right fusiform gyrus (FG) in the TBI-I group than the HC group. Right fusiform gyrus activity correlated with accuracy on the facial affect recognition tasks (both within and outside the scanner). Decreased FG activity suggests facial affect recognition deficits after TBI may be the result of impaired holistic face processing. Future directions and clinical implications are discussed.

Familial covariation of facial emotion recognition and IQ in schizophrenia.

PubMed

Andric, Sanja; Maric, Nadja P; Mihaljevic, Marina; Mirjanic, Tijana; van Os, Jim

2016-12-30

Alterations in general intellectual ability and social cognition in schizophrenia are core features of the disorder, evident at the illness' onset and persistent throughout its course. However, previous studies examining cognitive alterations in siblings discordant for schizophrenia yielded inconsistent results. Present study aimed to investigate the nature of the association between facial emotion recognition and general IQ by applying genetically sensitive cross-trait cross-sibling design. Participants (total n=158; patients, unaffected siblings, controls) were assessed using the Benton Facial Recognition Test, the Degraded Facial Affect Recognition Task (DFAR) and the Wechsler Adult Intelligence Scale-III. Patients had lower IQ and altered facial emotion recognition in comparison to other groups. Healthy siblings and controls did not significantly differ in IQ and DFAR performance, but siblings exhibited intermediate angry facial expression recognition. Cross-trait within-subject analyses showed significant associations between overall DFAR performance and IQ in all participants. Within-trait cross-sibling analyses found significant associations between patients' and siblings' IQ and overall DFAR performance, suggesting their familial clustering. Finally, cross-trait cross-sibling analyses revealed familial covariation of facial emotion recognition and IQ in siblings discordant for schizophrenia, further indicating their familial etiology. Both traits are important phenotypes for genetic studies and potential early clinical markers of schizophrenia-spectrum disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Plastic surgery and the biometric e-passport: implications for facial recognition.

PubMed

Ologunde, Rele

2015-04-01

This correspondence comments on the challenges of plastic reconstructive and aesthetic surgery on the facial recognition algorithms employed by biometric passports. The limitations of facial recognition technology in patients who have undergone facial plastic surgery are also discussed. Finally, the advice of the UK HM passport office to people who undergo facial surgery is reported.

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions.

PubMed

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants' tendency to over-attribute anger label to other negative facial expressions. Participants' heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants' performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants' tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children's "pre-existing bias" for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim's perceptive and attentive focus on salient environmental social stimuli.

Interactive and Stereoscopic Hybrid 3D Viewer of Radar Data with Gesture Recognition

NASA Astrophysics Data System (ADS)

Goenetxea, Jon; Moreno, Aitor; Unzueta, Luis; Galdós, Andoni; Segura, Álvaro

This work presents an interactive and stereoscopic 3D viewer of weather information coming from a Doppler radar. The hybrid system shows a GIS model of the regional zone where the radar is located and the corresponding reconstructed 3D volume weather data. To enhance the immersiveness of the navigation, stereoscopic visualization has been added to the viewer, using a polarized glasses based system. The user can interact with the 3D virtual world using a Nintendo Wiimote for navigating through it and a Nintendo Wii Nunchuk for giving commands by means of hand gestures. We also present a dynamic gesture recognition procedure that measures the temporal advance of the performed gesture postures. Experimental results show how dynamic gestures are effectively recognized so that a more natural interaction and immersive navigation in the virtual world is achieved.

Facial Affect Recognition and Social Anxiety in Preschool Children

ERIC Educational Resources Information Center

Ale, Chelsea M.; Chorney, Daniel B.; Brice, Chad S.; Morris, Tracy L.

2010-01-01

Research relating anxiety and facial affect recognition has focused mostly on school-aged children and adults and has yielded mixed results. The current study sought to demonstrate an association among behavioural inhibition and parent-reported social anxiety, shyness, social withdrawal and facial affect recognition performance in 30 children,…

Hand gesture recognition in confined spaces with partial observability and occultation constraints

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions

PubMed Central

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants’ tendency to over-attribute anger label to other negative facial expressions. Participants’ heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants’ performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants’ tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children’s “pre-existing bias” for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim’s perceptive and attentive focus on salient environmental social stimuli. PMID:26509890

Relation between facial affect recognition and configural face processing in antipsychotic-free schizophrenia.

PubMed

Fakra, Eric; Jouve, Elisabeth; Guillaume, Fabrice; Azorin, Jean-Michel; Blin, Olivier

2015-03-01

Deficit in facial affect recognition is a well-documented impairment in schizophrenia, closely connected to social outcome. This deficit could be related to psychopathology, but also to a broader dysfunction in processing facial information. In addition, patients with schizophrenia inadequately use configural information-a type of processing that relies on spatial relationships between facial features. To date, no study has specifically examined the link between symptoms and misuse of configural information in the deficit in facial affect recognition. Unmedicated schizophrenia patients (n = 30) and matched healthy controls (n = 30) performed a facial affect recognition task and a face inversion task, which tests aptitude to rely on configural information. In patients, regressions were carried out between facial affect recognition, symptom dimensions and inversion effect. Patients, compared with controls, showed a deficit in facial affect recognition and a lower inversion effect. Negative symptoms and lower inversion effect could account for 41.2% of the variance in facial affect recognition. This study confirms the presence of a deficit in facial affect recognition, and also of dysfunctional manipulation in configural information in antipsychotic-free patients. Negative symptoms and poor processing of configural information explained a substantial part of the deficient recognition of facial affect. We speculate that this deficit may be caused by several factors, among which independently stand psychopathology and failure in correctly manipulating configural information. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Trujillo, Anna; Shimada, Kenji; Allen, Danette

2016-01-01

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

[Recognition of facial emotions and theory of mind in schizophrenia: could the theory of mind deficit be due to the non-recognition of facial emotions?].

PubMed

Besche-Richard, C; Bourrin-Tisseron, A; Olivier, M; Cuervo-Lombard, C-V; Limosin, F

2012-06-01

The deficits of recognition of facial emotions and attribution of mental states are now well-documented in schizophrenic patients. However, we don't clearly know about the link between these two complex cognitive functions, especially in schizophrenia. In this study, we attempted to test the link between the recognition of facial emotions and the capacities of mentalization, notably the attribution of beliefs, in health and schizophrenic participants. We supposed that the level of performance of recognition of facial emotions, compared to the working memory and executive functioning, was the best predictor of the capacities to attribute a belief. Twenty schizophrenic participants according to DSM-IVTR (mean age: 35.9 years, S.D. 9.07; mean education level: 11.15 years, S.D. 2.58) clinically stabilized, receiving neuroleptic or antipsychotic medication participated in the study. They were matched on age (mean age: 36.3 years, S.D. 10.9) and educational level (mean educational level: 12.10, S.D. 2.25) with 30 matched healthy participants. All the participants were evaluated with a pool of tasks testing the recognition of facial emotions (the faces of Baron-Cohen), the attribution of beliefs (two stories of first order and two stories of second order), the working memory (the digit span of the WAIS-III and the Corsi test) and the executive functioning (Trail Making Test A et B, Wisconsin Card Sorting Test brief version). Comparing schizophrenic and healthy participants, our results confirmed a difference between the performances of the recognition of facial emotions and those of the attribution of beliefs. The result of the simple linear regression showed that the recognition of facial emotions, compared to the performances of working memory and executive functioning, was the best predictor of the performances in the theory of mind stories. Our results confirmed, in a sample of schizophrenic patients, the deficits in the recognition of facial emotions and in the

Mutual information-based facial expression recognition

NASA Astrophysics Data System (ADS)

Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah

2013-12-01

This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.

A study on facial expressions recognition

NASA Astrophysics Data System (ADS)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

[Developmental change in facial recognition by premature infants during infancy].

PubMed

Konishi, Yukihiko; Kusaka, Takashi; Nishida, Tomoko; Isobe, Kenichi; Itoh, Susumu

2014-09-01

Premature infants are thought to be at increased risk for developmental disorders. We evaluated facial recognition by premature infants during early infancy, as this ability has been reported to be impaired commonly in developmentally disabled children. In premature infants and full-term infants at the age of 4 months (4 corrected months for premature infants), visual behaviors while performing facial recognition tasks were determined and analyzed using an eye-tracking system (Tobii T60 manufactured by Tobii Technologics, Sweden). Both types of infants had a preference towards normal facial expressions; however, no preference towards the upper face was observed in premature infants. Our study suggests that facial recognition ability in premature infants may develop differently from that in full-term infants.

Facial emotion recognition in patients with focal and diffuse axonal injury.

PubMed

Yassin, Walid; Callahan, Brandy L; Ubukata, Shiho; Sugihara, Genichi; Murai, Toshiya; Ueda, Keita

2017-01-01

Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

The use of open and machine vision technologies for development of gesture recognition intelligent systems

NASA Astrophysics Data System (ADS)

Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

2018-05-01

The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

Association of impaired facial affect recognition with basic facial and visual processing deficits in schizophrenia.

PubMed

Norton, Daniel; McBain, Ryan; Holt, Daphne J; Ongur, Dost; Chen, Yue

2009-06-15

Impaired emotion recognition has been reported in schizophrenia, yet the nature of this impairment is not completely understood. Recognition of facial emotion depends on processing affective and nonaffective facial signals, as well as basic visual attributes. We examined whether and how poor facial emotion recognition in schizophrenia is related to basic visual processing and nonaffective face recognition. Schizophrenia patients (n = 32) and healthy control subjects (n = 29) performed emotion discrimination, identity discrimination, and visual contrast detection tasks, where the emotionality, distinctiveness of identity, or visual contrast was systematically manipulated. Subjects determined which of two presentations in a trial contained the target: the emotional face for emotion discrimination, a specific individual for identity discrimination, and a sinusoidal grating for contrast detection. Patients had significantly higher thresholds (worse performance) than control subjects for discriminating both fearful and happy faces. Furthermore, patients' poor performance in fear discrimination was predicted by performance in visual detection and face identity discrimination. Schizophrenia patients require greater emotional signal strength to discriminate fearful or happy face images from neutral ones. Deficient emotion recognition in schizophrenia does not appear to be determined solely by affective processing but is also linked to the processing of basic visual and facial information.

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

NASA Astrophysics Data System (ADS)

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

2010-11-01

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

Effects of Minority Status on Facial Recognition and Naming Performance.

ERIC Educational Resources Information Center

Roberts, Richard J.; Hamsher, Kerry

1984-01-01

Examined the differential effects of minority status in Blacks (N=94) on a facial recognition test and a naming test. Results showed that performance on the facial recognition test was relatively free of racial bias, but this was not the case for visual naming. (LLL)

More Pronounced Deficits in Facial Emotion Recognition for Schizophrenia than Bipolar Disorder

PubMed Central

Goghari, Vina M; Sponheim, Scott R

2012-01-01

Schizophrenia and bipolar disorder are typically separated in diagnostic systems. Behavioural, cognitive, and brain abnormalities associated with each disorder nonetheless overlap. We evaluated the diagnostic specificity of facial emotion recognition deficits in schizophrenia and bipolar disorder to determine whether select aspects of emotion recognition differed for the two disorders. The investigation used an experimental task that included the same facial images in an emotion recognition condition and an age recognition condition (to control for processes associated with general face recognition) in 27 schizophrenia patients, 16 bipolar I patients, and 30 controls. Schizophrenia and bipolar patients exhibited both shared and distinct aspects of facial emotion recognition deficits. Schizophrenia patients had deficits in recognizing angry facial expressions compared to healthy controls and bipolar patients. Compared to control participants, both schizophrenia and bipolar patients were more likely to mislabel facial expressions of anger as fear. Given that schizophrenia patients exhibited a deficit in emotion recognition for angry faces, which did not appear due to generalized perceptual and cognitive dysfunction, improving recognition of threat-related expression may be an important intervention target to improve social functioning in schizophrenia. PMID:23218816

Non-Cooperative Facial Recognition Video Dataset Collection Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kimura, Marcia L.; Erikson, Rebecca L.; Lombardo, Nicholas J.

The Pacific Northwest National Laboratory (PNNL) will produce a non-cooperative (i.e. not posing for the camera) facial recognition video data set for research purposes to evaluate and enhance facial recognition systems technology. The aggregate data set consists of 1) videos capturing PNNL role players and public volunteers in three key operational settings, 2) photographs of the role players for enrolling in an evaluation database, and 3) ground truth data that documents when the role player is within various camera fields of view. PNNL will deliver the aggregate data set to DHS who may then choose to make it available tomore » other government agencies interested in evaluating and enhancing facial recognition systems. The three operational settings that will be the focus of the video collection effort include: 1) unidirectional crowd flow 2) bi-directional crowd flow, and 3) linear and/or serpentine queues.« less

Facial emotion recognition in paranoid schizophrenia and autism spectrum disorder.

PubMed

Sachse, Michael; Schlitt, Sabine; Hainz, Daniela; Ciaramidaro, Angela; Walter, Henrik; Poustka, Fritz; Bölte, Sven; Freitag, Christine M

2014-11-01

Schizophrenia (SZ) and autism spectrum disorder (ASD) share deficits in emotion processing. In order to identify convergent and divergent mechanisms, we investigated facial emotion recognition in SZ, high-functioning ASD (HFASD), and typically developed controls (TD). Different degrees of task difficulty and emotion complexity (face, eyes; basic emotions, complex emotions) were used. Two Benton tests were implemented in order to elicit potentially confounding visuo-perceptual functioning and facial processing. Nineteen participants with paranoid SZ, 22 with HFASD and 20 TD were included, aged between 14 and 33 years. Individuals with SZ were comparable to TD in all obtained emotion recognition measures, but showed reduced basic visuo-perceptual abilities. The HFASD group was impaired in the recognition of basic and complex emotions compared to both, SZ and TD. When facial identity recognition was adjusted for, group differences remained for the recognition of complex emotions only. Our results suggest that there is a SZ subgroup with predominantly paranoid symptoms that does not show problems in face processing and emotion recognition, but visuo-perceptual impairments. They also confirm the notion of a general facial and emotion recognition deficit in HFASD. No shared emotion recognition deficit was found for paranoid SZ and HFASD, emphasizing the differential cognitive underpinnings of both disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

The recognition of facial emotion expressions in Parkinson's disease.

PubMed

Assogna, Francesca; Pontieri, Francesco E; Caltagirone, Carlo; Spalletta, Gianfranco

2008-11-01

A limited number of studies in Parkinson's Disease (PD) suggest a disturbance of recognition of facial emotion expressions. In particular, disgust recognition impairment has been reported in unmedicated and medicated PD patients. However, the results are rather inconclusive in the definition of the degree and the selectivity of emotion recognition impairment, and an associated impairment of almost all basic facial emotions in PD is also described. Few studies have investigated the relationship with neuropsychiatric and neuropsychological symptoms with mainly negative results. This inconsistency may be due to many different problems, such as emotion assessment, perception deficit, cognitive impairment, behavioral symptoms, illness severity and antiparkinsonian therapy. Here we review the clinical characteristics and neural structures involved in the recognition of specific facial emotion expressions, and the plausible role of dopamine transmission and dopamine replacement therapy in these processes. It is clear that future studies should be directed to clarify all these issues.

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

PubMed Central

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a

Multi-layer sparse representation for weighted LBP-patches based facial expression recognition.

PubMed

Jia, Qi; Gao, Xinkai; Guo, He; Luo, Zhongxuan; Wang, Yi

2015-03-19

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

Facial emotion recognition ability: psychiatry nurses versus nurses from other departments.

PubMed

Gultekin, Gozde; Kincir, Zeliha; Kurt, Merve; Catal, Yasir; Acil, Asli; Aydin, Aybike; Özcan, Mualla; Delikkaya, Busra N; Kacar, Selma; Emul, Murat

2016-12-01

Facial emotion recognition is a basic element in non-verbal communication. Although some researchers have shown that recognizing facial expressions may be important in the interaction between doctors and patients, there are no studies concerning facial emotion recognition in nurses. Here, we aimed to investigate facial emotion recognition ability in nurses and compare the abilities between nurses from psychiatry and other departments. In this cross-sectional study, sixty seven nurses were divided into two groups according to their departments: psychiatry (n=31); and, other departments (n=36). A Facial Emotion Recognition Test, constructed from a set of photographs from Ekman and Friesen's book "Pictures of Facial Affect", was administered to all participants. In whole group, the highest mean accuracy rate of recognizing facial emotion was the happy (99.14%) while the lowest accurately recognized facial expression was fear (47.71%). There were no significant differences between two groups among mean accuracy rates in recognizing happy, sad, fear, angry, surprised facial emotion expressions (for all, p>0.05). The ability of recognizing disgusted and neutral facial emotions tended to be better in other nurses than psychiatry nurses (p=0.052 and p=0.053, respectively) Conclusion: This study was the first that revealed indifference in the ability of FER between psychiatry nurses and non-psychiatry nurses. In medical education curricula throughout the world, no specific training program is scheduled for recognizing emotional cues of patients. We considered that improving the ability of recognizing facial emotion expression in medical stuff might be beneficial in reducing inappropriate patient-medical stuff interaction.

Recognition of facial emotions in neuropsychiatric disorders.

PubMed

Kohler, Christian G; Turner, Travis H; Gur, Raquel E; Gur, Ruben C

2004-04-01

Recognition of facial emotions represents an important aspect of interpersonal communication and is governed by select neural substrates. We present data on emotion recognition in healthy young adults utilizing a novel set of color photographs of evoked universal emotions. In addition, we review the recent literature on emotion recognition in psychiatric and neurologic disorders, and studies that compare different disorders.

Facial recognition deficits as a potential endophenotype in bipolar disorder.

PubMed

Vierck, Esther; Porter, Richard J; Joyce, Peter R

2015-11-30

Bipolar disorder (BD) is considered a highly heritable and genetically complex disorder. Several cognitive functions, such as executive functions and verbal memory have been suggested as promising candidates for endophenotypes. Although there is evidence for deficits in facial emotion recognition in individuals with BD, studies investigating these functions as endophenotypes are rare. The current study investigates emotion recognition as a potential endophenotype in BD by comparing 36 BD participants, 24 of their 1st degree relatives and 40 healthy control participants in a computerised facial emotion recognition task. Group differences were evaluated using repeated measurement analysis of co-variance with age as a covariate. Results revealed slowed emotion recognition for both BD and their relatives. Furthermore, BD participants were less accurate than healthy controls in their recognition of emotion expressions. We found no evidence of emotion specific differences between groups. Our results provide evidence for facial recognition as a potential endophenotype in BD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Explore Efficient Local Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Wan, Jun; Guo, Guodong; Li, Stan Z

2016-08-01

Availability of handy RGB-D sensors has brought about a surge of gesture recognition research and applications. Among various approaches, one shot learning approach is advantageous because it requires minimum amount of data. Here, we provide a thorough review about one-shot learning gesture recognition from RGB-D data and propose a novel spatiotemporal feature extracted from RGB-D data, namely mixed features around sparse keypoints (MFSK). In the review, we analyze the challenges that we are facing, and point out some future research directions which may enlighten researchers in this field. The proposed MFSK feature is robust and invariant to scale, rotation and partial occlusions. To alleviate the insufficiency of one shot training samples, we augment the training samples by artificially synthesizing versions of various temporal scales, which is beneficial for coping with gestures performed at varying speed. We evaluate the proposed method on the Chalearn gesture dataset (CGD). The results show that our approach outperforms all currently published approaches on the challenging data of CGD, such as translated, scaled and occluded subsets. When applied to the RGB-D datasets that are not one-shot (e.g., the Cornell Activity Dataset-60 and MSR Daily Activity 3D dataset), the proposed feature also produces very promising results under leave-one-out cross validation or one-shot learning.

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Use of Facial Recognition Software to Identify Disaster Victims With Facial Injuries.

PubMed

Broach, John; Yong, Rothsovann; Manuell, Mary-Elise; Nichols, Constance

2017-10-01

After large-scale disasters, victim identification frequently presents a challenge and a priority for responders attempting to reunite families and ensure proper identification of deceased persons. The purpose of this investigation was to determine whether currently commercially available facial recognition software can successfully identify disaster victims with facial injuries. Photos of 106 people were taken before and after application of moulage designed to simulate traumatic facial injuries. These photos as well as photos from volunteers' personal photo collections were analyzed by using facial recognition software to determine whether this technology could accurately identify a person with facial injuries. The study results suggest that a responder could expect to get a correct match between submitted photos and photos of injured patients between 39% and 45% of the time and a much higher percentage of correct returns if submitted photos were of optimal quality with percentages correct exceeding 90% in most situations. The present results suggest that the use of this software would provide significant benefit to responders. Although a correct result was returned only 40% of the time, this would still likely represent a benefit for a responder trying to identify hundreds or thousands of victims. (Disaster Med Public Health Preparedness. 2017;11:568-572).

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Quantifying facial expression recognition across viewing conditions.

PubMed

Goren, Deborah; Wilson, Hugh R

2006-04-01

Facial expressions are key to social interactions and to assessment of potential danger in various situations. Therefore, our brains must be able to recognize facial expressions when they are transformed in biologically plausible ways. We used synthetic happy, sad, angry and fearful faces to determine the amount of geometric change required to recognize these emotions during brief presentations. Five-alternative forced choice conditions involving central viewing, peripheral viewing and inversion were used to study recognition among the four emotions. Two-alternative forced choice was used to study affect discrimination when spatial frequency information in the stimulus was modified. The results show an emotion and task-dependent pattern of detection. Facial expressions presented with low peak frequencies are much harder to discriminate from neutral than faces defined by either mid or high peak frequencies. Peripheral presentation of faces also makes recognition much more difficult, except for happy faces. Differences between fearful detection and recognition tasks are probably due to common confusions with sadness when recognizing fear from among other emotions. These findings further support the idea that these emotions are processed separately from each other.

Novel dynamic Bayesian networks for facial action element recognition and understanding

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

NASA Astrophysics Data System (ADS)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

The Role of Embodiment and Individual Empathy Levels in Gesture Comprehension.

PubMed

Jospe, Karine; Flöel, Agnes; Lavidor, Michal

2017-01-01

Research suggests that the action-observation network is involved in both emotional-embodiment (empathy) and action-embodiment (imitation) mechanisms. Here we tested whether empathy modulates action-embodiment, hypothesizing that restricting imitation abilities will impair performance in a hand gesture comprehension task. Moreover, we hypothesized that empathy levels will modulate the imitation restriction effect. One hundred twenty participants with a range of empathy scores performed gesture comprehension under restricted and unrestricted hand conditions. Empathetic participants performed better under the unrestricted compared to the restricted condition, and compared to the low empathy participants. Remarkably however, the latter showed the exactly opposite pattern and performed better under the restricted condition. This pattern was not found in a facial expression recognition task. The selective interaction of embodiment restriction and empathy suggests that empathy modulates the way people employ embodiment in gesture comprehension. We discuss the potential of embodiment-induced therapy to improve empathetic abilities in individuals with low empathy.

Slowing down Presentation of Facial Movements and Vocal Sounds Enhances Facial Expression Recognition and Induces Facial-Vocal Imitation in Children with Autism

ERIC Educational Resources Information Center

Tardif, Carole; Laine, France; Rodriguez, Melissa; Gepner, Bruno

2007-01-01

This study examined the effects of slowing down presentation of facial expressions and their corresponding vocal sounds on facial expression recognition and facial and/or vocal imitation in children with autism. Twelve autistic children and twenty-four normal control children were presented with emotional and non-emotional facial expressions on…

Mapping correspondence between facial mimicry and emotion recognition in healthy subjects.

PubMed

Ponari, Marta; Conson, Massimiliano; D'Amico, Nunzia Pina; Grossi, Dario; Trojano, Luigi

2012-12-01

We aimed at verifying the hypothesis that facial mimicry is causally and selectively involved in emotion recognition. For this purpose, in Experiment 1, we explored the effect of tonic contraction of muscles in upper or lower half of participants' face on their ability to recognize emotional facial expressions. We found that the "lower" manipulation specifically impaired recognition of happiness and disgust, the "upper" manipulation impaired recognition of anger, while both manipulations affected recognition of fear; recognition of surprise and sadness were not affected by either blocking manipulations. In Experiment 2, we verified whether emotion recognition is hampered by stimuli in which an upper or lower half-face showing an emotional expression is combined with a neutral half-face. We found that the neutral lower half-face interfered with recognition of happiness and disgust, whereas the neutral upper half impaired recognition of anger; recognition of fear and sadness was impaired by both manipulations, whereas recognition of surprise was not affected by either manipulation. Taken together, the present findings support simulation models of emotion recognition and provide insight into the role of mimicry in comprehension of others' emotional facial expressions. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Emotional facial recognition in proactive and reactive violent offenders.

PubMed

Philipp-Wiegmann, Florence; Rösler, Michael; Retz-Junginger, Petra; Retz, Wolfgang

2017-10-01

The purpose of this study is to analyse individual differences in the ability of emotional facial recognition in violent offenders, who were characterised as either reactive or proactive in relation to their offending. In accordance with findings of our previous study, we expected higher impairments in facial recognition in reactive than proactive violent offenders. To assess the ability to recognize facial expressions, the computer-based Facial Emotional Expression Labeling Test (FEEL) was performed. Group allocation of reactive und proactive violent offenders and assessment of psychopathic traits were performed by an independent forensic expert using rating scales (PROREA, PCL-SV). Compared to proactive violent offenders and controls, the performance of emotion recognition in the reactive offender group was significantly lower, both in total and especially in recognition of negative emotions such as anxiety (d = -1.29), sadness (d = -1.54), and disgust (d = -1.11). Furthermore, reactive violent offenders showed a tendency to interpret non-anger emotions as anger. In contrast, proactive violent offenders performed as well as controls. General and specific deficits in reactive violent offenders are in line with the results of our previous study and correspond to predictions of the Integrated Emotion System (IES, 7) and the hostile attribution processes (21). Due to the different error pattern in the FEEL test, the theoretical distinction between proactive and reactive aggression can be supported based on emotion recognition, even though aggression itself is always a heterogeneous act rather than a distinct one-dimensional concept.

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

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

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

Pose-variant facial expression recognition using an embedded image system

NASA Astrophysics Data System (ADS)

Song, Kai-Tai; Han, Meng-Ju; Chang, Shuo-Hung

2008-12-01

In recent years, one of the most attractive research areas in human-robot interaction is automated facial expression recognition. Through recognizing the facial expression, a pet robot can interact with human in a more natural manner. In this study, we focus on the facial pose-variant problem. A novel method is proposed in this paper to recognize pose-variant facial expressions. After locating the face position in an image frame, the active appearance model (AAM) is applied to track facial features. Fourteen feature points are extracted to represent the variation of facial expressions. The distance between feature points are defined as the feature values. These feature values are sent to a support vector machine (SVM) for facial expression determination. The pose-variant facial expression is classified into happiness, neutral, sadness, surprise or anger. Furthermore, in order to evaluate the performance for practical applications, this study also built a low resolution database (160x120 pixels) using a CMOS image sensor. Experimental results show that the recognition rate is 84% with the self-built database.

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

Facial recognition using simulated prosthetic pixelized vision.

PubMed

Thompson, Robert W; Barnett, G David; Humayun, Mark S; Dagnelie, Gislin

2003-11-01

To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those faces viewed through a square pixelizing grid that contained 10x10 to 32x32 dots separated by gaps. The grid size, dot size, gap width, dot dropout rate, and gray-scale resolution were varied separately about a standard test condition, for a total of 16 conditions. All tests were first performed at 99% contrast and then repeated at 12.5% contrast. Discrimination speed and performance were influenced by all stimulus parameters. The subjects achieved highly significant facial recognition accuracy for all high-contrast tests except for grids with 70% random dot dropout and two gray levels. In low-contrast tests, significant facial recognition accuracy was achieved for all but the most adverse grid parameters: total grid area less than 17% of the target image, 70% dropout, four or fewer gray levels, and a gap of 40.5 arcmin. For difficult test conditions, a pronounced learning effect was noticed during high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials. These findings suggest that reliable face recognition with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis.

Intelligent Facial Recognition Systems: Technology advancements for security applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, C.L.

1993-07-01

Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g.,more » fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.« less

Accuracy of computer-assisted navigation: significant augmentation by facial recognition software.

PubMed

Glicksman, Jordan T; Reger, Christine; Parasher, Arjun K; Kennedy, David W

2017-09-01

Over the past 20 years, image guidance navigation has been used with increasing frequency as an adjunct during sinus and skull base surgery. These devices commonly utilize surface registration, where varying pressure of the registration probe and loss of contact with the face during the skin tracing process can lead to registration inaccuracies, and the number of registration points incorporated is necessarily limited. The aim of this study was to evaluate the use of novel facial recognition software for image guidance registration. Consecutive adults undergoing endoscopic sinus surgery (ESS) were prospectively studied. Patients underwent image guidance registration via both conventional surface registration and facial recognition software. The accuracy of both registration processes were measured at the head of the middle turbinate (MTH), middle turbinate axilla (MTA), anterior wall of sphenoid sinus (SS), and nasal tip (NT). Forty-five patients were included in this investigation. Facial recognition was accurate to within a mean of 0.47 mm at the MTH, 0.33 mm at the MTA, 0.39 mm at the SS, and 0.36 mm at the NT. Facial recognition was more accurate than surface registration at the MTH by an average of 0.43 mm (p = 0.002), at the MTA by an average of 0.44 mm (p < 0.001), and at the SS by an average of 0.40 mm (p < 0.001). The integration of facial recognition software did not adversely affect registration time. In this prospective study, automated facial recognition software significantly improved the accuracy of image guidance registration when compared to conventional surface registration. © 2017 ARS-AAOA, LLC.

Impaired recognition of facial emotions from low-spatial frequencies in Asperger syndrome.

PubMed

Kätsyri, Jari; Saalasti, Satu; Tiippana, Kaisa; von Wendt, Lennart; Sams, Mikko

2008-01-01

The theory of 'weak central coherence' [Happe, F., & Frith, U. (2006). The weak coherence account: Detail-focused cognitive style in autism spectrum disorders. Journal of Autism and Developmental Disorders, 36(1), 5-25] implies that persons with autism spectrum disorders (ASDs) have a perceptual bias for local but not for global stimulus features. The recognition of emotional facial expressions representing various different levels of detail has not been studied previously in ASDs. We analyzed the recognition of four basic emotional facial expressions (anger, disgust, fear and happiness) from low-spatial frequencies (overall global shapes without local features) in adults with an ASD. A group of 20 participants with Asperger syndrome (AS) was compared to a group of non-autistic age- and sex-matched controls. Emotion recognition was tested from static and dynamic facial expressions whose spatial frequency contents had been manipulated by low-pass filtering at two levels. The two groups recognized emotions similarly from non-filtered faces and from dynamic vs. static facial expressions. In contrast, the participants with AS were less accurate than controls in recognizing facial emotions from very low-spatial frequencies. The results suggest intact recognition of basic facial emotions and dynamic facial information, but impaired visual processing of global features in ASDs.

Relative preservation of the recognition of positive facial expression "happiness" in Alzheimer disease.

PubMed

Maki, Yohko; Yoshida, Hiroshi; Yamaguchi, Tomoharu; Yamaguchi, Haruyasu

2013-01-01

Positivity recognition bias has been reported for facial expression as well as memory and visual stimuli in aged individuals, whereas emotional facial recognition in Alzheimer disease (AD) patients is controversial, with possible involvement of confounding factors such as deficits in spatial processing of non-emotional facial features and in verbal processing to express emotions. Thus, we examined whether recognition of positive facial expressions was preserved in AD patients, by adapting a new method that eliminated the influences of these confounding factors. Sensitivity of six basic facial expressions (happiness, sadness, surprise, anger, disgust, and fear) was evaluated in 12 outpatients with mild AD, 17 aged normal controls (ANC), and 25 young normal controls (YNC). To eliminate the factors related to non-emotional facial features, averaged faces were prepared as stimuli. To eliminate the factors related to verbal processing, the participants were required to match the images of stimulus and answer, avoiding the use of verbal labels. In recognition of happiness, there was no difference in sensitivity between YNC and ANC, and between ANC and AD patients. AD patients were less sensitive than ANC in recognition of sadness, surprise, and anger. ANC were less sensitive than YNC in recognition of surprise, anger, and disgust. Within the AD patient group, sensitivity of happiness was significantly higher than those of the other five expressions. In AD patient, recognition of happiness was relatively preserved; recognition of happiness was most sensitive and was preserved against the influences of age and disease.

Neuroanatomical substrates involved in unrelated false facial recognition.

PubMed

Ronzon-Gonzalez, Eliane; Hernandez-Castillo, Carlos R; Pasaye, Erick H; Vaca-Palomares, Israel; Fernandez-Ruiz, Juan

2017-11-22

Identifying faces is a process central for social interaction and a relevant factor in eyewitness theory. False recognition is a critical mistake during an eyewitness's identification scenario because it can lead to a wrongful conviction. Previous studies have described neural areas related to false facial recognition using the standard Deese/Roediger-McDermott (DRM) paradigm, triggering related false recognition. Nonetheless, misidentification of faces without trying to elicit false memories (unrelated false recognition) in a police lineup could involve different cognitive processes, and distinct neural areas. To delve into the neural circuitry of unrelated false recognition, we evaluated the memory and response confidence of participants while watching faces photographs in an fMRI task. Functional activations of unrelated false recognition were identified by contrasting the activation on this condition vs. the activations related to recognition (hits) and correct rejections. The results identified the right precentral and cingulate gyri as areas with distinctive activations during false recognition events suggesting a conflict resulting in a dysfunction during memory retrieval. High confidence suggested that about 50% of misidentifications may be related to an unconscious process. These findings add to our understanding of the construction of facial memories and its biological basis, and the fallibility of the eyewitness testimony.

Stability of facial emotion recognition performance in bipolar disorder.

PubMed

Martino, Diego J; Samamé, Cecilia; Strejilevich, Sergio A

2016-09-30

The aim of this study was to assess the performance in emotional processing over time in a sample of euthymic patients with bipolar disorder (BD). Performance in the facial recognition of the six basic emotions (surprise, anger, sadness, happiness, disgust, and fear) did not change during a follow-up period of almost 7 years. These preliminary results suggest that performance in facial emotion recognition might be stable over time in BD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Perceptual and affective mechanisms in facial expression recognition: An integrative review.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2016-09-01

Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser's internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with "emotionless" computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms.

The association between PTSD and facial affect recognition.

PubMed

Williams, Christian L; Milanak, Melissa E; Judah, Matt R; Berenbaum, Howard

2018-05-05

The major aims of this study were to examine how, if at all, having higher levels of PTSD would be associated with performance on a facial affect recognition task in which facial expressions of emotion are superimposed on emotionally valenced, non-face images. College students with trauma histories (N = 90) completed a facial affect recognition task as well as measures of exposure to traumatic events, and PTSD symptoms. When the face and context matched, participants with higher levels of PTSD were significantly more accurate. When the face and context were mismatched, participants with lower levels of PTSD were more accurate than were those with higher levels of PTSD. These findings suggest that PTSD is associated with how people process affective information. Furthermore, these results suggest that the enhanced attention of people with higher levels of PTSD to affective information can be either beneficial or detrimental to their ability to accurately identify facial expressions of emotion. Limitations, future directions and clinical implications are discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Hybrid generative-discriminative approach to age-invariant face recognition

NASA Astrophysics Data System (ADS)

Sajid, Muhammad; Shafique, Tamoor

2018-03-01

Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

Temporal lobe structures and facial emotion recognition in schizophrenia patients and nonpsychotic relatives.

PubMed

Goghari, Vina M; Macdonald, Angus W; Sponheim, Scott R

2011-11-01

Temporal lobe abnormalities and emotion recognition deficits are prominent features of schizophrenia and appear related to the diathesis of the disorder. This study investigated whether temporal lobe structural abnormalities were associated with facial emotion recognition deficits in schizophrenia and related to genetic liability for the disorder. Twenty-seven schizophrenia patients, 23 biological family members, and 36 controls participated. Several temporal lobe regions (fusiform, superior temporal, middle temporal, amygdala, and hippocampus) previously associated with face recognition in normative samples and found to be abnormal in schizophrenia were evaluated using volumetric analyses. Participants completed a facial emotion recognition task and an age recognition control task under time-limited and self-paced conditions. Temporal lobe volumes were tested for associations with task performance. Group status explained 23% of the variance in temporal lobe volume. Left fusiform gray matter volume was decreased by 11% in patients and 7% in relatives compared with controls. Schizophrenia patients additionally exhibited smaller hippocampal and middle temporal volumes. Patients were unable to improve facial emotion recognition performance with unlimited time to make a judgment but were able to improve age recognition performance. Patients additionally showed a relationship between reduced temporal lobe gray matter and poor facial emotion recognition. For the middle temporal lobe region, the relationship between greater volume and better task performance was specific to facial emotion recognition and not age recognition. Because schizophrenia patients exhibited a specific deficit in emotion recognition not attributable to a generalized impairment in face perception, impaired emotion recognition may serve as a target for interventions.

Facial Recognition in a Group-Living Cichlid Fish.

PubMed

Kohda, Masanori; Jordan, Lyndon Alexander; Hotta, Takashi; Kosaka, Naoya; Karino, Kenji; Tanaka, Hirokazu; Taniyama, Masami; Takeyama, Tomohiro

2015-01-01

The theoretical underpinnings of the mechanisms of sociality, e.g. territoriality, hierarchy, and reciprocity, are based on assumptions of individual recognition. While behavioural evidence suggests individual recognition is widespread, the cues that animals use to recognise individuals are established in only a handful of systems. Here, we use digital models to demonstrate that facial features are the visual cue used for individual recognition in the social fish Neolamprologus pulcher. Focal fish were exposed to digital images showing four different combinations of familiar and unfamiliar face and body colorations. Focal fish attended to digital models with unfamiliar faces longer and from a further distance to the model than to models with familiar faces. These results strongly suggest that fish can distinguish individuals accurately using facial colour patterns. Our observations also suggest that fish are able to rapidly (≤ 0.5 sec) discriminate between familiar and unfamiliar individuals, a speed of recognition comparable to primates including humans.

Sex differences in facial emotion recognition across varying expression intensity levels from videos.

PubMed

Wingenbach, Tanja S H; Ashwin, Chris; Brosnan, Mark

2018-01-01

There has been much research on sex differences in the ability to recognise facial expressions of emotions, with results generally showing a female advantage in reading emotional expressions from the face. However, most of the research to date has used static images and/or 'extreme' examples of facial expressions. Therefore, little is known about how expression intensity and dynamic stimuli might affect the commonly reported female advantage in facial emotion recognition. The current study investigated sex differences in accuracy of response (Hu; unbiased hit rates) and response latencies for emotion recognition using short video stimuli (1sec) of 10 different facial emotion expressions (anger, disgust, fear, sadness, surprise, happiness, contempt, pride, embarrassment, neutral) across three variations in the intensity of the emotional expression (low, intermediate, high) in an adolescent and adult sample (N = 111; 51 male, 60 female) aged between 16 and 45 (M = 22.2, SD = 5.7). Overall, females showed more accurate facial emotion recognition compared to males and were faster in correctly recognising facial emotions. The female advantage in reading expressions from the faces of others was unaffected by expression intensity levels and emotion categories used in the study. The effects were specific to recognition of emotions, as males and females did not differ in the recognition of neutral faces. Together, the results showed a robust sex difference favouring females in facial emotion recognition using video stimuli of a wide range of emotions and expression intensity variations.

Sex differences in facial emotion recognition across varying expression intensity levels from videos

PubMed Central

2018-01-01

There has been much research on sex differences in the ability to recognise facial expressions of emotions, with results generally showing a female advantage in reading emotional expressions from the face. However, most of the research to date has used static images and/or ‘extreme’ examples of facial expressions. Therefore, little is known about how expression intensity and dynamic stimuli might affect the commonly reported female advantage in facial emotion recognition. The current study investigated sex differences in accuracy of response (Hu; unbiased hit rates) and response latencies for emotion recognition using short video stimuli (1sec) of 10 different facial emotion expressions (anger, disgust, fear, sadness, surprise, happiness, contempt, pride, embarrassment, neutral) across three variations in the intensity of the emotional expression (low, intermediate, high) in an adolescent and adult sample (N = 111; 51 male, 60 female) aged between 16 and 45 (M = 22.2, SD = 5.7). Overall, females showed more accurate facial emotion recognition compared to males and were faster in correctly recognising facial emotions. The female advantage in reading expressions from the faces of others was unaffected by expression intensity levels and emotion categories used in the study. The effects were specific to recognition of emotions, as males and females did not differ in the recognition of neutral faces. Together, the results showed a robust sex difference favouring females in facial emotion recognition using video stimuli of a wide range of emotions and expression intensity variations. PMID:29293674

Facial recognition in primary focal dystonia.

PubMed

Rinnerthaler, Martina; Benecke, Cord; Bartha, Lisa; Entner, Tanja; Poewe, Werner; Mueller, Joerg

2006-01-01

The basal ganglia seem to be involved in emotional processing. Primary dystonia is a movement disorder considered to result from basal ganglia dysfunction, and the aim of the present study was to investigate emotion recognition in patients with primary focal dystonia. Thirty-two patients with primary cranial (n=12) and cervical (n=20) dystonia were compared to 32 healthy controls matched for age, sex, and educational level on the facially expressed emotion labeling (FEEL) test, a computer-based tool measuring a person's ability to recognize facially expressed emotions. Patients with cognitive impairment or depression were excluded. None of the patients received medication with a possible cognitive side effect profile and only those with mild to moderate dystonia were included. Patients with primary dystonia showed isolated deficits in the recognition of disgust (P=0.007), while no differences between patients and controls were found with regard to the other emotions (fear, happiness, surprise, sadness, and anger). The findings of the present study add further evidence to the conception that dystonia is not only a motor but a complex basal ganglia disorder including selective emotion recognition disturbances. Copyright (c) 2005 Movement Disorder Society.

Intact anger recognition in depression despite aberrant visual facial information usage.

PubMed

Clark, Cameron M; Chiu, Carina G; Diaz, Ruth L; Goghari, Vina M

2014-08-01

Previous literature has indicated abnormalities in facial emotion recognition abilities, as well as deficits in basic visual processes in major depression. However, the literature is unclear on a number of important factors including whether or not these abnormalities represent deficient or enhanced emotion recognition abilities compared to control populations, and the degree to which basic visual deficits might impact this process. The present study investigated emotion recognition abilities for angry versus neutral facial expressions in a sample of undergraduate students with Beck Depression Inventory-II (BDI-II) scores indicative of moderate depression (i.e., ≥20), compared to matched low-BDI-II score (i.e., ≤2) controls via the Bubbles Facial Emotion Perception Task. Results indicated unimpaired behavioural performance in discriminating angry from neutral expressions in the high depressive symptoms group relative to the minimal depressive symptoms group, despite evidence of an abnormal pattern of visual facial information usage. The generalizability of the current findings is limited by the highly structured nature of the facial emotion recognition task used, as well as the use of an analog sample undergraduates scoring high in self-rated symptoms of depression rather than a clinical sample. Our findings suggest that basic visual processes are involved in emotion recognition abnormalities in depression, demonstrating consistency with the emotion recognition literature in other psychopathologies (e.g., schizophrenia, autism, social anxiety). Future research should seek to replicate these findings in clinical populations with major depression, and assess the association between aberrant face gaze behaviours and symptom severity and social functioning. Copyright © 2014 Elsevier B.V. All rights reserved.

Recognition of face identity and emotion in expressive specific language impairment.

PubMed

Merkenschlager, A; Amorosa, H; Kiefl, H; Martinius, J

2012-01-01

To study face and emotion recognition in children with mostly expressive specific language impairment (SLI-E). A test movie to study perception and recognition of faces and mimic-gestural expression was applied to 24 children diagnosed as suffering from SLI-E and an age-matched control group of normally developing children. Compared to a normal control group, the SLI-E children scored significantly worse in both the face and expression recognition tasks with a preponderant effect on emotion recognition. The performance of the SLI-E group could not be explained by reduced attention during the test session. We conclude that SLI-E is associated with a deficiency in decoding non-verbal emotional facial and gestural information, which might lead to profound and persistent problems in social interaction and development. Copyright © 2012 S. Karger AG, Basel.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Recognition of computerized facial approximations by familiar assessors.

PubMed

Richard, Adam H; Monson, Keith L

2017-11-01

Studies testing the effectiveness of facial approximations typically involve groups of participants who are unfamiliar with the approximated individual(s). This limitation requires the use of photograph arrays including a picture of the subject for comparison to the facial approximation. While this practice is often necessary due to the difficulty in obtaining a group of assessors who are familiar with the approximated subject, it may not accurately simulate the thought process of the target audience (friends and family members) in comparing a mental image of the approximated subject to the facial approximation. As part of a larger process to evaluate the effectiveness and best implementation of the ReFace facial approximation software program, the rare opportunity arose to conduct a recognition study using assessors who were personally acquainted with the subjects of the approximations. ReFace facial approximations were generated based on preexisting medical scans, and co-workers of the scan donors were tested on whether they could accurately pick out the approximation of their colleague from arrays of facial approximations. Results from the study demonstrated an overall poor recognition performance (i.e., where a single choice within a pool is not enforced) for individuals who were familiar with the approximated subjects. Out of 220 recognition tests only 10.5% resulted in the assessor selecting the correct approximation (or correctly choosing not to make a selection when the array consisted only of foils), an outcome that was not significantly different from the 9% random chance rate. When allowed to select multiple approximations the assessors felt resembled the target individual, the overall sensitivity for ReFace approximations was 16.0% and the overall specificity was 81.8%. These results differ markedly from the results of a previous study using assessors who were unfamiliar with the approximated subjects. Some possible explanations for this disparity in

Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

PubMed

Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

2014-02-01

Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A Comparative Study

DTIC Science & Technology

2006-01-01

Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A Comparative Study ∗ Andrea Selinger† Diego A. Socolinsky‡ †Equinox...TYPE 3. DATES COVERED 00-00-2006 to 00-00-2006 4. TITLE AND SUBTITLE Appearance-Based Facial Recognition Using Visible and Thermal Imagery: A

Gesture-controlled interfaces for self-service machines and other applications

NASA Technical Reports Server (NTRS)

Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)

2004-01-01

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.

Violent Media Consumption and the Recognition of Dynamic Facial Expressions

ERIC Educational Resources Information Center

Kirsh, Steven J.; Mounts, Jeffrey R. W.; Olczak, Paul V.

2006-01-01

This study assessed the speed of recognition of facial emotional expressions (happy and angry) as a function of violent media consumption. Color photos of calm facial expressions morphed to either an angry or a happy facial expression. Participants were asked to make a speeded identification of the emotion (happiness or anger) during the morph.…

The Differential Effects of Thalamus and Basal Ganglia on Facial Emotion Recognition

ERIC Educational Resources Information Center

Cheung, Crystal C. Y.; Lee, Tatia M. C.; Yip, James T. H.; King, Kristin E.; Li, Leonard S. W.

2006-01-01

This study examined if subcortical stroke was associated with impaired facial emotion recognition. Furthermore, the lateralization of the impairment and the differential profiles of facial emotion recognition deficits with localized thalamic or basal ganglia damage were also studied. Thirty-eight patients with subcortical strokes and 19 matched…

The Chinese Facial Emotion Recognition Database (CFERD): a computer-generated 3-D paradigm to measure the recognition of facial emotional expressions at different intensities.

PubMed

Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2012-12-30

The Chinese Facial Emotion Recognition Database (CFERD), a computer-generated three-dimensional (3D) paradigm, was developed to measure the recognition of facial emotional expressions at different intensities. The stimuli consisted of 3D colour photographic images of six basic facial emotional expressions (happiness, sadness, disgust, fear, anger and surprise) and neutral faces of the Chinese. The purpose of the present study is to describe the development and validation of CFERD with nonclinical healthy participants (N=100; 50 men; age ranging between 18 and 50 years), and to generate normative data set. The results showed that the sensitivity index d' [d'=Z(hit rate)-Z(false alarm rate), where function Z(p), p∈[0,1

Age, gender, and puberty influence the development of facial emotion recognition.

PubMed

Lawrence, Kate; Campbell, Ruth; Skuse, David

2015-01-01

Our ability to differentiate between simple facial expressions of emotion develops between infancy and early adulthood, yet few studies have explored the developmental trajectory of emotion recognition using a single methodology across a wide age-range. We investigated the development of emotion recognition abilities through childhood and adolescence, testing the hypothesis that children's ability to recognize simple emotions is modulated by chronological age, pubertal stage and gender. In order to establish norms, we assessed 478 children aged 6-16 years, using the Ekman-Friesen Pictures of Facial Affect. We then modeled these cross-sectional data in terms of competence in accurate recognition of the six emotions studied, when the positive correlation between emotion recognition and IQ was controlled. Significant linear trends were seen in children's ability to recognize facial expressions of happiness, surprise, fear, and disgust; there was improvement with increasing age. In contrast, for sad and angry expressions there is little or no change in accuracy over the age range 6-16 years; near-adult levels of competence are established by middle-childhood. In a sampled subset, pubertal status influenced the ability to recognize facial expressions of disgust and anger; there was an increase in competence from mid to late puberty, which occurred independently of age. A small female advantage was found in the recognition of some facial expressions. The normative data provided in this study will aid clinicians and researchers in assessing the emotion recognition abilities of children and will facilitate the identification of abnormalities in a skill that is often impaired in neurodevelopmental disorders. If emotion recognition abilities are a good model with which to understand adolescent development, then these results could have implications for the education, mental health provision and legal treatment of teenagers.

Age, gender, and puberty influence the development of facial emotion recognition

PubMed Central

Lawrence, Kate; Campbell, Ruth; Skuse, David

2015-01-01

Our ability to differentiate between simple facial expressions of emotion develops between infancy and early adulthood, yet few studies have explored the developmental trajectory of emotion recognition using a single methodology across a wide age-range. We investigated the development of emotion recognition abilities through childhood and adolescence, testing the hypothesis that children’s ability to recognize simple emotions is modulated by chronological age, pubertal stage and gender. In order to establish norms, we assessed 478 children aged 6–16 years, using the Ekman-Friesen Pictures of Facial Affect. We then modeled these cross-sectional data in terms of competence in accurate recognition of the six emotions studied, when the positive correlation between emotion recognition and IQ was controlled. Significant linear trends were seen in children’s ability to recognize facial expressions of happiness, surprise, fear, and disgust; there was improvement with increasing age. In contrast, for sad and angry expressions there is little or no change in accuracy over the age range 6–16 years; near-adult levels of competence are established by middle-childhood. In a sampled subset, pubertal status influenced the ability to recognize facial expressions of disgust and anger; there was an increase in competence from mid to late puberty, which occurred independently of age. A small female advantage was found in the recognition of some facial expressions. The normative data provided in this study will aid clinicians and researchers in assessing the emotion recognition abilities of children and will facilitate the identification of abnormalities in a skill that is often impaired in neurodevelopmental disorders. If emotion recognition abilities are a good model with which to understand adolescent development, then these results could have implications for the education, mental health provision and legal treatment of teenagers. PMID:26136697

A Neural Basis of Facial Action Recognition in Humans

PubMed Central

Srinivasan, Ramprakash; Golomb, Julie D.

2016-01-01

By combining different facial muscle actions, called action units, humans can produce an extraordinarily large number of facial expressions. Computational models and studies in cognitive science and social psychology have long hypothesized that the brain needs to visually interpret these action units to understand other people's actions and intentions. Surprisingly, no studies have identified the neural basis of the visual recognition of these action units. Here, using functional magnetic resonance imaging and an innovative machine learning analysis approach, we identify a consistent and differential coding of action units in the brain. Crucially, in a brain region thought to be responsible for the processing of changeable aspects of the face, multivoxel pattern analysis could decode the presence of specific action units in an image. This coding was found to be consistent across people, facilitating the estimation of the perceived action units on participants not used to train the multivoxel decoder. Furthermore, this coding of action units was identified when participants attended to the emotion category of the facial expression, suggesting an interaction between the visual analysis of action units and emotion categorization as predicted by the computational models mentioned above. These results provide the first evidence for a representation of action units in the brain and suggest a mechanism for the analysis of large numbers of facial actions and a loss of this capacity in psychopathologies. SIGNIFICANCE STATEMENT Computational models and studies in cognitive and social psychology propound that visual recognition of facial expressions requires an intermediate step to identify visible facial changes caused by the movement of specific facial muscles. Because facial expressions are indeed created by moving one's facial muscles, it is logical to assume that our visual system solves this inverse problem. Here, using an innovative machine learning method and

Glucose enhancement of a facial recognition task in young adults.

PubMed

Metzger, M M

2000-02-01

Numerous studies have reported that glucose administration enhances memory processes in both elderly and young adult subjects. Although these studies have utilized a variety of procedures and paradigms, investigations of both young and elderly subjects have typically used verbal tasks (word list recall, paragraph recall, etc.). In the present study, the effect of glucose consumption on a nonverbal, facial recognition task in young adults was examined. Lemonade sweetened with either glucose (50 g) or saccharin (23.7 mg) was consumed by college students (mean age of 21.1 years) 15 min prior to a facial recognition task. The task consisted of a familiarization phase in which subjects were presented with "target" faces, followed immediately by a recognition phase in which subjects had to identify the targets among a random array of familiar target and novel "distractor" faces. Statistical analysis indicated that there were no differences on hit rate (target identification) for subjects who consumed either saccharin or glucose prior to the test. However, further analyses revealed that subjects who consumed glucose committed significantly fewer false alarms and had (marginally) higher d-prime scores (a signal detection measure) compared to subjects who consumed saccharin prior to the test. These results parallel a previous report demonstrating glucose enhancement of a facial recognition task in probable Alzheimer's patients; however, this is believed to be the first demonstration of glucose enhancement for a facial recognition task in healthy, young adults.

Face to face: blocking facial mimicry can selectively impair recognition of emotional expressions.

PubMed

Oberman, Lindsay M; Winkielman, Piotr; Ramachandran, Vilayanur S

2007-01-01

People spontaneously mimic a variety of behaviors, including emotional facial expressions. Embodied cognition theories suggest that mimicry reflects internal simulation of perceived emotion in order to facilitate its understanding. If so, blocking facial mimicry should impair recognition of expressions, especially of emotions that are simulated using facial musculature. The current research tested this hypothesis using four expressions (happy, disgust, fear, and sad) and two mimicry-interfering manipulations (1) biting on a pen and (2) chewing gum, as well as two control conditions. Experiment 1 used electromyography over cheek, mouth, and nose regions. The bite manipulation consistently activated assessed muscles, whereas the chew manipulation activated muscles only intermittently. Further, expressing happiness generated most facial action. Experiment 2 found that the bite manipulation interfered most with recognition of happiness. These findings suggest that facial mimicry differentially contributes to recognition of specific facial expressions, thus allowing for more refined predictions from embodied cognition theories.

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

PubMed Central

Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

2013-01-01

Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

The Relationships among Facial Emotion Recognition, Social Skills, and Quality of Life.

ERIC Educational Resources Information Center

Simon, Elliott W.; And Others

1995-01-01

Forty-six institutionalized adults with mild or moderate mental retardation were administered the Vineland Adaptive Behavior Scales (socialization domain), a subjective measure of quality of life, and a facial emotion recognition test. Facial emotion recognition, quality of life, and social skills appeared to be independent of one another. Facial…

Specific Impairments in the Recognition of Emotional Facial Expressions in Parkinson’s Disease

PubMed Central

Clark, Uraina S.; Neargarder, Sandy; Cronin-Golomb, Alice

2008-01-01

Studies investigating the ability to recognize emotional facial expressions in non-demented individuals with Parkinson’s disease (PD) have yielded equivocal findings. A possible reason for this variability may lie in the confounding of emotion recognition with cognitive task requirements, a confound arising from the lack of a control condition using non-emotional stimuli. The present study examined emotional facial expression recognition abilities in 20 non-demented patients with PD and 23 control participants relative to their performances on a non-emotional landscape categorization test with comparable task requirements. We found that PD participants were normal on the control task but exhibited selective impairments in the recognition of facial emotion, specifically for anger (driven by those with right hemisphere pathology) and surprise (driven by those with left hemisphere pathology), even when controlling for depression level. Male but not female PD participants further displayed specific deficits in the recognition of fearful expressions. We suggest that the neural substrates that may subserve these impairments include the ventral striatum, amygdala, and prefrontal cortices. Finally, we observed that in PD participants, deficiencies in facial emotion recognition correlated with higher levels of interpersonal distress, which calls attention to the significant psychosocial impact that facial emotion recognition impairments may have on individuals with PD. PMID:18485422

[Impact of facial emotional recognition alterations in Dementia of the Alzheimer type].

PubMed

Rubinstein, Wanda; Cossini, Florencia; Politis, Daniel

2016-07-01

Face recognition of basic emotions is independent of other deficits in dementia of the Alzheimer type. Among these deficits, there is disagreement about what emotions are more difficult to recognize. Our aim was to study the presence of alterations in the process of facial recognition of basic emotions, and to investigate if there were differences in the recognition of each type of emotion in Alzheimer's disease. With three tests of recognition of basic facial emotions we evaluated 29 patients who had been diagnosed with dementia of the Alzheimer type and 18 control subjects. Significant differences were obtained in tests of recognition of basic facial emotions and between each. Since the amygdala, one of the brain structures responsible for emotional reaction, is affected in the early stages of this disease, our findings become relevant to understand how this alteration of the process of emotional recognition impacts the difficulties these patients have in both interpersonal relations and behavioral disorders.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

In what sense 'familiar'? Examining experiential differences within pathologies of facial recognition.

PubMed

Young, Garry

2009-09-01

Explanations of Capgras delusion and prosopagnosia typically incorporate a dual-route approach to facial recognition in which a deficit in overt or covert processing in one condition is mirror-reversed in the other. Despite this double dissociation, experiences of either patient-group are often reported in the same way--as lacking a sense of familiarity toward familiar faces. In this paper, deficits in the facial processing of these patients are compared to other facial recognition pathologies, and their experiential characteristics mapped onto the dual-route model in order to provide a less ambiguous link between facial processing and experiential content. The paper concludes that the experiential states of Capgras delusion, prosopagnosia, and related facial pathologies are quite distinct, and that this descriptive distinctiveness finds explanatory equivalence at the level of anatomical and functional disruption within the face recognition system. The role of skin conductance response (SCR) as a measure of 'familiarity' is also clarified.

Impaired Facial Expression Recognition in Children with Temporal Lobe Epilepsy: Impact of Early Seizure Onset on Fear Recognition

ERIC Educational Resources Information Center

Golouboff, Nathalie; Fiori, Nicole; Delalande, Olivier; Fohlen, Martine; Dellatolas, Georges; Jambaque, Isabelle

2008-01-01

The amygdala has been implicated in the recognition of facial emotions, especially fearful expressions, in adults with early-onset right temporal lobe epilepsy (TLE). The present study investigates the recognition of facial emotions in children and adolescents, 8-16 years old, with epilepsy. Twenty-nine subjects had TLE (13 right, 16 left) and…

Facial recognition performance of female inmates as a result of sexual assault history.

PubMed

Islam-Zwart, Kayleen A; Heath, Nicole M; Vik, Peter W

2005-06-01

This study examined the effect of sexual assault history on facial recognition performance. Gender of facial stimuli and posttraumatic stress disorder (PTSD) symptoms also were expected to influence performance. Fifty-six female inmates completed an interview and the Wechsler Memory Scale-Third Edition Faces I and Faces II subtests (Wechsler, 1997). Women with a sexual assault exhibited better immediate and delayed facial recognition skills than those with no assault history. There were no differences in performance based on the gender of faces or PTSD diagnosis. Immediate facial recognition was correlated with report of PTSD symptoms. Findings provide greater insight into women's reactions to, and the uniqueness of, the trauma of sexual victimization.

Facial Expression Recognition Deficits and Faulty Learning: Implications for Theoretical Models and Clinical Applications

ERIC Educational Resources Information Center

Sheaffer, Beverly L.; Golden, Jeannie A.; Averett, Paige

2009-01-01

The ability to recognize facial expressions of emotion is integral in social interaction. Although the importance of facial expression recognition is reflected in increased research interest as well as in popular culture, clinicians may know little about this topic. The purpose of this article is to discuss facial expression recognition literature…

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Expression intensity, gender and facial emotion recognition: Women recognize only subtle facial emotions better than men.

PubMed

Hoffmann, Holger; Kessler, Henrik; Eppel, Tobias; Rukavina, Stefanie; Traue, Harald C

2010-11-01

Two experiments were conducted in order to investigate the effect of expression intensity on gender differences in the recognition of facial emotions. The first experiment compared recognition accuracy between female and male participants when emotional faces were shown with full-blown (100% emotional content) or subtle expressiveness (50%). In a second experiment more finely grained analyses were applied in order to measure recognition accuracy as a function of expression intensity (40%-100%). The results show that although women were more accurate than men in recognizing subtle facial displays of emotion, there was no difference between male and female participants when recognizing highly expressive stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

Facial expressions recognition with an emotion expressive robotic head

NASA Astrophysics Data System (ADS)

Doroftei, I.; Adascalitei, F.; Lefeber, D.; Vanderborght, B.; Doroftei, I. A.

2016-08-01

The purpose of this study is to present the preliminary steps in facial expressions recognition with a new version of an expressive social robotic head. So, in a first phase, our main goal was to reach a minimum level of emotional expressiveness in order to obtain nonverbal communication between the robot and human by building six basic facial expressions. To evaluate the facial expressions, the robot was used in some preliminary user studies, among children and adults.

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

PubMed

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.

Deficits in recognition, identification, and discrimination of facial emotions in patients with bipolar disorder.

PubMed

Benito, Adolfo; Lahera, Guillermo; Herrera, Sara; Muncharaz, Ramón; Benito, Guillermo; Fernández-Liria, Alberto; Montes, José Manuel

2013-01-01

To analyze the recognition, identification, and discrimination of facial emotions in a sample of outpatients with bipolar disorder (BD). Forty-four outpatients with diagnosis of BD and 48 matched control subjects were selected. Both groups were assessed with tests for recognition (Emotion Recognition-40 - ER40), identification (Facial Emotion Identification Test - FEIT), and discrimination (Facial Emotion Discrimination Test - FEDT) of facial emotions, as well as a theory of mind (ToM) verbal test (Hinting Task). Differences between groups were analyzed, controlling the influence of mild depressive and manic symptoms. Patients with BD scored significantly lower than controls on recognition (ER40), identification (FEIT), and discrimination (FEDT) of emotions. Regarding the verbal measure of ToM, a lower score was also observed in patients compared to controls. Patients with mild syndromal depressive symptoms obtained outcomes similar to patients in euthymia. A significant correlation between FEDT scores and global functioning (measured by the Functioning Assessment Short Test, FAST) was found. These results suggest that, even in euthymia, patients with BD experience deficits in recognition, identification, and discrimination of facial emotions, with potential functional implications.

Dissociation between recognition and detection advantage for facial expressions: a meta-analysis.

PubMed

Nummenmaa, Lauri; Calvo, Manuel G

2015-04-01

Happy facial expressions are recognized faster and more accurately than other expressions in categorization tasks, whereas detection in visual search tasks is widely believed to be faster for angry than happy faces. We used meta-analytic techniques for resolving this categorization versus detection advantage discrepancy for positive versus negative facial expressions. Effect sizes were computed on the basis of the r statistic for a total of 34 recognition studies with 3,561 participants and 37 visual search studies with 2,455 participants, yielding a total of 41 effect sizes for recognition accuracy, 25 for recognition speed, and 125 for visual search speed. Random effects meta-analysis was conducted to estimate effect sizes at population level. For recognition tasks, an advantage in recognition accuracy and speed for happy expressions was found for all stimulus types. In contrast, for visual search tasks, moderator analysis revealed that a happy face detection advantage was restricted to photographic faces, whereas a clear angry face advantage was found for schematic and "smiley" faces. Robust detection advantage for nonhappy faces was observed even when stimulus emotionality was distorted by inversion or rearrangement of the facial features, suggesting that visual features primarily drive the search. We conclude that the recognition advantage for happy faces is a genuine phenomenon related to processing of facial expression category and affective valence. In contrast, detection advantages toward either happy (photographic stimuli) or nonhappy (schematic) faces is contingent on visual stimulus features rather than facial expression, and may not involve categorical or affective processing. (c) 2015 APA, all rights reserved).

Facial emotion recognition is inversely correlated with tremor severity in essential tremor.

PubMed

Auzou, Nicolas; Foubert-Samier, Alexandra; Dupouy, Sandrine; Meissner, Wassilios G

2014-04-01

We here assess limbic and orbitofrontal control in 20 patients with essential tremor (ET) and 18 age-matched healthy controls using the Ekman Facial Emotion Recognition Task and the IOWA Gambling Task. Our results show an inverse relation between facial emotion recognition and tremor severity. ET patients also showed worse performance in joy and fear recognition, as well as subtle abnormalities in risk detection, but these differences did not reach significance after correction for multiple testing.

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

PubMed

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

2016-05-15

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

Dissociation between facial and bodily expressions in emotion recognition: A case study.

PubMed

Leiva, Samanta; Margulis, Laura; Micciulli, Andrea; Ferreres, Aldo

2017-12-21

Existing single-case studies have reported deficit in recognizing basic emotions through facial expression and unaffected performance with body expressions, but not the opposite pattern. The aim of this paper is to present a case study with impaired emotion recognition through body expressions and intact performance with facial expressions. In this single-case study we assessed a 30-year-old patient with autism spectrum disorder, without intellectual disability, and a healthy control group (n = 30) with four tasks of basic and complex emotion recognition through face and body movements, and two non-emotional control tasks. To analyze the dissociation between facial and body expressions, we used Crawford and Garthwaite's operational criteria, and we compared the patient and the control group performance with a modified one-tailed t-test designed specifically for single-case studies. There were no statistically significant differences between the patient's and the control group's performances on the non-emotional body movement task or the facial perception task. For both kinds of emotions (basic and complex) when the patient's performance was compared to the control group's, statistically significant differences were only observed for the recognition of body expressions. There were no significant differences between the patient's and the control group's correct answers for emotional facial stimuli. Our results showed a profile of impaired emotion recognition through body expressions and intact performance with facial expressions. This is the first case study that describes the existence of this kind of dissociation pattern between facial and body expressions of basic and complex emotions.

An interactive VR system based on full-body tracking and gesture recognition

NASA Astrophysics Data System (ADS)

Zeng, Xia; Sang, Xinzhu; Chen, Duo; Wang, Peng; Guo, Nan; Yan, Binbin; Wang, Kuiru

2016-10-01

Most current virtual reality (VR) interactions are realized with the hand-held input device which leads to a low degree of presence. There is other solutions using sensors like Leap Motion to recognize the gestures of users in order to interact in a more natural way, but the navigation in these systems is still a problem, because they fail to map the actual walking to virtual walking only with a partial body of the user represented in the synthetic environment. Therefore, we propose a system in which users can walk around in the virtual environment as a humanoid model, selecting menu items and manipulating with the virtual objects using natural hand gestures. With a Kinect depth camera, the system tracks the joints of the user, mapping them to a full virtual body which follows the move of the tracked user. The movements of the feet can be detected to determine whether the user is in walking state, so that the walking of model in the virtual world can be activated and stopped by means of animation control in Unity engine. This method frees the hands of users comparing to traditional navigation way using hand-held device. We use the point cloud data getting from Kinect depth camera to recognize the gestures of users, such as swiping, pressing and manipulating virtual objects. Combining the full body tracking and gestures recognition using Kinect, we achieve our interactive VR system in Unity engine with a high degree of presence.

Altered Kinematics of Facial Emotion Expression and Emotion Recognition Deficits Are Unrelated in Parkinson's Disease.

PubMed

Bologna, Matteo; Berardelli, Isabella; Paparella, Giulia; Marsili, Luca; Ricciardi, Lucia; Fabbrini, Giovanni; Berardelli, Alfredo

2016-01-01

Altered emotional processing, including reduced emotion facial expression and defective emotion recognition, has been reported in patients with Parkinson's disease (PD). However, few studies have objectively investigated facial expression abnormalities in PD using neurophysiological techniques. It is not known whether altered facial expression and recognition in PD are related. To investigate possible deficits in facial emotion expression and emotion recognition and their relationship, if any, in patients with PD. Eighteen patients with PD and 16 healthy controls were enrolled in this study. Facial expressions of emotion were recorded using a 3D optoelectronic system and analyzed using the facial action coding system. Possible deficits in emotion recognition were assessed using the Ekman test. Participants were assessed in one experimental session. Possible relationship between the kinematic variables of facial emotion expression, the Ekman test scores, and clinical and demographic data in patients were evaluated using the Spearman's test and multiple regression analysis. The facial expression of all six basic emotions had slower velocity and lower amplitude in patients in comparison to healthy controls (all P s < 0.05). Patients also yielded worse Ekman global score and disgust, sadness, and fear sub-scores than healthy controls (all P s < 0.001). Altered facial expression kinematics and emotion recognition deficits were unrelated in patients (all P s > 0.05). Finally, no relationship emerged between kinematic variables of facial emotion expression, the Ekman test scores, and clinical and demographic data in patients (all P s > 0.05). The results in this study provide further evidence of altered emotional processing in PD. The lack of any correlation between altered facial emotion expression kinematics and emotion recognition deficits in patients suggests that these abnormalities are mediated by separate pathophysiological mechanisms.

Oxytocin Promotes Facial Emotion Recognition and Amygdala Reactivity in Adults with Asperger Syndrome

PubMed Central

Domes, Gregor; Kumbier, Ekkehardt; Heinrichs, Markus; Herpertz, Sabine C

2014-01-01

The neuropeptide oxytocin has recently been shown to enhance eye gaze and emotion recognition in healthy men. Here, we report a randomized double-blind, placebo-controlled trial that examined the neural and behavioral effects of a single dose of intranasal oxytocin on emotion recognition in individuals with Asperger syndrome (AS), a clinical condition characterized by impaired eye gaze and facial emotion recognition. Using functional magnetic resonance imaging, we examined whether oxytocin would enhance emotion recognition from facial sections of the eye vs the mouth region and modulate regional activity in brain areas associated with face perception in both adults with AS, and a neurotypical control group. Intranasal administration of the neuropeptide oxytocin improved performance in a facial emotion recognition task in individuals with AS. This was linked to increased left amygdala reactivity in response to facial stimuli and increased activity in the neural network involved in social cognition. Our data suggest that the amygdala, together with functionally associated cortical areas mediate the positive effect of oxytocin on social cognitive functioning in AS. PMID:24067301

Oxytocin promotes facial emotion recognition and amygdala reactivity in adults with asperger syndrome.

PubMed

Domes, Gregor; Kumbier, Ekkehardt; Heinrichs, Markus; Herpertz, Sabine C

2014-02-01

The neuropeptide oxytocin has recently been shown to enhance eye gaze and emotion recognition in healthy men. Here, we report a randomized double-blind, placebo-controlled trial that examined the neural and behavioral effects of a single dose of intranasal oxytocin on emotion recognition in individuals with Asperger syndrome (AS), a clinical condition characterized by impaired eye gaze and facial emotion recognition. Using functional magnetic resonance imaging, we examined whether oxytocin would enhance emotion recognition from facial sections of the eye vs the mouth region and modulate regional activity in brain areas associated with face perception in both adults with AS, and a neurotypical control group. Intranasal administration of the neuropeptide oxytocin improved performance in a facial emotion recognition task in individuals with AS. This was linked to increased left amygdala reactivity in response to facial stimuli and increased activity in the neural network involved in social cognition. Our data suggest that the amygdala, together with functionally associated cortical areas mediate the positive effect of oxytocin on social cognitive functioning in AS.

Viewpoint Invariant Gesture Recognition and 3D Hand Pose Estimation Using RGB-D

ERIC Educational Resources Information Center

Doliotis, Paul

2013-01-01

The broad application domain of the work presented in this thesis is pattern classification with a focus on gesture recognition and 3D hand pose estimation. One of the main contributions of the proposed thesis is a novel method for 3D hand pose estimation using RGB-D. Hand pose estimation is formulated as a database retrieval problem. The proposed…

[Association between intelligence development and facial expression recognition ability in children with autism spectrum disorder].

PubMed

Pan, Ning; Wu, Gui-Hua; Zhang, Ling; Zhao, Ya-Fen; Guan, Han; Xu, Cai-Juan; Jing, Jin; Jin, Yu

2017-03-01

To investigate the features of intelligence development, facial expression recognition ability, and the association between them in children with autism spectrum disorder (ASD). A total of 27 ASD children aged 6-16 years (ASD group, full intelligence quotient >70) and age- and gender-matched normally developed children (control group) were enrolled. Wechsler Intelligence Scale for Children Fourth Edition and Chinese Static Facial Expression Photos were used for intelligence evaluation and facial expression recognition test. Compared with the control group, the ASD group had significantly lower scores of full intelligence quotient, verbal comprehension index, perceptual reasoning index (PRI), processing speed index（PSI), and working memory index (WMI) (P<0.05). The ASD group also had a significantly lower overall accuracy rate of facial expression recognition and significantly lower accuracy rates of the recognition of happy, angry, sad, and frightened expressions than the control group (P<0.05). In the ASD group, the overall accuracy rate of facial expression recognition and the accuracy rates of the recognition of happy and frightened expressions were positively correlated with PRI (r=0.415, 0.455, and 0.393 respectively; P<0.05). The accuracy rate of the recognition of angry expression was positively correlated with WMI (r=0.397; P<0.05). ASD children have delayed intelligence development compared with normally developed children and impaired expression recognition ability. Perceptual reasoning and working memory abilities are positively correlated with expression recognition ability, which suggests that insufficient perceptual reasoning and working memory abilities may be important factors affecting facial expression recognition ability in ASD children.

Gesture Based Control and EMG Decomposition

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Chang, Mindy H.; Knuth, Kevin H.

2005-01-01

This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

Theory of mind and recognition of facial emotion in dementia: challenge to current concepts.

PubMed

Freedman, Morris; Binns, Malcolm A; Black, Sandra E; Murphy, Cara; Stuss, Donald T

2013-01-01

Current literature suggests that theory of mind (ToM) and recognition of facial emotion are impaired in behavioral variant frontotemporal dementia (bvFTD). In contrast, studies suggest that ToM is spared in Alzheimer disease (AD). However, there is controversy whether recognition of emotion in faces is impaired in AD. This study challenges the concepts that ToM is preserved in AD and that recognition of facial emotion is impaired in bvFTD. ToM, recognition of facial emotion, and identification of emotions associated with video vignettes were studied in bvFTD, AD, and normal controls. ToM was assessed using false-belief and visual perspective-taking tasks. Identification of facial emotion was tested using Ekman and Friesen's pictures of facial affect. After adjusting for relevant covariates, there were significant ToM deficits in bvFTD and AD compared with controls, whereas neither group was impaired in the identification of emotions associated with video vignettes. There was borderline impairment in recognizing angry faces in bvFTD. Patients with AD showed significant deficits on false belief and visual perspective taking, and bvFTD patients were impaired on second-order false belief. We report novel findings challenging the concepts that ToM is spared in AD and that recognition of facial emotion is impaired in bvFTD.

Facial affect recognition in symptomatically remitted patients with schizophrenia and bipolar disorder.

PubMed

Yalcin-Siedentopf, Nursen; Hoertnagl, Christine M; Biedermann, Falko; Baumgartner, Susanne; Deisenhammer, Eberhard A; Hausmann, Armand; Kaufmann, Alexandra; Kemmler, Georg; Mühlbacher, Moritz; Rauch, Anna-Sophia; Fleischhacker, W Wolfgang; Hofer, Alex

2014-02-01

Both schizophrenia and bipolar disorder (BD) have consistently been associated with deficits in facial affect recognition (FAR). These impairments have been related to various aspects of social competence and functioning and are relatively stable over time. However, individuals in remission may outperform patients experiencing an acute phase of the disorders. The present study directly contrasted FAR in symptomatically remitted patients with schizophrenia or BD and healthy volunteers and investigated its relationship with patients' outcomes. Compared to healthy control subjects, schizophrenia patients were impaired in the recognition of angry, disgusted, sad and happy facial expressions, while BD patients showed deficits only in the recognition of disgusted and happy facial expressions. When directly comparing the two patient groups individuals suffering from BD outperformed those with schizophrenia in the recognition of expressions depicting anger. There was no significant association between affect recognition abilities and symptomatic or psychosocial outcomes in schizophrenia patients. Among BD patients, relatively higher depression scores were associated with impairments in both the identification of happy faces and psychosocial functioning. Overall, our findings indicate that during periods of symptomatic remission the recognition of facial affect may be less impaired in patients with BD than in those suffering from schizophrenia. However, in the psychosocial context BD patients seem to be more sensitive to residual symptomatology. Copyright © 2013 Elsevier B.V. All rights reserved.

LBP and SIFT based facial expression recognition

NASA Astrophysics Data System (ADS)

Sumer, Omer; Gunes, Ece O.

2015-02-01

This study compares the performance of local binary patterns (LBP) and scale invariant feature transform (SIFT) with support vector machines (SVM) in automatic classification of discrete facial expressions. Facial expression recognition is a multiclass classification problem and seven classes; happiness, anger, sadness, disgust, surprise, fear and comtempt are classified. Using SIFT feature vectors and linear SVM, 93.1% mean accuracy is acquired on CK+ database. On the other hand, the performance of LBP-based classifier with linear SVM is reported on SFEW using strictly person independent (SPI) protocol. Seven-class mean accuracy on SFEW is 59.76%. Experiments on both databases showed that LBP features can be used in a fairly descriptive way if a good localization of facial points and partitioning strategy are followed.

Facial Emotion Recognition in Child Psychiatry: A Systematic Review

ERIC Educational Resources Information Center

Collin, Lisa; Bindra, Jasmeet; Raju, Monika; Gillberg, Christopher; Minnis, Helen

2013-01-01

This review focuses on facial affect (emotion) recognition in children and adolescents with psychiatric disorders other than autism. A systematic search, using PRISMA guidelines, was conducted to identify original articles published prior to October 2011 pertaining to face recognition tasks in case-control studies. Used in the qualitative…

Discriminability effect on Garner interference: evidence from recognition of facial identity and expression

PubMed Central

Wang, Yamin; Fu, Xiaolan; Johnston, Robert A.; Yan, Zheng

2013-01-01

Using Garner’s speeded classification task existing studies demonstrated an asymmetric interference in the recognition of facial identity and facial expression. It seems that expression is hard to interfere with identity recognition. However, discriminability of identity and expression, a potential confounding variable, had not been carefully examined in existing studies. In current work, we manipulated discriminability of identity and expression by matching facial shape (long or round) in identity and matching mouth (opened or closed) in facial expression. Garner interference was found either from identity to expression (Experiment 1) or from expression to identity (Experiment 2). Interference was also found in both directions (Experiment 3) or in neither direction (Experiment 4). The results support that Garner interference tends to occur under condition of low discriminability of relevant dimension regardless of facial property. Our findings indicate that Garner interference is not necessarily related to interdependent processing in recognition of facial identity and expression. The findings also suggest that discriminability as a mediating factor should be carefully controlled in future research. PMID:24391609

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

PubMed

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

2016-10-01

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

Instructions to mimic improve facial emotion recognition in people with sub-clinical autism traits.

PubMed

Lewis, Michael B; Dunn, Emily

2017-11-01

People tend to mimic the facial expression of others. It has been suggested that this helps provide social glue between affiliated people but it could also aid recognition of emotions through embodied cognition. The degree of facial mimicry, however, varies between individuals and is limited in people with autism spectrum conditions (ASC). The present study sought to investigate the effect of promoting facial mimicry during a facial-emotion-recognition test. In two experiments, participants without an ASC diagnosis had their autism quotient (AQ) measured. Following a baseline test, they did an emotion-recognition test again but half of the participants were asked to mimic the target face they saw prior to making their responses. Mimicry improved emotion recognition, and further analysis revealed that the largest improvement was for participants who had higher scores on the autism traits. In fact, recognition performance was best overall for people who had high AQ scores but also received the instruction to mimic. Implications for people with ASC are explored.

Functional integration of the posterior superior temporal sulcus correlates with facial expression recognition.

PubMed

Wang, Xu; Song, Yiying; Zhen, Zonglei; Liu, Jia

2016-05-01

Face perception is essential for daily and social activities. Neuroimaging studies have revealed a distributed face network (FN) consisting of multiple regions that exhibit preferential responses to invariant or changeable facial information. However, our understanding about how these regions work collaboratively to facilitate facial information processing is limited. Here, we focused on changeable facial information processing, and investigated how the functional integration of the FN is related to the performance of facial expression recognition. To do so, we first defined the FN as voxels that responded more strongly to faces than objects, and then used a voxel-based global brain connectivity method based on resting-state fMRI to characterize the within-network connectivity (WNC) of each voxel in the FN. By relating the WNC and performance in the "Reading the Mind in the Eyes" Test across participants, we found that individuals with stronger WNC in the right posterior superior temporal sulcus (rpSTS) were better at recognizing facial expressions. Further, the resting-state functional connectivity (FC) between the rpSTS and right occipital face area (rOFA), early visual cortex (EVC), and bilateral STS were positively correlated with the ability of facial expression recognition, and the FCs of EVC-pSTS and OFA-pSTS contributed independently to facial expression recognition. In short, our study highlights the behavioral significance of intrinsic functional integration of the FN in facial expression processing, and provides evidence for the hub-like role of the rpSTS for facial expression recognition. Hum Brain Mapp 37:1930-1940, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Facial soft biometric features for forensic face recognition.

PubMed

Tome, Pedro; Vera-Rodriguez, Ruben; Fierrez, Julian; Ortega-Garcia, Javier

2015-12-01

This paper proposes a functional feature-based approach useful for real forensic caseworks, based on the shape, orientation and size of facial traits, which can be considered as a soft biometric approach. The motivation of this work is to provide a set of facial features, which can be understood by non-experts such as judges and support the work of forensic examiners who, in practice, carry out a thorough manual comparison of face images paying special attention to the similarities and differences in shape and size of various facial traits. This new approach constitutes a tool that automatically converts a set of facial landmarks to a set of features (shape and size) corresponding to facial regions of forensic value. These features are furthermore evaluated in a population to generate statistics to support forensic examiners. The proposed features can also be used as additional information that can improve the performance of traditional face recognition systems. These features follow the forensic methodology and are obtained in a continuous and discrete manner from raw images. A statistical analysis is also carried out to study the stability, discrimination power and correlation of the proposed facial features on two realistic databases: MORPH and ATVS Forensic DB. Finally, the performance of both continuous and discrete features is analyzed using different similarity measures. Experimental results show high discrimination power and good recognition performance, especially for continuous features. A final fusion of the best systems configurations achieves rank 10 match results of 100% for ATVS database and 75% for MORPH database demonstrating the benefits of using this information in practice. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Oxytocin improves facial emotion recognition in young adults with antisocial personality disorder.

PubMed

Timmermann, Marion; Jeung, Haang; Schmitt, Ruth; Boll, Sabrina; Freitag, Christine M; Bertsch, Katja; Herpertz, Sabine C

2017-11-01

Deficient facial emotion recognition has been suggested to underlie aggression in individuals with antisocial personality disorder (ASPD). As the neuropeptide oxytocin (OT) has been shown to improve facial emotion recognition, it might also exert beneficial effects in individuals providing so much harm to the society. In a double-blind, randomized, placebo-controlled crossover trial, 22 individuals with ASPD and 29 healthy control (HC) subjects (matched for age, sex, intelligence, and education) were intranasally administered either OT (24 IU) or a placebo 45min before participating in an emotion classification paradigm with fearful, angry, and happy faces. We assessed the number of correct classifications and reaction times as indicators of emotion recognition ability. Significant group×substance×emotion interactions were found in correct classifications and reaction times. Compared to HC, individuals with ASPD showed deficits in recognizing fearful and happy faces; these group differences were no longer observable under OT. Additionally, reaction times for angry faces differed significantly between the ASPD and HC group in the placebo condition. This effect was mainly driven by longer reaction times in HC subjects after placebo administration compared to OT administration while individuals with ASPD revealed descriptively the contrary response pattern. Our data indicate an improvement of the recognition of fearful and happy facial expressions by OT in young adults with ASPD. Particularly the increased recognition of facial fear is of high importance since the correct perception of distress signals in others is thought to inhibit aggression. Beneficial effects of OT might be further mediated by improved recognition of facial happiness probably reflecting increased social reward responsiveness. Copyright © 2017. Published by Elsevier Ltd.

Development of Emotional Facial Recognition in Late Childhood and Adolescence

ERIC Educational Resources Information Center

Thomas, Laura A.; De Bellis, Michael D.; Graham, Reiko; Labar, Kevin S.

2007-01-01

The ability to interpret emotions in facial expressions is crucial for social functioning across the lifespan. Facial expression recognition develops rapidly during infancy and improves with age during the preschool years. However, the developmental trajectory from late childhood to adulthood is less clear. We tested older children, adolescents…

Fusiform gyrus volume reduction and facial recognition in chronic schizophrenia.

PubMed

Onitsuka, Toshiaki; Shenton, Martha E; Kasai, Kiyoto; Nestor, Paul G; Toner, Sarah K; Kikinis, Ron; Jolesz, Ferenc A; McCarley, Robert W

2003-04-01

The fusiform gyrus (FG), or occipitotemporal gyrus, is thought to subserve the processing and encoding of faces. Of note, several studies have reported that patients with schizophrenia show deficits in facial processing. It is thus hypothesized that the FG might be one brain region underlying abnormal facial recognition in schizophrenia. The objectives of this study were to determine whether there are abnormalities in gray matter volumes for the anterior and the posterior FG in patients with chronic schizophrenia and to investigate relationships between FG subregions and immediate and delayed memory for faces. Patients were recruited from the Boston VA Healthcare System, Brockton Division, and control subjects were recruited through newspaper advertisement. Study participants included 21 male patients diagnosed as having chronic schizophrenia and 28 male controls. Participants underwent high-spatial-resolution magnetic resonance imaging, and facial recognition memory was evaluated. Main outcome measures included anterior and posterior FG gray matter volumes based on high-spatial-resolution magnetic resonance imaging, a detailed and reliable manual delineation using 3-dimensional information, and correlation coefficients between FG subregions and raw scores on immediate and delayed facial memory derived from the Wechsler Memory Scale III. Patients with chronic schizophrenia had overall smaller FG gray matter volumes (10%) than normal controls. Additionally, patients with schizophrenia performed more poorly than normal controls in both immediate and delayed facial memory tests. Moreover, the degree of poor performance on delayed memory for faces was significantly correlated with the degree of bilateral anterior FG reduction in patients with schizophrenia. These results suggest that neuroanatomic FG abnormalities underlie at least some of the deficits associated with facial recognition in schizophrenia.

Biases in facial and vocal emotion recognition in chronic schizophrenia

PubMed Central

Dondaine, Thibaut; Robert, Gabriel; Péron, Julie; Grandjean, Didier; Vérin, Marc; Drapier, Dominique; Millet, Bruno

2014-01-01

There has been extensive research on impaired emotion recognition in schizophrenia in the facial and vocal modalities. The literature points to biases toward non-relevant emotions for emotional faces but few studies have examined biases in emotional recognition across different modalities (facial and vocal). In order to test emotion recognition biases, we exposed 23 patients with stabilized chronic schizophrenia and 23 healthy controls (HCs) to emotional facial and vocal tasks asking them to rate emotional intensity on visual analog scales. We showed that patients with schizophrenia provided higher intensity ratings on the non-target scales (e.g., surprise scale for fear stimuli) than HCs for the both tasks. Furthermore, with the exception of neutral vocal stimuli, they provided the same intensity ratings on the target scales as the HCs. These findings suggest that patients with chronic schizophrenia have emotional biases when judging emotional stimuli in the visual and vocal modalities. These biases may stem from a basic sensorial deficit, a high-order cognitive dysfunction, or both. The respective roles of prefrontal-subcortical circuitry and the basal ganglia are discussed. PMID:25202287

Does vigilance to pain make individuals experts in facial recognition of pain?

PubMed

Baum, Corinna; Kappesser, Judith; Schneider, Raphaela; Lautenbacher, Stefan

2013-01-01

It is well known that individual factors are important in the facial recognition of pain. However, it is unclear whether vigilance to pain as a pain-related attentional mechanism is among these relevant factors. Vigilance to pain may have two different effects on the recognition of facial pain expressions: pain-vigilant individuals may detect pain faces better but overinclude other facial displays, misinterpreting them as expressing pain; or they may be true experts in discriminating between pain and other facial expressions. The present study aimed to test these two hypotheses. Furthermore, pain vigilance was assumed to be a distinct predictor, the impact of which on recognition cannot be completely replaced by related concepts such as pain catastrophizing and fear of pain. Photographs of neutral, happy, angry and pain facial expressions were presented to 40 healthy participants, who were asked to classify them into the appropriate emotion categories and provide a confidence rating for each classification. Additionally, potential predictors of the discrimination performance for pain and anger faces - pain vigilance, pain-related catastrophizing, fear of pain--were assessed using self-report questionnaires. Pain-vigilant participants classified pain faces more accurately and did not misclassify anger as pain faces more frequently. However, vigilance to pain was not related to the confidence of recognition ratings. Pain catastrophizing and fear of pain did not account for the recognition performance. Moderate pain vigilance, as assessed in the present study, appears to be associated with appropriate detection of pain-related cues and not necessarily with the overinclusion of other negative cues.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Recognition of facial expressions and prosodic cues with graded emotional intensities in adults with Asperger syndrome.

PubMed

Doi, Hirokazu; Fujisawa, Takashi X; Kanai, Chieko; Ohta, Haruhisa; Yokoi, Hideki; Iwanami, Akira; Kato, Nobumasa; Shinohara, Kazuyuki

2013-09-01

This study investigated the ability of adults with Asperger syndrome to recognize emotional categories of facial expressions and emotional prosodies with graded emotional intensities. The individuals with Asperger syndrome showed poorer recognition performance for angry and sad expressions from both facial and vocal information. The group difference in facial expression recognition was prominent for stimuli with low or intermediate emotional intensities. In contrast to this, the individuals with Asperger syndrome exhibited lower recognition accuracy than typically-developed controls mainly for emotional prosody with high emotional intensity. In facial expression recognition, Asperger and control groups showed an inversion effect for all categories. The magnitude of this effect was less in the Asperger group for angry and sad expressions, presumably attributable to reduced recruitment of the configural mode of face processing. The individuals with Asperger syndrome outperformed the control participants in recognizing inverted sad expressions, indicating enhanced processing of local facial information representing sad emotion. These results suggest that the adults with Asperger syndrome rely on modality-specific strategies in emotion recognition from facial expression and prosodic information.

Brain correlates of musical and facial emotion recognition: evidence from the dementias.

PubMed

Hsieh, S; Hornberger, M; Piguet, O; Hodges, J R

2012-07-01

The recognition of facial expressions of emotion is impaired in semantic dementia (SD) and is associated with right-sided brain atrophy in areas known to be involved in emotion processing, notably the amygdala. Whether patients with SD also experience difficulty recognizing emotions conveyed by other media, such as music, is unclear. Prior studies have used excerpts of known music from classical or film repertoire but not unfamiliar melodies designed to convey distinct emotions. Patients with SD (n = 11), Alzheimer's disease (n = 12) and healthy control participants (n = 20) underwent tests of emotion recognition in two modalities: unfamiliar musical tunes and unknown faces as well as volumetric MRI. Patients with SD were most impaired with the recognition of facial and musical emotions, particularly for negative emotions. Voxel-based morphometry showed that the labelling of emotions, regardless of modality, correlated with the degree of atrophy in the right temporal pole, amygdala and insula. The recognition of musical (but not facial) emotions was also associated with atrophy of the left anterior and inferior temporal lobe, which overlapped with regions correlating with standardized measures of verbal semantic memory. These findings highlight the common neural substrates supporting the processing of emotions by facial and musical stimuli but also indicate that the recognition of emotions from music draws upon brain regions that are associated with semantics in language. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Recognition of facial expression of emotions in Parkinson's disease: a theoretical review].

PubMed

Alonso-Recio, L; Serrano-Rodriguez, J M; Carvajal-Molina, F; Loeches-Alonso, A; Martin-Plasencia, P

2012-04-16

Emotional facial expression is a basic guide during social interaction and, therefore, alterations in their expression or recognition are important limitations for communication. To examine facial expression recognition abilities and their possible impairment in Parkinson's disease. First, we review the studies on this topic which have not found entirely similar results. Second, we analyze the factors that may explain these discrepancies and, in particular, as third objective, we consider the relationship between emotional recognition problems and cognitive impairment associated with the disease. Finally, we propose alternatives strategies for the development of studies that could clarify the state of these abilities in Parkinson's disease. Most studies suggest deficits in facial expression recognition, especially in those with negative emotional content. However, it is possible that these alterations are related to those that also appear in the course of the disease in other perceptual and executive processes. To advance in this issue, we consider necessary to design emotional recognition studies implicating differentially the executive or visuospatial processes, and/or contrasting cognitive abilities with facial expressions and non emotional stimuli. The precision of the status of these abilities, as well as increase our knowledge of the functional consequences of the characteristic brain damage in the disease, may indicate if we should pay special attention in their rehabilitation inside the programs implemented.

Face recognition using facial expression: a novel approach

NASA Astrophysics Data System (ADS)

Singh, Deepak Kumar; Gupta, Priya; Tiwary, U. S.

2008-04-01

Facial expressions are undoubtedly the most effective nonverbal communication. The face has always been the equation of a person's identity. The face draws the demarcation line between identity and extinction. Each line on the face adds an attribute to the identity. These lines become prominent when we experience an emotion and these lines do not change completely with age. In this paper we have proposed a new technique for face recognition which focuses on the facial expressions of the subject to identify his face. This is a grey area on which not much light has been thrown earlier. According to earlier researches it is difficult to alter the natural expression. So our technique will be beneficial for identifying occluded or intentionally disguised faces. The test results of the experiments conducted prove that this technique will give a new direction in the field of face recognition. This technique will provide a strong base to the area of face recognition and will be used as the core method for critical defense security related issues.

The look of fear and anger: facial maturity modulates recognition of fearful and angry expressions.

PubMed

Sacco, Donald F; Hugenberg, Kurt

2009-02-01

The current series of studies provide converging evidence that facial expressions of fear and anger may have co-evolved to mimic mature and babyish faces in order to enhance their communicative signal. In Studies 1 and 2, fearful and angry facial expressions were manipulated to have enhanced babyish features (larger eyes) or enhanced mature features (smaller eyes) and in the context of a speeded categorization task in Study 1 and a visual noise paradigm in Study 2, results indicated that larger eyes facilitated the recognition of fearful facial expressions, while smaller eyes facilitated the recognition of angry facial expressions. Study 3 manipulated facial roundness, a stable structure that does not vary systematically with expressions, and found that congruency between maturity and expression (narrow face-anger; round face-fear) facilitated expression recognition accuracy. Results are discussed as representing a broad co-evolutionary relationship between facial maturity and fearful and angry facial expressions. (c) 2009 APA, all rights reserved

Recognition of children on age-different images: Facial morphology and age-stable features.

PubMed

Caplova, Zuzana; Compassi, Valentina; Giancola, Silvio; Gibelli, Daniele M; Obertová, Zuzana; Poppa, Pasquale; Sala, Remo; Sforza, Chiarella; Cattaneo, Cristina

2017-07-01

The situation of missing children is one of the most emotional social issues worldwide. The search for and identification of missing children is often hampered, among others, by the fact that the facial morphology of long-term missing children changes as they grow. Nowadays, the wide coverage by surveillance systems potentially provides image material for comparisons with images of missing children that may facilitate identification. The aim of study was to identify whether facial features are stable in time and can be utilized for facial recognition by comparing facial images of children at different ages as well as to test the possible use of moles in recognition. The study was divided into two phases (1) morphological classification of facial features using an Anthropological Atlas; (2) algorithm developed in MATLAB® R2014b for assessing the use of moles as age-stable features. The assessment of facial features by Anthropological Atlases showed high mismatch percentages among observers. On average, the mismatch percentages were lower for features describing shape than for those describing size. The nose tip cleft and the chin dimple showed the best agreement between observers regarding both categorization and stability over time. Using the position of moles as a reference point for recognition of the same person on age-different images seems to be a useful method in terms of objectivity and it can be concluded that moles represent age-stable facial features that may be considered for preliminary recognition. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Mapping structural covariance networks of facial emotion recognition in early psychosis: A pilot study.

PubMed

Buchy, Lisa; Barbato, Mariapaola; Makowski, Carolina; Bray, Signe; MacMaster, Frank P; Deighton, Stephanie; Addington, Jean

2017-11-01

People with psychosis show deficits recognizing facial emotions and disrupted activation in the underlying neural circuitry. We evaluated associations between facial emotion recognition and cortical thickness using a correlation-based approach to map structural covariance networks across the brain. Fifteen people with an early psychosis provided magnetic resonance scans and completed the Penn Emotion Recognition and Differentiation tasks. Fifteen historical controls provided magnetic resonance scans. Cortical thickness was computed using CIVET and analyzed with linear models. Seed-based structural covariance analysis was done using the mapping anatomical correlations across the cerebral cortex methodology. To map structural covariance networks involved in facial emotion recognition, the right somatosensory cortex and bilateral fusiform face areas were selected as seeds. Statistics were run in SurfStat. Findings showed increased cortical covariance between the right fusiform face region seed and right orbitofrontal cortex in controls than early psychosis subjects. Facial emotion recognition scores were not significantly associated with thickness in any region. A negative effect of Penn Differentiation scores on cortical covariance was seen between the left fusiform face area seed and right superior parietal lobule in early psychosis subjects. Results suggest that facial emotion recognition ability is related to covariance in a temporal-parietal network in early psychosis. Copyright © 2017 Elsevier B.V. All rights reserved.

[The effect of the serotonin transporter 5-HTTLPR polymorphism on the recognition of facial emotions in schizophrenia].

PubMed

Alfimova, M V; Golimbet, V E; Korovaitseva, G I; Lezheiko, T V; Abramova, L I; Aksenova, E V; Bolgov, M I

2014-01-01

The 5-HTTLPR SLC6A4 and catechol-o-methyltransferase (COMT) Val158Met polymorphisms are reported to be associated with processing of facial expressions in general population. Impaired recognition of facial expressions that is characteristic of schizophrenia negatively impacts on the social adaptation of the patients. To search for molecular mechanisms of this deficit, we studied main and epistatic effects of 5-HTTLPR and Val158Met polymorphisms on the facial emotion recognition in patients with schizophrenia (n=299) and healthy controls (n=232). The 5-HTTLPR polymorphism was associated with the emotion recognition in patients. The ll-homozygotes recognized facial emotions significantly better compared to those with an s-allele (F=8.00; p=0.005). Although the recognition of facial emotions was correlated with negative symptoms, verbal learning and trait anxiety, these variables did not significantly modified the association. In both groups, no effect of the COMT on the recognition of facial emotions was found.

Device Control Using Gestures Sensed from EMG

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.

2003-01-01

In this paper we present neuro-electric interfaces for virtual device control. The examples presented rely upon sampling Electromyogram data from a participants forearm. This data is then fed into pattern recognition software that has been trained to distinguish gestures from a given gesture set. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard.

Holistic face processing can inhibit recognition of forensic facial composites.

PubMed

McIntyre, Alex H; Hancock, Peter J B; Frowd, Charlie D; Langton, Stephen R H

2016-04-01

Facial composite systems help eyewitnesses to show the appearance of criminals. However, likenesses created by unfamiliar witnesses will not be completely accurate, and people familiar with the target can find them difficult to identify. Faces are processed holistically; we explore whether this impairs identification of inaccurate composite images and whether recognition can be improved. In Experiment 1 (n = 64) an imaging technique was used to make composites of celebrity faces more accurate and identification was contrasted with the original composite images. Corrected composites were better recognized, confirming that errors in production of the likenesses impair identification. The influence of holistic face processing was explored by misaligning the top and bottom parts of the composites (cf. Young, Hellawell, & Hay, 1987). Misalignment impaired recognition of corrected composites but identification of the original, inaccurate composites significantly improved. This effect was replicated with facial composites of noncelebrities in Experiment 2 (n = 57). We conclude that, like real faces, facial composites are processed holistically: recognition is impaired because unlike real faces, composites contain inaccuracies and holistic face processing makes it difficult to perceive identifiable features. This effect was consistent across composites of celebrities and composites of people who are personally familiar. Our findings suggest that identification of forensic facial composites can be enhanced by presenting composites in a misaligned format. (c) 2016 APA, all rights reserved).

The Change in Facial Emotion Recognition Ability in Inpatients with Treatment Resistant Schizophrenia After Electroconvulsive Therapy.

PubMed

Dalkıran, Mihriban; Tasdemir, Akif; Salihoglu, Tamer; Emul, Murat; Duran, Alaattin; Ugur, Mufit; Yavuz, Ruhi

2017-09-01

People with schizophrenia have impairments in emotion recognition along with other social cognitive deficits. In the current study, we aimed to investigate the immediate benefits of ECT on facial emotion recognition ability. Thirty-two treatment resistant patients with schizophrenia who have been indicated for ECT enrolled in the study. Facial emotion stimuli were a set of 56 photographs that depicted seven basic emotions: sadness, anger, happiness, disgust, surprise, fear, and neutral faces. The average age of the participants was 33.4 ± 10.5 years. The rate of recognizing the disgusted facial expression increased significantly after ECT (p < 0.05) and no significant changes were found in the rest of the facial expressions (p > 0.05). After the ECT, the time period of responding to the fear and happy facial expressions were significantly shorter (p < 0.05). Facial emotion recognition ability is an important social cognitive skill for social harmony, proper relation and living independently. At least, the ECT sessions do not seem to affect facial emotion recognition ability negatively and seem to improve identifying disgusted facial emotion which is related with dopamine enriched regions in brain.

Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications.

PubMed

Parks, Connie L; Monson, Keith L

2017-04-01

The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries. Depending on the scanning protocol and gallery size, in 6-61 % of the cases, a correct life photo match for a CT-derived facial image was the top ranked image in the generated candidate lists, even when blind searching in excess of 100,000 images. In 31-91 % of the cases, a correct match was located within the top 50 images. Few significant differences (p > 0.05) in match rates were observed between the sexes or across the three age cohorts. Highly significant differences (p < 0.01) were, however, observed across the three ancestral cohorts and between the two CT scanning protocols. Results suggest that the probability of a match between a facial image extracted from a medical scan and a photograph of the individual is moderately high. The facial image data inherent in commonly employed medical imaging modalities may need to consider a potentially identifiable form of "comparable" facial imagery and protected as such under patient privacy legislation.

Power independent EMG based gesture recognition for robotics.

PubMed

Li, Ling; Looney, David; Park, Cheolsoo; Rehman, Naveed U; Mandic, Danilo P

2011-01-01

A novel method for detecting muscle contraction is presented. This method is further developed for identifying four different gestures to facilitate a hand gesture controlled robot system. It is achieved based on surface Electromyograph (EMG) measurements of groups of arm muscles. The cross-information is preserved through a simultaneous processing of EMG channels using a recent multivariate extension of Empirical Mode Decomposition (EMD). Next, phase synchrony measures are employed to make the system robust to different power levels due to electrode placements and impedances. The multiple pairwise muscle synchronies are used as features of a discrete gesture space comprising four gestures (flexion, extension, pronation, supination). Simulations on real-time robot control illustrate the enhanced accuracy and robustness of the proposed methodology.

Effects of facial emotion recognition remediation on visual scanning of novel face stimuli.

PubMed

Marsh, Pamela J; Luckett, Gemma; Russell, Tamara; Coltheart, Max; Green, Melissa J

2012-11-01

Previous research shows that emotion recognition in schizophrenia can be improved with targeted remediation that draws attention to important facial features (eyes, nose, mouth). Moreover, the effects of training have been shown to last for up to one month after training. The aim of this study was to investigate whether improved emotion recognition of novel faces is associated with concomitant changes in visual scanning of these same novel facial expressions. Thirty-nine participants with schizophrenia received emotion recognition training using Ekman's Micro-Expression Training Tool (METT), with emotion recognition and visual scanpath (VSP) recordings to face stimuli collected simultaneously. Baseline ratings of interpersonal and cognitive functioning were also collected from all participants. Post-METT training, participants showed changes in foveal attention to the features of facial expressions of emotion not used in METT training, which were generally consistent with the information about important features from the METT. In particular, there were changes in how participants looked at the features of facial expressions of emotion surprise, disgust, fear, happiness, and neutral, demonstrating that improved emotion recognition is paralleled by changes in the way participants with schizophrenia viewed novel facial expressions of emotion. However, there were overall decreases in foveal attention to sad and neutral faces that indicate more intensive instruction might be needed for these faces during training. Most importantly, the evidence shows that participant gender may affect training outcomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Does vigilance to pain make individuals experts in facial recognition of pain?

PubMed Central

Baum, Corinna; Kappesser, Judith; Schneider, Raphaela; Lautenbacher, Stefan

2013-01-01

BACKGROUND: It is well known that individual factors are important in the facial recognition of pain. However, it is unclear whether vigilance to pain as a pain-related attentional mechanism is among these relevant factors. OBJECTIVES: Vigilance to pain may have two different effects on the recognition of facial pain expressions: pain-vigilant individuals may detect pain faces better but overinclude other facial displays, misinterpreting them as expressing pain; or they may be true experts in discriminating between pain and other facial expressions. The present study aimed to test these two hypotheses. Furthermore, pain vigilance was assumed to be a distinct predictor, the impact of which on recognition cannot be completely replaced by related concepts such as pain catastrophizing and fear of pain. METHODS: Photographs of neutral, happy, angry and pain facial expressions were presented to 40 healthy participants, who were asked to classify them into the appropriate emotion categories and provide a confidence rating for each classification. Additionally, potential predictors of the discrimination performance for pain and anger faces – pain vigilance, pain-related catastrophizing, fear of pain – were assessed using self-report questionnaires. RESULTS: Pain-vigilant participants classified pain faces more accurately and did not misclassify anger as pain faces more frequently. However, vigilance to pain was not related to the confidence of recognition ratings. Pain catastrophizing and fear of pain did not account for the recognition performance. CONCLUSIONS: Moderate pain vigilance, as assessed in the present study, appears to be associated with appropriate detection of pain-related cues and not necessarily with the overinclusion of other negative cues. PMID:23717826

Automated facial recognition of manually generated clay facial approximations: Potential application in unidentified persons data repositories.

PubMed

Parks, Connie L; Monson, Keith L

2018-01-01

This research examined how accurately 2D images (i.e., photographs) of 3D clay facial approximations were matched to corresponding photographs of the approximated individuals using an objective automated facial recognition system. Irrespective of search filter (i.e., blind, sex, or ancestry) or rank class (R 1 , R 10 , R 25 , and R 50 ) employed, few operationally informative results were observed. In only a single instance of 48 potential match opportunities was a clay approximation matched to a corresponding life photograph within the top 50 images (R 50 ) of a candidate list, even with relatively small gallery sizes created from the application of search filters (e.g., sex or ancestry search restrictions). Increasing the candidate lists to include the top 100 images (R 100 ) resulted in only two additional instances of correct match. Although other untested variables (e.g., approximation method, 2D photographic process, and practitioner skill level) may have impacted the observed results, this study suggests that 2D images of manually generated clay approximations are not readily matched to life photos by automated facial recognition systems. Further investigation is necessary in order to identify the underlying cause(s), if any, of the poor recognition results observed in this study (e.g., potential inferior facial feature detection and extraction). Additional inquiry exploring prospective remedial measures (e.g., stronger feature differentiation) is also warranted, particularly given the prominent use of clay approximations in unidentified persons casework. Copyright © 2017. Published by Elsevier B.V.

People with chronic facial pain perform worse than controls at a facial emotion recognition task, but it is not all about the emotion.

PubMed

von Piekartz, H; Wallwork, S B; Mohr, G; Butler, D S; Moseley, G L

2015-04-01

Alexithymia, or a lack of emotional awareness, is prevalent in some chronic pain conditions and has been linked to poor recognition of others' emotions. Recognising others' emotions from their facial expression involves both emotional and motor processing, but the possible contribution of motor disruption has not been considered. It is possible that poor performance on emotional recognition tasks could reflect problems with emotional processing, motor processing or both. We hypothesised that people with chronic facial pain would be less accurate in recognising others' emotions from facial expressions, would be less accurate in a motor imagery task involving the face, and that performance on both tasks would be positively related. A convenience sample of 19 people (15 females) with chronic facial pain and 19 gender-matched controls participated. They undertook two tasks; in the first task, they identified the facial emotion presented in a photograph. In the second, they identified whether the person in the image had a facial feature pointed towards their left or right side, a well-recognised paradigm to induce implicit motor imagery. People with chronic facial pain performed worse than controls at both tasks (Facially Expressed Emotion Labelling (FEEL) task P < 0·001; left/right judgment task P < 0·001). Participants who were more accurate at one task were also more accurate at the other, regardless of group (P < 0·001, r(2)  = 0·523). Participants with chronic facial pain were worse than controls at both the FEEL emotion recognition task and the left/right facial expression task and performance covaried within participants. We propose that disrupted motor processing may underpin or at least contribute to the difficulty that facial pain patients have in emotion recognition and that further research that tests this proposal is warranted. © 2014 John Wiley & Sons Ltd.

Facial Emotion Recognition Impairments are Associated with Brain Volume Abnormalities in Individuals with HIV

PubMed Central

Clark, Uraina S.; Walker, Keenan A.; Cohen, Ronald A.; Devlin, Kathryn N.; Folkers, Anna M.; Pina, Mathew M.; Tashima, Karen T.

2015-01-01

Impaired facial emotion recognition abilities in HIV+ patients are well documented, but little is known about the neural etiology of these difficulties. We examined the relation of facial emotion recognition abilities to regional brain volumes in 44 HIV-positive (HIV+) and 44 HIV-negative control (HC) adults. Volumes of structures implicated in HIV− associated neuropathology and emotion recognition were measured on MRI using an automated segmentation tool. Relative to HC, HIV+ patients demonstrated emotion recognition impairments for fearful expressions, reduced anterior cingulate cortex (ACC) volumes, and increased amygdala volumes. In the HIV+ group, fear recognition impairments correlated significantly with ACC, but not amygdala volumes. ACC reductions were also associated with lower nadir CD4 levels (i.e., greater HIV-disease severity). These findings extend our understanding of the neurobiological substrates underlying an essential social function, facial emotion recognition, in HIV+ individuals and implicate HIV-related ACC atrophy in the impairment of these abilities. PMID:25744868

Effect of camera resolution and bandwidth on facial affect recognition.

PubMed

Cruz, Mario; Cruz, Robyn Flaum; Krupinski, Elizabeth A; Lopez, Ana Maria; McNeeley, Richard M; Weinstein, Ronald S

2004-01-01

This preliminary study explored the effect of camera resolution and bandwidth on facial affect recognition, an important process and clinical variable in mental health service delivery. Sixty medical students and mental health-care professionals were recruited and randomized to four different combinations of commonly used teleconferencing camera resolutions and bandwidths: (1) one chip charged coupling device (CCD) camera, commonly used for VHSgrade taping and in teleconferencing systems costing less than $4,000 with a resolution of 280 lines, and 128 kilobytes per second bandwidth (kbps); (2) VHS and 768 kbps; (3) three-chip CCD camera, commonly used for Betacam (Beta) grade taping and in teleconferencing systems costing more than $4,000 with a resolution of 480 lines, and 128 kbps; and (4) Betacam and 768 kbps. The subjects were asked to identify four facial affects dynamically presented on videotape by an actor and actress presented via a video monitor at 30 frames per second. Two-way analysis of variance (ANOVA) revealed a significant interaction effect for camera resolution and bandwidth (p = 0.02) and a significant main effect for camera resolution (p = 0.006), but no main effect for bandwidth was detected. Post hoc testing of interaction means, using the Tukey Honestly Significant Difference (HSD) test and the critical difference (CD) at the 0.05 alpha level = 1.71, revealed subjects in the VHS/768 kbps (M = 7.133) and VHS/128 kbps (M = 6.533) were significantly better at recognizing the displayed facial affects than those in the Betacam/768 kbps (M = 4.733) or Betacam/128 kbps (M = 6.333) conditions. Camera resolution and bandwidth combinations differ in their capacity to influence facial affect recognition. For service providers, this study's results support the use of VHS cameras with either 768 kbps or 128 kbps bandwidths for facial affect recognition compared to Betacam cameras. The authors argue that the results of this study are a consequence of the

Emotional recognition from dynamic facial, vocal and musical expressions following traumatic brain injury.

PubMed

Drapeau, Joanie; Gosselin, Nathalie; Peretz, Isabelle; McKerral, Michelle

2017-01-01

To assess emotion recognition from dynamic facial, vocal and musical expressions in sub-groups of adults with traumatic brain injuries (TBI) of different severities and identify possible common underlying mechanisms across domains. Forty-one adults participated in this study: 10 with moderate-severe TBI, nine with complicated mild TBI, 11 with uncomplicated mild TBI and 11 healthy controls, who were administered experimental (emotional recognition, valence-arousal) and control tasks (emotional and structural discrimination) for each domain. Recognition of fearful faces was significantly impaired in moderate-severe and in complicated mild TBI sub-groups, as compared to those with uncomplicated mild TBI and controls. Effect sizes were medium-large. Participants with lower GCS scores performed more poorly when recognizing fearful dynamic facial expressions. Emotion recognition from auditory domains was preserved following TBI, irrespective of severity. All groups performed equally on control tasks, indicating no perceptual disorders. Although emotional recognition from vocal and musical expressions was preserved, no correlation was found across auditory domains. This preliminary study may contribute to improving comprehension of emotional recognition following TBI. Future studies of larger samples could usefully include measures of functional impacts of recognition deficits for fearful facial expressions. These could help refine interventions for emotional recognition following a brain injury.

Multimedia Content Development as a Facial Expression Datasets for Recognition of Human Emotions

NASA Astrophysics Data System (ADS)

Mamonto, N. E.; Maulana, H.; Liliana, D. Y.; Basaruddin, T.

2018-02-01

Datasets that have been developed before contain facial expression from foreign people. The development of multimedia content aims to answer the problems experienced by the research team and other researchers who will conduct similar research. The method used in the development of multimedia content as facial expression datasets for human emotion recognition is the Villamil-Molina version of the multimedia development method. Multimedia content developed with 10 subjects or talents with each talent performing 3 shots with each capturing talent having to demonstrate 19 facial expressions. After the process of editing and rendering, tests are carried out with the conclusion that the multimedia content can be used as a facial expression dataset for recognition of human emotions.

Neurocognition and symptoms identify links between facial recognition and emotion processing in schizophrenia: Meta-analytic findings

PubMed Central

Ventura, Joseph; Wood, Rachel C.; Jimenez, Amy M.; Hellemann, Gerhard S.

2014-01-01

Background In schizophrenia patients, one of the most commonly studied deficits of social cognition is emotion processing (EP), which has documented links to facial recognition (FR). But, how are deficits in facial recognition linked to emotion processing deficits? Can neurocognitive and symptom correlates of FR and EP help differentiate the unique contribution of FR to the domain of social cognition? Methods A meta-analysis of 102 studies (combined n = 4826) in schizophrenia patients was conducted to determine the magnitude and pattern of relationships between facial recognition, emotion processing, neurocognition, and type of symptom. Results Meta-analytic results indicated that facial recognition and emotion processing are strongly interrelated (r = .51). In addition, the relationship between FR and EP through voice prosody (r = .58) is as strong as the relationship between FR and EP based on facial stimuli (r = .53). Further, the relationship between emotion recognition, neurocognition, and symptoms is independent of the emotion processing modality – facial stimuli and voice prosody. Discussion The association between FR and EP that occurs through voice prosody suggests that FR is a fundamental cognitive process. The observed links between FR and EP might be due to bottom-up associations between neurocognition and EP, and not simply because most emotion recognition tasks use visual facial stimuli. In addition, links with symptoms, especially negative symptoms and disorganization, suggest possible symptom mechanisms that contribute to FR and EP deficits. PMID:24268469

Neurocognition and symptoms identify links between facial recognition and emotion processing in schizophrenia: meta-analytic findings.

PubMed

Ventura, Joseph; Wood, Rachel C; Jimenez, Amy M; Hellemann, Gerhard S

2013-12-01

In schizophrenia patients, one of the most commonly studied deficits of social cognition is emotion processing (EP), which has documented links to facial recognition (FR). But, how are deficits in facial recognition linked to emotion processing deficits? Can neurocognitive and symptom correlates of FR and EP help differentiate the unique contribution of FR to the domain of social cognition? A meta-analysis of 102 studies (combined n=4826) in schizophrenia patients was conducted to determine the magnitude and pattern of relationships between facial recognition, emotion processing, neurocognition, and type of symptom. Meta-analytic results indicated that facial recognition and emotion processing are strongly interrelated (r=.51). In addition, the relationship between FR and EP through voice prosody (r=.58) is as strong as the relationship between FR and EP based on facial stimuli (r=.53). Further, the relationship between emotion recognition, neurocognition, and symptoms is independent of the emotion processing modality - facial stimuli and voice prosody. The association between FR and EP that occurs through voice prosody suggests that FR is a fundamental cognitive process. The observed links between FR and EP might be due to bottom-up associations between neurocognition and EP, and not simply because most emotion recognition tasks use visual facial stimuli. In addition, links with symptoms, especially negative symptoms and disorganization, suggest possible symptom mechanisms that contribute to FR and EP deficits. © 2013 Elsevier B.V. All rights reserved.

Facial emotion recognition in Williams syndrome and Down syndrome: A matching and developmental study.

PubMed

Martínez-Castilla, Pastora; Burt, Michael; Borgatti, Renato; Gagliardi, Chiara

2015-01-01

In this study both the matching and developmental trajectories approaches were used to clarify questions that remain open in the literature on facial emotion recognition in Williams syndrome (WS) and Down syndrome (DS). The matching approach showed that individuals with WS or DS exhibit neither proficiency for the expression of happiness nor specific impairments for negative emotions. Instead, they present the same pattern of emotion recognition as typically developing (TD) individuals. Thus, the better performance on the recognition of positive compared to negative emotions usually reported in WS and DS is not specific of these populations but seems to represent a typical pattern. Prior studies based on the matching approach suggested that the development of facial emotion recognition is delayed in WS and atypical in DS. Nevertheless, and even though performance levels were lower in DS than in WS, the developmental trajectories approach used in this study evidenced that not only individuals with DS but also those with WS present atypical development in facial emotion recognition. Unlike in the TD participants, where developmental changes were observed along with age, in the WS and DS groups, the development of facial emotion recognition was static. Both individuals with WS and those with DS reached an early maximum developmental level due to cognitive constraints.

Facial Expression Recognition using Multiclass Ensemble Least-Square Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Sya'Rani Machrizzandi, M.

2018-03-01

Facial expression is one of behavior characteristics of human-being. The use of biometrics technology system with facial expression characteristics makes it possible to recognize a person’s mood or emotion. The basic components of facial expression analysis system are face detection, face image extraction, facial classification and facial expressions recognition. This paper uses Principal Component Analysis (PCA) algorithm to extract facial features with expression parameters, i.e., happy, sad, neutral, angry, fear, and disgusted. Then Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM) is used for the classification process of facial expression. The result of MELS-SVM model obtained from our 185 different expression images of 10 persons showed high accuracy level of 99.998% using RBF kernel.

EMOTION RECOGNITION OF VIRTUAL AGENTS FACIAL EXPRESSIONS: THE EFFECTS OF AGE AND EMOTION INTENSITY

PubMed Central

Beer, Jenay M.; Fisk, Arthur D.; Rogers, Wendy A.

2014-01-01

People make determinations about the social characteristics of an agent (e.g., robot or virtual agent) by interpreting social cues displayed by the agent, such as facial expressions. Although a considerable amount of research has been conducted investigating age-related differences in emotion recognition of human faces (e.g., Sullivan, & Ruffman, 2004), the effect of age on emotion identification of virtual agent facial expressions has been largely unexplored. Age-related differences in emotion recognition of facial expressions are an important factor to consider in the design of agents that may assist older adults in a recreational or healthcare setting. The purpose of the current research was to investigate whether age-related differences in facial emotion recognition can extend to emotion-expressive virtual agents. Younger and older adults performed a recognition task with a virtual agent expressing six basic emotions. Larger age-related differences were expected for virtual agents displaying negative emotions, such as anger, sadness, and fear. In fact, the results indicated that older adults showed a decrease in emotion recognition accuracy for a virtual agent's emotions of anger, fear, and happiness. PMID:25552896

Proposal of Self-Learning and Recognition System of Facial Expression

NASA Astrophysics Data System (ADS)

Ogawa, Yukihiro; Kato, Kunihito; Yamamoto, Kazuhiko

We describe realization of more complicated function by using the information acquired from some equipped unripe functions. The self-learning and recognition system of the human facial expression, which achieved under the natural relation between human and robot, are proposed. The robot with this system can understand human facial expressions and behave according to their facial expressions after the completion of learning process. The system modelled after the process that a baby learns his/her parents’ facial expressions. Equipping the robot with a camera the system can get face images and equipping the CdS sensors on the robot’s head the robot can get the information of human action. Using the information of these sensors, the robot can get feature of each facial expression. After self-learning is completed, when a person changed his facial expression in front of the robot, the robot operates actions under the relevant facial expression.

Computer-Aided Recognition of Facial Attributes for Fetal Alcohol Spectrum Disorders.

PubMed

Valentine, Matthew; Bihm, Dustin C J; Wolf, Lior; Hoyme, H Eugene; May, Philip A; Buckley, David; Kalberg, Wendy; Abdul-Rahman, Omar A

2017-12-01

To compare the detection of facial attributes by computer-based facial recognition software of 2-D images against standard, manual examination in fetal alcohol spectrum disorders (FASD). Participants were gathered from the Fetal Alcohol Syndrome Epidemiology Research database. Standard frontal and oblique photographs of children were obtained during a manual, in-person dysmorphology assessment. Images were submitted for facial analysis conducted by the facial dysmorphology novel analysis technology (an automated system), which assesses ratios of measurements between various facial landmarks to determine the presence of dysmorphic features. Manual blinded dysmorphology assessments were compared with those obtained via the computer-aided system. Areas under the curve values for individual receiver-operating characteristic curves revealed the computer-aided system (0.88 ± 0.02) to be comparable to the manual method (0.86 ± 0.03) in detecting patients with FASD. Interestingly, cases of alcohol-related neurodevelopmental disorder (ARND) were identified more efficiently by the computer-aided system (0.84 ± 0.07) in comparison to the manual method (0.74 ± 0.04). A facial gestalt analysis of patients with ARND also identified more generalized facial findings compared to the cardinal facial features seen in more severe forms of FASD. We found there was an increased diagnostic accuracy for ARND via our computer-aided method. As this category has been historically difficult to diagnose, we believe our experiment demonstrates that facial dysmorphology novel analysis technology can potentially improve ARND diagnosis by introducing a standardized metric for recognizing FASD-associated facial anomalies. Earlier recognition of these patients will lead to earlier intervention with improved patient outcomes. Copyright © 2017 by the American Academy of Pediatrics.

Facial Emotion Recognition and Expression in Parkinson's Disease: An Emotional Mirror Mechanism?

PubMed

Ricciardi, Lucia; Visco-Comandini, Federica; Erro, Roberto; Morgante, Francesca; Bologna, Matteo; Fasano, Alfonso; Ricciardi, Diego; Edwards, Mark J; Kilner, James

2017-01-01

Parkinson's disease (PD) patients have impairment of facial expressivity (hypomimia) and difficulties in interpreting the emotional facial expressions produced by others, especially for aversive emotions. We aimed to evaluate the ability to produce facial emotional expressions and to recognize facial emotional expressions produced by others in a group of PD patients and a group of healthy participants in order to explore the relationship between these two abilities and any differences between the two groups of participants. Twenty non-demented, non-depressed PD patients and twenty healthy participants (HC) matched for demographic characteristics were studied. The ability of recognizing emotional facial expressions was assessed with the Ekman 60-faces test (Emotion recognition task). Participants were video-recorded while posing facial expressions of 6 primary emotions (happiness, sadness, surprise, disgust, fear and anger). The most expressive pictures for each emotion were derived from the videos. Ten healthy raters were asked to look at the pictures displayed on a computer-screen in pseudo-random fashion and to identify the emotional label in a six-forced-choice response format (Emotion expressivity task). Reaction time (RT) and accuracy of responses were recorded. At the end of each trial the participant was asked to rate his/her confidence in his/her perceived accuracy of response. For emotion recognition, PD reported lower score than HC for Ekman total score (p<0.001), and for single emotions sub-scores happiness, fear, anger, sadness (p<0.01) and surprise (p = 0.02). In the facial emotion expressivity task, PD and HC significantly differed in the total score (p = 0.05) and in the sub-scores for happiness, sadness, anger (all p<0.001). RT and the level of confidence showed significant differences between PD and HC for the same emotions. There was a significant positive correlation between the emotion facial recognition and expressivity in both groups; the

Iconic gestures prime related concepts: an ERP study.

PubMed

Wu, Ying Croon; Coulson, Seana

2007-02-01

To assess priming by iconic gestures, we recorded EEG (at 29 scalp sites) in two experiments while adults watched short, soundless videos of spontaneously produced, cospeech iconic gestures followed by related or unrelated probe words. In Experiment 1, participants classified the relatedness between gestures and words. In Experiment 2, they attended to stimuli, and performed an incidental recognition memory test on words presented during the EEG recording session. Event-related potentials (ERPs) time-locked to the onset of probe words were measured, along with response latencies and word recognition rates. Although word relatedness did not affect reaction times or recognition rates, contextually related probe words elicited less-negative ERPs than did unrelated ones between 300 and 500 msec after stimulus onset (N400) in both experiments. These findings demonstrate sensitivity to semantic relations between iconic gestures and words in brain activity engendered during word comprehension.

Robust representation and recognition of facial emotions using extreme sparse learning.

PubMed

Shojaeilangari, Seyedehsamaneh; Yau, Wei-Yun; Nandakumar, Karthik; Li, Jun; Teoh, Eam Khwang

2015-07-01

Recognition of natural emotions from human faces is an interesting topic with a wide range of potential applications, such as human-computer interaction, automated tutoring systems, image and video retrieval, smart environments, and driver warning systems. Traditionally, facial emotion recognition systems have been evaluated on laboratory controlled data, which is not representative of the environment faced in real-world applications. To robustly recognize the facial emotions in real-world natural situations, this paper proposes an approach called extreme sparse learning, which has the ability to jointly learn a dictionary (set of basis) and a nonlinear classification model. The proposed approach combines the discriminative power of extreme learning machine with the reconstruction property of sparse representation to enable accurate classification when presented with noisy signals and imperfect data recorded in natural settings. In addition, this paper presents a new local spatio-temporal descriptor that is distinctive and pose-invariant. The proposed framework is able to achieve the state-of-the-art recognition accuracy on both acted and spontaneous facial emotion databases.

CACNA1C risk variant affects facial emotion recognition in healthy individuals.

PubMed

Nieratschker, Vanessa; Brückmann, Christof; Plewnia, Christian

2015-11-27

Recognition and correct interpretation of facial emotion is essential for social interaction and communication. Previous studies have shown that impairments in this cognitive domain are common features of several psychiatric disorders. Recent association studies identified CACNA1C as one of the most promising genetic risk factors for psychiatric disorders and previous evidence suggests that the most replicated risk variant in CACNA1C (rs1006737) is affecting emotion recognition and processing. However, studies investigating the influence of rs1006737 on this intermediate phenotype in healthy subjects at the behavioral level are largely missing to date. Here, we applied the "Reading the Mind in the Eyes" test, a facial emotion recognition paradigm in a cohort of 92 healthy individuals to address this question. Whereas accuracy was not affected by genotype, CACNA1C rs1006737 risk-allele carries (AA/AG) showed significantly slower mean response times compared to individuals homozygous for the G-allele, indicating that healthy risk-allele carriers require more information to correctly identify a facial emotion. Our study is the first to provide evidence for an impairing behavioral effect of the CACNA1C risk variant rs1006737 on facial emotion recognition in healthy individuals and adds to the growing number of studies pointing towards CACNA1C as affecting intermediate phenotypes of psychiatric disorders.

Gesture Recognition and Sensorimotor Learning-by-Doing of Motor Skills in Manual Professions: A Case Study in the Wheel-Throwing Art of Pottery

ERIC Educational Resources Information Center

Glushkova, Alina; Manitsaris, Sotiris

2018-01-01

This paper presents a methodological framework for the use of gesture recognition technologies in the learning/mastery of the gestural skills required in wheel-throwing pottery. In the case of self-instruction or training, learners face difficulties due to the absence of the teacher/expert and the consequent lack of guidance. Motion capture…

Evidence for Anger Saliency during the Recognition of Chimeric Facial Expressions of Emotions in Underage Ebola Survivors

PubMed Central

Ardizzi, Martina; Evangelista, Valentina; Ferroni, Francesca; Umiltà, Maria A.; Ravera, Roberto; Gallese, Vittorio

2017-01-01

One of the crucial features defining basic emotions and their prototypical facial expressions is their value for survival. Childhood traumatic experiences affect the effective recognition of facial expressions of negative emotions, normally allowing the recruitment of adequate behavioral responses to environmental threats. Specifically, anger becomes an extraordinarily salient stimulus unbalancing victims’ recognition of negative emotions. Despite the plethora of studies on this topic, to date, it is not clear whether this phenomenon reflects an overall response tendency toward anger recognition or a selective proneness to the salience of specific facial expressive cues of anger after trauma exposure. To address this issue, a group of underage Sierra Leonean Ebola virus disease survivors (mean age 15.40 years, SE 0.35; years of schooling 8.8 years, SE 0.46; 14 males) and a control group (mean age 14.55, SE 0.30; years of schooling 8.07 years, SE 0.30, 15 males) performed a forced-choice chimeric facial expressions recognition task. The chimeric facial expressions were obtained pairing upper and lower half faces of two different negative emotions (selected from anger, fear and sadness for a total of six different combinations). Overall, results showed that upper facial expressive cues were more salient than lower facial expressive cues. This priority was lost among Ebola virus disease survivors for the chimeric facial expressions of anger. In this case, differently from controls, Ebola virus disease survivors recognized anger regardless of the upper or lower position of the facial expressive cues of this emotion. The present results demonstrate that victims’ performance in the recognition of the facial expression of anger does not reflect an overall response tendency toward anger recognition, but rather the specific greater salience of facial expressive cues of anger. Furthermore, the present results show that traumatic experiences deeply modify the perceptual

Evidence for Anger Saliency during the Recognition of Chimeric Facial Expressions of Emotions in Underage Ebola Survivors.

PubMed

Ardizzi, Martina; Evangelista, Valentina; Ferroni, Francesca; Umiltà, Maria A; Ravera, Roberto; Gallese, Vittorio

2017-01-01

One of the crucial features defining basic emotions and their prototypical facial expressions is their value for survival. Childhood traumatic experiences affect the effective recognition of facial expressions of negative emotions, normally allowing the recruitment of adequate behavioral responses to environmental threats. Specifically, anger becomes an extraordinarily salient stimulus unbalancing victims' recognition of negative emotions. Despite the plethora of studies on this topic, to date, it is not clear whether this phenomenon reflects an overall response tendency toward anger recognition or a selective proneness to the salience of specific facial expressive cues of anger after trauma exposure. To address this issue, a group of underage Sierra Leonean Ebola virus disease survivors (mean age 15.40 years, SE 0.35; years of schooling 8.8 years, SE 0.46; 14 males) and a control group (mean age 14.55, SE 0.30; years of schooling 8.07 years, SE 0.30, 15 males) performed a forced-choice chimeric facial expressions recognition task. The chimeric facial expressions were obtained pairing upper and lower half faces of two different negative emotions (selected from anger, fear and sadness for a total of six different combinations). Overall, results showed that upper facial expressive cues were more salient than lower facial expressive cues. This priority was lost among Ebola virus disease survivors for the chimeric facial expressions of anger. In this case, differently from controls, Ebola virus disease survivors recognized anger regardless of the upper or lower position of the facial expressive cues of this emotion. The present results demonstrate that victims' performance in the recognition of the facial expression of anger does not reflect an overall response tendency toward anger recognition, but rather the specific greater salience of facial expressive cues of anger. Furthermore, the present results show that traumatic experiences deeply modify the perceptual

Facial emotion recognition deficits in relatives of children with autism are not associated with 5HTTLPR.

PubMed

Neves, Maila de Castro Lourenço das; Tremeau, Fabien; Nicolato, Rodrigo; Lauar, Hélio; Romano-Silva, Marco Aurélio; Correa, Humberto

2011-09-01

A large body of evidence suggests that several aspects of face processing are impaired in autism and that this impairment might be hereditary. This study was aimed at assessing facial emotion recognition in parents of children with autism and its associations with a functional polymorphism of the serotonin transporter (5HTTLPR). We evaluated 40 parents of children with autism and 41 healthy controls. All participants were administered the Penn Emotion Recognition Test (ER40) and were genotyped for 5HTTLPR. Our study showed that parents of children with autism performed worse in the facial emotion recognition test than controls. Analyses of error patterns showed that parents of children with autism over-attributed neutral to emotional faces. We found evidence that 5HTTLPR polymorphism did not influence the performance in the Penn Emotion Recognition Test, but that it may determine different error patterns. Facial emotion recognition deficits are more common in first-degree relatives of autistic patients than in the general population, suggesting that facial emotion recognition is a candidate endophenotype for autism.

Modulation of α power and functional connectivity during facial affect recognition.

PubMed

Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte; Weisz, Nathan

2013-04-03

Research has linked oscillatory activity in the α frequency range, particularly in sensorimotor cortex, to processing of social actions. Results further suggest involvement of sensorimotor α in the processing of facial expressions, including affect. The sensorimotor face area may be critical for perception of emotional face expression, but the role it plays is unclear. The present study sought to clarify how oscillatory brain activity contributes to or reflects processing of facial affect during changes in facial expression. Neuromagnetic oscillatory brain activity was monitored while 30 volunteers viewed videos of human faces that changed their expression from neutral to fearful, neutral, or happy expressions. Induced changes in α power during the different morphs, source analysis, and graph-theoretic metrics served to identify the role of α power modulation and cross-regional coupling by means of phase synchrony during facial affect recognition. Changes from neutral to emotional faces were associated with a 10-15 Hz power increase localized in bilateral sensorimotor areas, together with occipital power decrease, preceding reported emotional expression recognition. Graph-theoretic analysis revealed that, in the course of a trial, the balance between sensorimotor power increase and decrease was associated with decreased and increased transregional connectedness as measured by node degree. Results suggest that modulations in α power facilitate early registration, with sensorimotor cortex including the sensorimotor face area largely functionally decoupled and thereby protected from additional, disruptive input and that subsequent α power decrease together with increased connectedness of sensorimotor areas facilitates successful facial affect recognition.

Deficits in Facial Emotion Recognition in Schizophrenia: A Replication Study with Korean Subjects

PubMed Central

Lee, Seung Jae; Lee, Hae-Kook; Kweon, Yong-Sil; Lee, Chung Tai

2010-01-01

Objective We investigated the deficit in the recognition of facial emotions in a sample of medicated, stable Korean patients with schizophrenia using Korean facial emotion pictures and examined whether the possible impairments would corroborate previous findings. Methods Fifty-five patients with schizophrenia and 62 healthy control subjects completed the Facial Affect Identification Test with a new set of 44 colored photographs of Korean faces including the six universal emotions as well as neutral faces. Results Korean patients with schizophrenia showed impairments in the recognition of sad, fearful, and angry faces [F(1,114)=6.26, p=0.014; F(1,114)=6.18, p=0.014; F(1,114)=9.28, p=0.003, respectively], but their accuracy was no different from that of controls in the recognition of happy emotions. Higher total and three subscale scores of the Positive and Negative Syndrome Scale (PANSS) correlated with worse performance on both angry and neutral faces. Correct responses on happy stimuli were negatively correlated with negative symptom scores of the PANSS. Patients with schizophrenia also exhibited different patterns of misidentification relative to normal controls. Conclusion These findings were consistent with previous studies carried out with different ethnic groups, suggesting cross-cultural similarities in facial recognition impairment in schizophrenia. PMID:21253414

Facial expression recognition based on weber local descriptor and sparse representation

NASA Astrophysics Data System (ADS)

Ouyang, Yan

2018-03-01

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

Discovering motion primitives for unsupervised grouping and one-shot learning of human actions, gestures, and expressions.

PubMed

Yang, Yang; Saleemi, Imran; Shah, Mubarak

2013-07-01

This paper proposes a novel representation of articulated human actions and gestures and facial expressions. The main goals of the proposed approach are: 1) to enable recognition using very few examples, i.e., one or k-shot learning, and 2) meaningful organization of unlabeled datasets by unsupervised clustering. Our proposed representation is obtained by automatically discovering high-level subactions or motion primitives, by hierarchical clustering of observed optical flow in four-dimensional, spatial, and motion flow space. The completely unsupervised proposed method, in contrast to state-of-the-art representations like bag of video words, provides a meaningful representation conducive to visual interpretation and textual labeling. Each primitive action depicts an atomic subaction, like directional motion of limb or torso, and is represented by a mixture of four-dimensional Gaussian distributions. For one--shot and k-shot learning, the sequence of primitive labels discovered in a test video are labeled using KL divergence, and can then be represented as a string and matched against similar strings of training videos. The same sequence can also be collapsed into a histogram of primitives or be used to learn a Hidden Markov model to represent classes. We have performed extensive experiments on recognition by one and k-shot learning as well as unsupervised action clustering on six human actions and gesture datasets, a composite dataset, and a database of facial expressions. These experiments confirm the validity and discriminative nature of the proposed representation.

Constructive autoassociative neural network for facial recognition.

PubMed

Fernandes, Bruno J T; Cavalcanti, George D C; Ren, Tsang I

2014-01-01

Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.

Facial recognition software success rates for the identification of 3D surface reconstructed facial images: implications for patient privacy and security.

PubMed

Mazura, Jan C; Juluru, Krishna; Chen, Joseph J; Morgan, Tara A; John, Majnu; Siegel, Eliot L

2012-06-01

Image de-identification has focused on the removal of textual protected health information (PHI). Surface reconstructions of the face have the potential to reveal a subject's identity even when textual PHI is absent. This study assessed the ability of a computer application to match research subjects' 3D facial reconstructions with conventional photographs of their face. In a prospective study, 29 subjects underwent CT scans of the head and had frontal digital photographs of their face taken. Facial reconstructions of each CT dataset were generated on a 3D workstation. In phase 1, photographs of the 29 subjects undergoing CT scans were added to a digital directory and tested for recognition using facial recognition software. In phases 2-4, additional photographs were added in groups of 50 to increase the pool of possible matches and the test for recognition was repeated. As an internal control, photographs of all subjects were tested for recognition against an identical photograph. Of 3D reconstructions, 27.5% were matched correctly to corresponding photographs (95% upper CL, 40.1%). All study subject photographs were matched correctly to identical photographs (95% lower CL, 88.6%). Of 3D reconstructions, 96.6% were recognized simply as a face by the software (95% lower CL, 83.5%). Facial recognition software has the potential to recognize features on 3D CT surface reconstructions and match these with photographs, with implications for PHI.

Individual differences in the recognition of facial expressions: an event-related potentials study.

PubMed

Tamamiya, Yoshiyuki; Hiraki, Kazuo

2013-01-01

Previous studies have shown that early posterior components of event-related potentials (ERPs) are modulated by facial expressions. The goal of the current study was to investigate individual differences in the recognition of facial expressions by examining the relationship between ERP components and the discrimination of facial expressions. Pictures of 3 facial expressions (angry, happy, and neutral) were presented to 36 young adults during ERP recording. Participants were asked to respond with a button press as soon as they recognized the expression depicted. A multiple regression analysis, where ERP components were set as predictor variables, assessed hits and reaction times in response to the facial expressions as dependent variables. The N170 amplitudes significantly predicted for accuracy of angry and happy expressions, and the N170 latencies were predictive for accuracy of neutral expressions. The P2 amplitudes significantly predicted reaction time. The P2 latencies significantly predicted reaction times only for neutral faces. These results suggest that individual differences in the recognition of facial expressions emerge from early components in visual processing.

The familial basis of facial emotion recognition deficits in adolescents with conduct disorder and their unaffected relatives.

PubMed

Sully, K; Sonuga-Barke, E J S; Fairchild, G

2015-07-01

There is accumulating evidence of impairments in facial emotion recognition in adolescents with conduct disorder (CD). However, the majority of studies in this area have only been able to demonstrate an association, rather than a causal link, between emotion recognition deficits and CD. To move closer towards understanding the causal pathways linking emotion recognition problems with CD, we studied emotion recognition in the unaffected first-degree relatives of CD probands, as well as those with a diagnosis of CD. Using a family-based design, we investigated facial emotion recognition in probands with CD (n = 43), their unaffected relatives (n = 21), and healthy controls (n = 38). We used the Emotion Hexagon task, an alternative forced-choice task using morphed facial expressions depicting the six primary emotions, to assess facial emotion recognition accuracy. Relative to controls, the CD group showed impaired recognition of anger, fear, happiness, sadness and surprise (all p < 0.005). Similar to probands with CD, unaffected relatives showed deficits in anger and happiness recognition relative to controls (all p < 0.008), with a trend toward a deficit in fear recognition. There were no significant differences in performance between the CD probands and the unaffected relatives following correction for multiple comparisons. These results suggest that facial emotion recognition deficits are present in adolescents who are at increased familial risk for developing antisocial behaviour, as well as those who have already developed CD. Consequently, impaired emotion recognition appears to be a viable familial risk marker or candidate endophenotype for CD.

Facial emotion recognition, face scan paths, and face perception in children with neurofibromatosis type 1.

PubMed

Lewis, Amelia K; Porter, Melanie A; Williams, Tracey A; Bzishvili, Samantha; North, Kathryn N; Payne, Jonathan M

2017-05-01

This study aimed to investigate face scan paths and face perception abilities in children with Neurofibromatosis Type 1 (NF1) and how these might relate to emotion recognition abilities in this population. The authors investigated facial emotion recognition, face scan paths, and face perception in 29 children with NF1 compared to 29 chronological age-matched typically developing controls. Correlations between facial emotion recognition, face scan paths, and face perception in children with NF1 were examined. Children with NF1 displayed significantly poorer recognition of fearful expressions compared to controls, as well as a nonsignificant trend toward poorer recognition of anger. Although there was no significant difference between groups in time spent viewing individual core facial features (eyes, nose, mouth, and nonfeature regions), children with NF1 spent significantly less time than controls viewing the face as a whole. Children with NF1 also displayed significantly poorer face perception abilities than typically developing controls. Facial emotion recognition deficits were not significantly associated with aberrant face scan paths or face perception abilities in the NF1 group. These results suggest that impairments in the perception, identification, and interpretation of information from faces are important aspects of the social-cognitive phenotype of NF1. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Violent media consumption and the recognition of dynamic facial expressions.

PubMed

Kirsh, Steven J; Mounts, Jeffrey R W; Olczak, Paul V

2006-05-01

This study assessed the speed of recognition of facial emotional expressions (happy and angry) as a function of violent media consumption. Color photos of calm facial expressions morphed to either an angry or a happy facial expression. Participants were asked to make a speeded identification of the emotion (happiness or anger) during the morph. Results indicated that, independent of trait aggressiveness, participants high in violent media consumption responded slower to depictions of happiness and faster to depictions of anger than participants low in violent media consumption. Implications of these findings are discussed with respect to current models of aggressive behavior.

Role of temporal processing stages by inferior temporal neurons in facial recognition.

PubMed

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

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition.

Role of Temporal Processing Stages by Inferior Temporal Neurons in Facial Recognition

PubMed Central

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

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition

Investigation of facial emotion recognition, alexithymia, and levels of anxiety and depression in patients with somatic symptoms and related disorders

PubMed Central

Öztürk, Ahmet; Kiliç, Alperen; Deveci, Erdem; Kirpinar, İsmet

2016-01-01

Background The concept of facial emotion recognition is well established in various neuropsychiatric disorders. Although emotional disturbances are strongly associated with somatoform disorders, there are a restricted number of studies that have investigated facial emotion recognition in somatoform disorders. Furthermore, there have been no studies that have regarded this issue using the new diagnostic criteria for somatoform disorders as somatic symptoms and related disorders (SSD). In this study, we aimed to compare the factors of facial emotion recognition between patients with SSD and age- and sex-matched healthy controls (HC) and to retest and investigate the factors of facial emotion recognition using the new criteria for SSD. Patients and methods After applying the inclusion and exclusion criteria, 54 patients who were diagnosed with SSD according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria and 46 age- and sex-matched HC were selected to participate in the present study. Facial emotion recognition, alexithymia, and the status of anxiety and depression were compared between the groups. Results Patients with SSD had significantly decreased scores of facial emotion for fear faces, disgust faces, and neutral faces compared with age- and sex-matched HC (t=−2.88, P=0.005; t=−2.86, P=0.005; and t=−2.56, P=0.009, respectively). After eliminating the effects of alexithymia and depressive and anxious states, the groups were found to be similar in terms of their responses to facial emotion and mean reaction time to facial emotions. Discussion Although there have been limited numbers of studies that have examined the recognition of facial emotion in patients with somatoform disorders, our study is the first to investigate facial recognition in patients with SSD diagnosed according to the DSM-5 criteria. Recognition of facial emotion was found to be disturbed in patients with SSD. However, our findings suggest that

Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

PubMed

Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

2014-06-03

Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

Hybrid Feature Extraction-based Approach for Facial Parts Representation and Recognition

NASA Astrophysics Data System (ADS)

Rouabhia, C.; Tebbikh, H.

2008-06-01

Face recognition is a specialized image processing which has attracted a considerable attention in computer vision. In this article, we develop a new facial recognition system from video sequences images dedicated to person identification whose face is partly occulted. This system is based on a hybrid image feature extraction technique called ACPDL2D (Rouabhia et al. 2007), it combines two-dimensional principal component analysis and two-dimensional linear discriminant analysis with neural network. We performed the feature extraction task on the eyes and the nose images separately then a Multi-Layers Perceptron classifier is used. Compared to the whole face, the results of simulation are in favor of the facial parts in terms of memory capacity and recognition (99.41% for the eyes part, 98.16% for the nose part and 97.25 % for the whole face).

Facial Emotion Recognition and Expression in Parkinson’s Disease: An Emotional Mirror Mechanism?

PubMed Central

Ricciardi, Lucia; Visco-Comandini, Federica; Erro, Roberto; Morgante, Francesca; Bologna, Matteo; Fasano, Alfonso; Ricciardi, Diego; Edwards, Mark J.; Kilner, James

2017-01-01

Background and aim Parkinson’s disease (PD) patients have impairment of facial expressivity (hypomimia) and difficulties in interpreting the emotional facial expressions produced by others, especially for aversive emotions. We aimed to evaluate the ability to produce facial emotional expressions and to recognize facial emotional expressions produced by others in a group of PD patients and a group of healthy participants in order to explore the relationship between these two abilities and any differences between the two groups of participants. Methods Twenty non-demented, non-depressed PD patients and twenty healthy participants (HC) matched for demographic characteristics were studied. The ability of recognizing emotional facial expressions was assessed with the Ekman 60-faces test (Emotion recognition task). Participants were video-recorded while posing facial expressions of 6 primary emotions (happiness, sadness, surprise, disgust, fear and anger). The most expressive pictures for each emotion were derived from the videos. Ten healthy raters were asked to look at the pictures displayed on a computer-screen in pseudo-random fashion and to identify the emotional label in a six-forced-choice response format (Emotion expressivity task). Reaction time (RT) and accuracy of responses were recorded. At the end of each trial the participant was asked to rate his/her confidence in his/her perceived accuracy of response. Results For emotion recognition, PD reported lower score than HC for Ekman total score (p<0.001), and for single emotions sub-scores happiness, fear, anger, sadness (p<0.01) and surprise (p = 0.02). In the facial emotion expressivity task, PD and HC significantly differed in the total score (p = 0.05) and in the sub-scores for happiness, sadness, anger (all p<0.001). RT and the level of confidence showed significant differences between PD and HC for the same emotions. There was a significant positive correlation between the emotion facial recognition and

Facial Expression Influences Face Identity Recognition During the Attentional Blink

PubMed Central

2014-01-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another. PMID:25286076

Facial expression influences face identity recognition during the attentional blink.

PubMed

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

2014-12-01

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

Age Deficits in Facial Affect Recognition: The Influence of Dynamic Cues.

PubMed

Grainger, Sarah A; Henry, Julie D; Phillips, Louise H; Vanman, Eric J; Allen, Roy

2017-07-01

Older adults have difficulties in identifying most facial expressions of emotion. However, most aging studies have presented static photographs of intense expressions, whereas in everyday experience people see emotions that develop and change. The present study was designed to assess whether age-related difficulties with emotion recognition are reduced when more ecologically valid (i.e., dynamic) stimuli are used. We examined the effect of stimuli format (i.e., static vs. dynamic) on facial affect recognition in two separate studies that included independent samples and distinct stimuli sets. In addition to younger and older participants, a middle-aged group was included in Study 1 and eye gaze patterns were assessed in Study 2. Across both studies, older adults performed worse than younger adults on measures of facial affect recognition. In Study 1, older and-middle aged adults benefited from dynamic stimuli, but only when the emotional displays were subtle. Younger adults gazed more at the eye region of the face relative to older adults (Study 2), but dynamic presentation increased attention towards the eye region for younger adults only. Together, these studies provide important and novel insights into the specific circumstances in which older adults may be expected to experience difficulties in perceiving facial emotions. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

In-the-wild facial expression recognition in extreme poses

NASA Astrophysics Data System (ADS)

Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

The relationship between facial emotion recognition and executive functions in first-episode patients with schizophrenia and their siblings.

PubMed

Yang, Chengqing; Zhang, Tianhong; Li, Zezhi; Heeramun-Aubeeluck, Anisha; Liu, Na; Huang, Nan; Zhang, Jie; He, Leiying; Li, Hui; Tang, Yingying; Chen, Fazhan; Liu, Fei; Wang, Jijun; Lu, Zheng

2015-10-08

Although many studies have examined executive functions and facial emotion recognition in people with schizophrenia, few of them focused on the correlation between them. Furthermore, their relationship in the siblings of patients also remains unclear. The aim of the present study is to examine the correlation between executive functions and facial emotion recognition in patients with first-episode schizophrenia and their siblings. Thirty patients with first-episode schizophrenia, their twenty-six siblings, and thirty healthy controls were enrolled. They completed facial emotion recognition tasks using the Ekman Standard Faces Database, and executive functioning was measured by Wisconsin Card Sorting Test (WCST). Hierarchical regression analysis was applied to assess the correlation between executive functions and facial emotion recognition. Our study found that in siblings, the accuracy in recognizing low degree 'disgust' emotion was negatively correlated with the total correct rate in WCST (r = -0.614, p = 0.023), but was positively correlated with the total error in WCST (r = 0.623, p = 0.020); the accuracy in recognizing 'neutral' emotion was positively correlated with the total error rate in WCST (r = 0.683, p = 0.014) while negatively correlated with the total correct rate in WCST (r = -0.677, p = 0.017). People with schizophrenia showed an impairment in facial emotion recognition when identifying moderate 'happy' facial emotion, the accuracy of which was significantly correlated with the number of completed categories of WCST (R(2) = 0.432, P < .05). There were no correlations between executive functions and facial emotion recognition in the healthy control group. Our study demonstrated that facial emotion recognition impairment correlated with executive function impairment in people with schizophrenia and their unaffected siblings but not in healthy controls.

Interference with facial emotion recognition by verbal but not visual loads.

PubMed

Reed, Phil; Steed, Ian

2015-12-01

The ability to recognize emotions through facial characteristics is critical for social functioning, but is often impaired in those with a developmental or intellectual disability. The current experiments explored the degree to which interfering with the processing capacities of typically-developing individuals would produce a similar inability to recognize emotions through the facial elements of faces displaying particular emotions. It was found that increasing the cognitive load (in an attempt to model learning impairments in a typically developing population) produced deficits in correctly identifying emotions from facial elements. However, this effect was much more pronounced when using a concurrent verbal task than when employing a concurrent visual task, suggesting that there is a substantial verbal element to the labeling and subsequent recognition of emotions. This concurs with previous work conducted with those with developmental disabilities that suggests emotion recognition deficits are connected with language deficits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fashioning the Face: Sensorimotor Simulation Contributes to Facial Expression Recognition.

PubMed

Wood, Adrienne; Rychlowska, Magdalena; Korb, Sebastian; Niedenthal, Paula

2016-03-01

When we observe a facial expression of emotion, we often mimic it. This automatic mimicry reflects underlying sensorimotor simulation that supports accurate emotion recognition. Why this is so is becoming more obvious: emotions are patterns of expressive, behavioral, physiological, and subjective feeling responses. Activation of one component can therefore automatically activate other components. When people simulate a perceived facial expression, they partially activate the corresponding emotional state in themselves, which provides a basis for inferring the underlying emotion of the expresser. We integrate recent evidence in favor of a role for sensorimotor simulation in emotion recognition. We then connect this account to a domain-general understanding of how sensory information from multiple modalities is integrated to generate perceptual predictions in the brain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impairment of facial recognition in patients with right cerebral infarcts quantified by computer aided "morphing".

PubMed Central

Rösler, A; Lanquillon, S; Dippel, O; Braune, H J

1997-01-01

OBJECTIVE: To investigate where facial recognition is located anatomically and to establish whether there is a graded transition from unimpaired recognition of faces to complete prosopagnosia after infarctions in the territory of the middle cerebral artery. METHODS: A computerised morphing program was developed which shows 30 frames gradually changing from portrait photographs of unfamiliar persons to those of well known persons. With a standardised protocol, 31 patients with right and left sided infarctions in the territory of the middle cerebral artery and an age and sex matched control group were compared by non-parametric tests. RESULTS AND CONCLUSION: Facial recognition in patients with right sided lesions was significantly impaired compared with controls and with patients with left sided lesions. A graded impairment in facial recognition in patients with right sided ischaemic infarcts in the territory of the middle cerebral artery seems to exist. Images PMID:9069481

Autonomic imbalance is associated with reduced facial recognition in somatoform disorders.

PubMed

Pollatos, Olga; Herbert, Beate M; Wankner, Sarah; Dietel, Anja; Wachsmuth, Cornelia; Henningsen, Peter; Sack, Martin

2011-10-01

Somatoform disorders are characterized by the presence of multiple somatic symptoms. While the accuracy of perceiving bodily signal (interoceptive awareness) is only sparely investigated in somatoform disorders, recent research has associated autonomic imbalance with cognitive and emotional difficulties in stress-related diseases. This study aimed to investigate how sympathovagal reactivity interacts with performance in recognizing emotions in faces (facial recognition task). Using a facial recognition and appraisal task, skin conductance levels (SCLs), heart rate (HR) and heart rate variability (HRV) were assessed in 26 somatoform patients and compared to healthy controls. Interoceptive awareness was assessed by a heartbeat detection task. We found evidence for a sympathovagal imbalance in somatoform disorders characterized by low parasympathetic reactivity during emotional tasks and increased sympathetic activation during baseline. Somatoform patients exhibited a reduced recognition performance for neutral and sad emotional expressions only. Possible confounding variables such as alexithymia, anxiety or depression were taken into account. Interoceptive awareness was reduced in somatoform patients. Our data demonstrate an imbalance in sympathovagal activation in somatoform disorders associated with decreased parasympathetic activation. This might account for difficulties in processing of sad and neutral facial expressions in somatoform patients which might be a pathogenic mechanism for increased everyday vulnerability. Copyright © 2011 Elsevier Inc. All rights reserved.

Facial emotion recognition and sleep in mentally disordered patients: A natural experiment in a high security hospital.

PubMed

Chu, Simon; McNeill, Kimberley; Ireland, Jane L; Qurashi, Inti

2015-12-15

We investigated the relationship between a change in sleep quality and facial emotion recognition accuracy in a group of mentally-disordered inpatients at a secure forensic psychiatric unit. Patients whose sleep improved over time also showed improved facial emotion recognition while patients who showed no sleep improvement showed no change in emotion recognition. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Recognition of facial and musical emotions in Parkinson's disease.

PubMed

Saenz, A; Doé de Maindreville, A; Henry, A; de Labbey, S; Bakchine, S; Ehrlé, N

2013-03-01

Patients with amygdala lesions were found to be impaired in recognizing the fear emotion both from face and from music. In patients with Parkinson's disease (PD), impairment in recognition of emotions from facial expressions was reported for disgust, fear, sadness and anger, but no studies had yet investigated this population for the recognition of emotions from both face and music. The ability to recognize basic universal emotions (fear, happiness and sadness) from both face and music was investigated in 24 medicated patients with PD and 24 healthy controls. The patient group was tested for language (verbal fluency tasks), memory (digit and spatial span), executive functions (Similarities and Picture Completion subtests of the WAIS III, Brixton and Stroop tests), visual attention (Bells test), and fulfilled self-assessment tests for anxiety and depression. Results showed that the PD group was significantly impaired for recognition of both fear and sadness emotions from facial expressions, whereas their performance in recognition of emotions from musical excerpts was not different from that of the control group. The scores of fear and sadness recognition from faces were neither correlated to scores in tests for executive and cognitive functions, nor to scores in self-assessment scales. We attributed the observed dissociation to the modality (visual vs. auditory) of presentation and to the ecological value of the musical stimuli that we used. We discuss the relevance of our findings for the care of patients with PD. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

Effects of exposure to facial expression variation in face learning and recognition.

PubMed

Liu, Chang Hong; Chen, Wenfeng; Ward, James

2015-11-01

Facial expression is a major source of image variation in face images. Linking numerous expressions to the same face can be a huge challenge for face learning and recognition. It remains largely unknown what level of exposure to this image variation is critical for expression-invariant face recognition. We examined this issue in a recognition memory task, where the number of facial expressions of each face being exposed during a training session was manipulated. Faces were either trained with multiple expressions or a single expression, and they were later tested in either the same or different expressions. We found that recognition performance after learning three emotional expressions had no improvement over learning a single emotional expression (Experiments 1 and 2). However, learning three emotional expressions improved recognition compared to learning a single neutral expression (Experiment 3). These findings reveal both the limitation and the benefit of multiple exposures to variations of emotional expression in achieving expression-invariant face recognition. The transfer of expression training to a new type of expression is likely to depend on a relatively extensive level of training and a certain degree of variation across the types of expressions.

The effect of comorbid depression on facial and prosody emotion recognition in first-episode schizophrenia spectrum.

PubMed

Herniman, Sarah E; Allott, Kelly A; Killackey, Eóin; Hester, Robert; Cotton, Sue M

2017-01-15

Comorbid depression is common in first-episode schizophrenia spectrum (FES) disorders. Both depression and FES are associated with significant deficits in facial and prosody emotion recognition performance. However, it remains unclear whether people with FES and comorbid depression, compared to those without comorbid depression, have overall poorer emotion recognition, or instead, a different pattern of emotion recognition deficits. The aim of this study was to compare facial and prosody emotion recognition performance between those with and without comorbid depression in FES. This study involved secondary analysis of baseline data from a randomized controlled trial of vocational intervention for young people with first-episode psychosis (N=82; age range: 15-25 years). Those with comorbid depression (n=24) had more accurate recognition of sadness in faces compared to those without comorbid depression. Severity of depressive symptoms was also associated with more accurate recognition of sadness in faces. Such results did not recur for prosody emotion recognition. In addition to the cross-sectional design, limitations of this study include the absence of facial and prosodic recognition of neutral emotions. Findings indicate a mood congruent negative bias in facial emotion recognition in those with comorbid depression and FES, and provide support for cognitive theories of depression that emphasise the role of such biases in the development and maintenance of depression. Longitudinal research is needed to determine whether mood-congruent negative biases are implicated in the development and maintenance of depression in FES, or whether such biases are simply markers of depressed state. Copyright © 2016 Elsevier B.V. All rights reserved.

Coronary Heart Disease Preoperative Gesture Interactive Diagnostic System Based on Augmented Reality.

PubMed

Zou, Yi-Bo; Chen, Yi-Min; Gao, Ming-Ke; Liu, Quan; Jiang, Si-Yu; Lu, Jia-Hui; Huang, Chen; Li, Ze-Yu; Zhang, Dian-Hua

2017-08-01

Coronary heart disease preoperative diagnosis plays an important role in the treatment of vascular interventional surgery. Actually, most doctors are used to diagnosing the position of the vascular stenosis and then empirically estimating vascular stenosis by selective coronary angiography images instead of using mouse, keyboard and computer during preoperative diagnosis. The invasive diagnostic modality is short of intuitive and natural interaction and the results are not accurate enough. Aiming at above problems, the coronary heart disease preoperative gesture interactive diagnostic system based on Augmented Reality is proposed. The system uses Leap Motion Controller to capture hand gesture video sequences and extract the features which that are the position and orientation vector of the gesture motion trajectory and the change of the hand shape. The training planet is determined by K-means algorithm and then the effect of gesture training is improved by multi-features and multi-observation sequences for gesture training. The reusability of gesture is improved by establishing the state transition model. The algorithm efficiency is improved by gesture prejudgment which is used by threshold discriminating before recognition. The integrity of the trajectory is preserved and the gesture motion space is extended by employing space rotation transformation of gesture manipulation plane. Ultimately, the gesture recognition based on SRT-HMM is realized. The diagnosis and measurement of the vascular stenosis are intuitively and naturally realized by operating and measuring the coronary artery model with augmented reality and gesture interaction techniques. All of the gesture recognition experiments show the distinguish ability and generalization ability of the algorithm and gesture interaction experiments prove the availability and reliability of the system.

Influence of Emotional Facial Expressions on 3-5-Year-Olds' Face Recognition

ERIC Educational Resources Information Center

Freitag, Claudia; Schwarzer, Gudrun

2011-01-01

Three experiments examined 3- and 5-year-olds' recognition of faces in constant and varied emotional expressions. Children were asked to identify repeatedly presented target faces, distinguishing them from distractor faces, during an immediate recognition test and during delayed assessments after 10 min and one week. Emotional facial expression…

Detecting facial emotion recognition deficits in schizophrenia using dynamic stimuli of varying intensities.

PubMed

Hargreaves, A; Mothersill, O; Anderson, M; Lawless, S; Corvin, A; Donohoe, G

2016-10-28

Deficits in facial emotion recognition have been associated with functional impairments in patients with Schizophrenia (SZ). Whilst a strong ecological argument has been made for the use of both dynamic facial expressions and varied emotion intensities in research, SZ emotion recognition studies to date have primarily used static stimuli of a singular, 100%, intensity of emotion. To address this issue, the present study aimed to investigate accuracy of emotion recognition amongst patients with SZ and healthy subjects using dynamic facial emotion stimuli of varying intensities. To this end an emotion recognition task (ERT) designed by Montagne (2007) was adapted and employed. 47 patients with a DSM-IV diagnosis of SZ and 51 healthy participants were assessed for emotion recognition. Results of the ERT were tested for correlation with performance in areas of cognitive ability typically found to be impaired in psychosis, including IQ, memory, attention and social cognition. Patients were found to perform less well than healthy participants at recognising each of the 6 emotions analysed. Surprisingly, however, groups did not differ in terms of impact of emotion intensity on recognition accuracy; for both groups higher intensity levels predicted greater accuracy, but no significant interaction between diagnosis and emotional intensity was found for any of the 6 emotions. Accuracy of emotion recognition was, however, more strongly correlated with cognition in the patient cohort. Whilst this study demonstrates the feasibility of using ecologically valid dynamic stimuli in the study of emotion recognition accuracy, varying the intensity of the emotion displayed was not demonstrated to impact patients and healthy participants differentially, and thus may not be a necessary variable to include in emotion recognition research. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Facial emotion recognition in Parkinson's disease: A review and new hypotheses

PubMed Central

Vérin, Marc; Sauleau, Paul; Grandjean, Didier

2018-01-01

Abstract Parkinson's disease is a neurodegenerative disorder classically characterized by motor symptoms. Among them, hypomimia affects facial expressiveness and social communication and has a highly negative impact on patients' and relatives' quality of life. Patients also frequently experience nonmotor symptoms, including emotional‐processing impairments, leading to difficulty in recognizing emotions from faces. Aside from its theoretical importance, understanding the disruption of facial emotion recognition in PD is crucial for improving quality of life for both patients and caregivers, as this impairment is associated with heightened interpersonal difficulties. However, studies assessing abilities in recognizing facial emotions in PD still report contradictory outcomes. The origins of this inconsistency are unclear, and several questions (regarding the role of dopamine replacement therapy or the possible consequences of hypomimia) remain unanswered. We therefore undertook a fresh review of relevant articles focusing on facial emotion recognition in PD to deepen current understanding of this nonmotor feature, exploring multiple significant potential confounding factors, both clinical and methodological, and discussing probable pathophysiological mechanisms. This led us to examine recent proposals about the role of basal ganglia‐based circuits in emotion and to consider the involvement of facial mimicry in this deficit from the perspective of embodied simulation theory. We believe our findings will inform clinical practice and increase fundamental knowledge, particularly in relation to potential embodied emotion impairment in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. PMID:29473661

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

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

Are there differential deficits in facial emotion recognition between paranoid and non-paranoid schizophrenia? A signal detection analysis.

PubMed

Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2013-10-30

This study assessed facial emotion recognition abilities in subjects with paranoid and non-paranoid schizophrenia (NPS) using signal detection theory. We explore the differential deficits in facial emotion recognition in 44 paranoid patients with schizophrenia (PS) and 30 non-paranoid patients with schizophrenia (NPS), compared to 80 healthy controls. We used morphed faces with different intensities of emotion and computed the sensitivity index (d') of each emotion. The results showed that performance differed between the schizophrenia and healthy controls groups in the recognition of both negative and positive affects. The PS group performed worse than the healthy controls group but better than the NPS group in overall performance. Performance differed between the NPS and healthy controls groups in the recognition of all basic emotions and neutral faces; between the PS and healthy controls groups in the recognition of angry faces; and between the PS and NPS groups in the recognition of happiness, anger, sadness, disgust, and neutral affects. The facial emotion recognition impairment in schizophrenia may reflect a generalized deficit rather than a negative-emotion specific deficit. The PS group performed worse than the control group, but better than the NPS group in facial expression recognition, with differential deficits between PS and NPS patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Facial Emotion Recognition by Persons with Mental Retardation: A Review of the Experimental Literature.

ERIC Educational Resources Information Center

Rojahn, Johannes; And Others

1995-01-01

This literature review discusses 21 studies on facial emotion recognition by persons with mental retardation in terms of methodological characteristics, stimulus material, salient variables and their relation to recognition tasks, and emotion recognition deficits in mental retardation. A table provides comparative data on all 21 studies. (DB)

Developmental prosopagnosia and the Benton Facial Recognition Test.

PubMed

Duchaine, Bradley C; Nakayama, Ken

2004-04-13

The Benton Facial Recognition Test is used for clinical and research purposes, but evidence suggests that it is possible to pass the test with impaired face discrimination abilities. The authors tested 11 patients with developmental prosopagnosia using this test, and a majority scored in the normal range. Consequently, scores in the normal range should be interpreted cautiously, and testing should always be supplemented by other face tests.

Pervasive influence of idiosyncratic associative biases during facial emotion recognition.

PubMed

El Zein, Marwa; Wyart, Valentin; Grèzes, Julie

2018-06-11

Facial morphology has been shown to influence perceptual judgments of emotion in a way that is shared across human observers. Here we demonstrate that these shared associations between facial morphology and emotion coexist with strong variations unique to each human observer. Interestingly, a large part of these idiosyncratic associations does not vary on short time scales, emerging from stable inter-individual differences in the way facial morphological features influence emotion recognition. Computational modelling of decision-making and neural recordings of electrical brain activity revealed that both shared and idiosyncratic face-emotion associations operate through a common biasing mechanism rather than an increased sensitivity to face-associated emotions. Together, these findings emphasize the underestimated influence of idiosyncrasies on core social judgments and identify their neuro-computational signatures.

The Relation of Facial Affect Recognition and Empathy to Delinquency in Youth Offenders

ERIC Educational Resources Information Center

Carr, Mary B.; Lutjemeier, John A.

2005-01-01

Associations among facial affect recognition, empathy, and self-reported delinquency were studied in a sample of 29 male youth offenders at a probation placement facility. Youth offenders were asked to recognize facial expressions of emotions from adult faces, child faces, and cartoon faces. Youth offenders also responded to a series of statements…

Gestural interaction in a virtual environment

NASA Astrophysics Data System (ADS)

Jacoby, Richard H.; Ferneau, Mark; Humphries, Jim

1994-04-01

This paper discusses the use of hand gestures (i.e., changing finger flexion) within a virtual environment (VE). Many systems now employ static hand postures (i.e., static finger flexion), often coupled with hand translations and rotations, as a method of interacting with a VE. However, few systems are currently using dynamically changing finger flexion for interacting with VEs. In our system, the user wears an electronically instrumented glove. We have developed a simple algorithm for recognizing gestures for use in two applications: automotive design and visualization of atmospheric data. In addition to recognizing the gestures, we also calculate the rate at which the gestures are made and the rate and direction of hand movement while making the gestures. We report on our experiences with the algorithm design and implementation, and the use of the gestures in our applications. We also talk about our background work in user calibration of the glove, as well as learned and innate posture recognition (postures recognized with and without training, respectively).

Facial recognition: a cognitive study of elderly dementia patients and normal older adults.

PubMed

Zandi, T; Cooper, M; Garrison, L

1992-01-01

Dementia patients' and normal elderlies' recognition of familiar, ordinary emotional and facial expressions was tested. In three conditions subjects were required to name the emotions depicted in pictures and to produce them while presented with the verbal labels of the expressions. The dementia patients' best performance occurred when they had access to the verbal labels while viewing the pictures. The major deficiency in facial recognition was found to be dysnomia related. Findings of this study suggest that the connection between the gnostic units of expression and the gnostic units of verbal labeling is not impaired significantly among the dementia patients.

Local intensity area descriptor for facial recognition in ideal and noise conditions

NASA Astrophysics Data System (ADS)

Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

The Emotional Modulation of Facial Mimicry: A Kinematic Study.

PubMed

Tramacere, Antonella; Ferrari, Pier F; Gentilucci, Maurizio; Giuffrida, Valeria; De Marco, Doriana

2017-01-01

It is well-established that the observation of emotional facial expression induces facial mimicry responses in the observers. However, how the interaction between emotional and motor components of facial expressions can modulate the motor behavior of the perceiver is still unknown. We have developed a kinematic experiment to evaluate the effect of different oro-facial expressions on perceiver's face movements. Participants were asked to perform two movements, i.e., lip stretching and lip protrusion, in response to the observation of four meaningful (i.e., smile, angry-mouth, kiss, and spit) and two meaningless mouth gestures. All the stimuli were characterized by different motor patterns (mouth aperture or mouth closure). Response Times and kinematics parameters of the movements (amplitude, duration, and mean velocity) were recorded and analyzed. Results evidenced a dissociated effect on reaction times and movement kinematics. We found shorter reaction time when a mouth movement was preceded by the observation of a meaningful and motorically congruent oro-facial gesture, in line with facial mimicry effect. On the contrary, during execution, the perception of smile was associated with the facilitation, in terms of shorter duration and higher velocity of the incongruent movement, i.e., lip protrusion. The same effect resulted in response to kiss and spit that significantly facilitated the execution of lip stretching. We called this phenomenon facial mimicry reversal effect , intended as the overturning of the effect normally observed during facial mimicry. In general, the findings show that both motor features and types of emotional oro-facial gestures (conveying positive or negative valence) affect the kinematics of subsequent mouth movements at different levels: while congruent motor features facilitate a general motor response, motor execution could be speeded by gestures that are motorically incongruent with the observed one. Moreover, valence effect depends on

Relationship between individual differences in functional connectivity and facial-emotion recognition abilities in adults with traumatic brain injury.

PubMed

Rigon, A; Voss, M W; Turkstra, L S; Mutlu, B; Duff, M C

2017-01-01

Although several studies have demonstrated that facial-affect recognition impairment is common following moderate-severe traumatic brain injury (TBI), and that there are diffuse alterations in large-scale functional brain networks in TBI populations, little is known about the relationship between the two. Here, in a sample of 26 participants with TBI and 20 healthy comparison participants (HC) we measured facial-affect recognition abilities and resting-state functional connectivity (rs-FC) using fMRI. We then used network-based statistics to examine (A) the presence of rs-FC differences between individuals with TBI and HC within the facial-affect processing network, and (B) the association between inter-individual differences in emotion recognition skills and rs-FC within the facial-affect processing network. We found that participants with TBI showed significantly lower rs-FC in a component comprising homotopic and within-hemisphere, anterior-posterior connections within the facial-affect processing network. In addition, within the TBI group, participants with higher emotion-labeling skills showed stronger rs-FC within a network comprised of intra- and inter-hemispheric bilateral connections. Findings indicate that the ability to successfully recognize facial-affect after TBI is related to rs-FC within components of facial-affective networks, and provide new evidence that further our understanding of the mechanisms underlying emotion recognition impairment in TBI.

Deficits in facial affect recognition among antisocial populations: a meta-analysis.

PubMed

Marsh, Abigail A; Blair, R J R

2008-01-01

Individuals with disorders marked by antisocial behavior frequently show deficits in recognizing displays of facial affect. Antisociality may be associated with specific deficits in identifying fearful expressions, which would implicate dysfunction in neural structures that subserve fearful expression processing. A meta-analysis of 20 studies was conducted to assess: (a) if antisocial populations show any consistent deficits in recognizing six emotional expressions; (b) beyond any generalized impairment, whether specific fear recognition deficits are apparent; and (c) if deficits in fear recognition are a function of task difficulty. Results show a robust link between antisocial behavior and specific deficits in recognizing fearful expressions. This impairment cannot be attributed solely to task difficulty. These results suggest dysfunction among antisocial individuals in specified neural substrates, namely the amygdala, involved in processing fearful facial affect.

Facial affect recognition deficit as a marker of genetic vulnerability to schizophrenia.

PubMed

Alfimova, Margarita V; Abramova, Lilia I; Barhatova, Aleksandra I; Yumatova, Polina E; Lyachenko, Galina L; Golimbet, Vera E

2009-05-01

The aim of this study was to investigate the possibility that affect recognition impairments are associated with genetic liability to schizophrenia. In a group of 55 unaffected relatives of schizophrenia patients (parents and siblings) we examined the capacity to detect facially expressed emotions and its relationship to schizotypal personality, neurocognitive functioning, and the subject's actual emotional state. The relatives were compared with 103 schizophrenia patients and 99 healthy subjects without any family history of psychoses. Emotional stimuli were nine black-and-white photos of actors, who portrayed six basic emotions as well as interest, contempt, and shame. The results evidenced the affect recognition deficit in relatives, though milder than that in patients themselves. No correlation between the deficit and schizotypal personality measured with SPQ was detected in the group of relatives. Neither cognitive functioning, including attention, verbal memory and linguistic ability, nor actual emotional states accounted for their affect recognition impairments. The results suggest that the facial affect recognition deficit in schizophrenia may be related to genetic predisposition to the disorder and may serve as an endophenotype in molecular-genetic studies.

Violent video game players and non-players differ on facial emotion recognition.

PubMed

Diaz, Ruth L; Wong, Ulric; Hodgins, David C; Chiu, Carina G; Goghari, Vina M

2016-01-01

Violent video game playing has been associated with both positive and negative effects on cognition. We examined whether playing two or more hours of violent video games a day, compared to not playing video games, was associated with a different pattern of recognition of five facial emotions, while controlling for general perceptual and cognitive differences that might also occur. Undergraduate students were categorized as violent video game players (n = 83) or non-gamers (n = 69) and completed a facial recognition task, consisting of an emotion recognition condition and a control condition of gender recognition. Additionally, participants completed questionnaires assessing their video game and media consumption, aggression, and mood. Violent video game players recognized fearful faces both more accurately and quickly and disgusted faces less accurately than non-gamers. Desensitization to violence, constant exposure to fear and anxiety during game playing, and the habituation to unpleasant stimuli, are possible mechanisms that could explain these results. Future research should evaluate the effects of violent video game playing on emotion processing and social cognition more broadly. © 2015 Wiley Periodicals, Inc.

A Kinect-Based Sign Language Hand Gesture Recognition System for Hearing- and Speech-Impaired: A Pilot Study of Pakistani Sign Language.

PubMed

Halim, Zahid; Abbas, Ghulam

2015-01-01

Sign language provides hearing and speech impaired individuals with an interface to communicate with other members of the society. Unfortunately, sign language is not understood by most of the common people. For this, a gadget based on image processing and pattern recognition can provide with a vital aid for detecting and translating sign language into a vocal language. This work presents a system for detecting and understanding the sign language gestures by a custom built software tool and later translating the gesture into a vocal language. For the purpose of recognizing a particular gesture, the system employs a Dynamic Time Warping (DTW) algorithm and an off-the-shelf software tool is employed for vocal language generation. Microsoft(®) Kinect is the primary tool used to capture video stream of a user. The proposed method is capable of successfully detecting gestures stored in the dictionary with an accuracy of 91%. The proposed system has the ability to define and add custom made gestures. Based on an experiment in which 10 individuals with impairments used the system to communicate with 5 people with no disability, 87% agreed that the system was useful.

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

PubMed

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

2014-07-01

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

Utilizing Current Commercial-off-the-Shelf Facial Recognition and Public Live Video Streaming to Enhance National Security

DTIC Science & Technology

2014-09-01

biometrics technologies. 14. SUBJECT TERMS Facial recognition, systems engineering, live video streaming, security cameras, national security ...national security by sharing biometric facial recognition data in real-time utilizing infrastructures currently in place. It should be noted that the...9/11),law enforcement (LE) and Intelligence community (IC)authorities responsible for protecting citizens from threats against national security

The Reliability of Facial Recognition of Deceased Persons on Photographs.

PubMed

Caplova, Zuzana; Obertova, Zuzana; Gibelli, Daniele M; Mazzarelli, Debora; Fracasso, Tony; Vanezis, Peter; Sforza, Chiarella; Cattaneo, Cristina

2017-09-01

In humanitarian emergencies, such as the current deceased migrants in the Mediterranean, antemortem documentation needed for identification may be limited. The use of visual identification has been previously reported in cases of mass disasters such as Thai tsunami. This pilot study explores the ability of observers to match unfamiliar faces of living and dead persons and whether facial morphology can be used for identification. A questionnaire was given to 41 students and five professionals in the field of forensic identification with the task to choose whether a facial photograph corresponds to one of the five photographs in a lineup and to identify the most useful features used for recognition. Although the overall recognition score did not significantly differ between professionals and students, the median scores of 78.1% and 80.0%, respectively, were too low to consider this method as a reliable identification method and thus needs to be supported by other means. © 2017 American Academy of Forensic Sciences.

Development of emotional facial recognition in late childhood and adolescence.

PubMed

Thomas, Laura A; De Bellis, Michael D; Graham, Reiko; LaBar, Kevin S

2007-09-01

The ability to interpret emotions in facial expressions is crucial for social functioning across the lifespan. Facial expression recognition develops rapidly during infancy and improves with age during the preschool years. However, the developmental trajectory from late childhood to adulthood is less clear. We tested older children, adolescents and adults on a two-alternative forced-choice discrimination task using morphed faces that varied in emotional content. Actors appeared to pose expressions that changed incrementally along three progressions: neutral-to-fear, neutral-to-anger, and fear-to-anger. Across all three morph types, adults displayed more sensitivity to subtle changes in emotional expression than children and adolescents. Fear morphs and fear-to-anger blends showed a linear developmental trajectory, whereas anger morphs showed a quadratic trend, increasing sharply from adolescents to adults. The results provide evidence for late developmental changes in emotional expression recognition with some specificity in the time course for distinct emotions.

A New Method of Facial Expression Recognition Based on SPE Plus SVM

NASA Astrophysics Data System (ADS)

Ying, Zilu; Huang, Mingwei; Wang, Zhen; Wang, Zhewei

A novel method of facial expression recognition (FER) is presented, which uses stochastic proximity embedding (SPE) for data dimension reduction, and support vector machine (SVM) for expression classification. The proposed algorithm is applied to Japanese Female Facial Expression (JAFFE) database for FER, better performance is obtained compared with some traditional algorithms, such as PCA and LDA etc.. The result have further proved the effectiveness of the proposed algorithm.

Abnormal Facial Emotion Recognition in Depression: Serial Testing in an Ultra-Rapid-Cycling Patient.

ERIC Educational Resources Information Center

George, Mark S.; Huggins, Teresa; McDermut, Wilson; Parekh, Priti I.; Rubinow, David; Post, Robert M.

1998-01-01

Mood disorder subjects have a selective deficit in recognizing human facial emotion. Whether the facial emotion recognition errors persist during normal mood states (i.e., are state vs. trait dependent) was studied in one male bipolar II patient. Results of five sessions are presented and discussed. (Author/EMK)

Gestural cue analysis in automated semantic miscommunication annotation

PubMed Central

Inoue, Masashi; Ogihara, Mitsunori; Hanada, Ryoko; Furuyama, Nobuhiro

2011-01-01

The automated annotation of conversational video by semantic miscommunication labels is a challenging topic. Although miscommunications are often obvious to the speakers as well as the observers, it is difficult for machines to detect them from the low-level features. We investigate the utility of gestural cues in this paper among various non-verbal features. Compared with gesture recognition tasks in human-computer interaction, this process is difficult due to the lack of understanding on which cues contribute to miscommunications and the implicitness of gestures. Nine simple gestural features are taken from gesture data, and both simple and complex classifiers are constructed using machine learning. The experimental results suggest that there is no single gestural feature that can predict or explain the occurrence of semantic miscommunication in our setting. PMID:23585724

Cerebellum and processing of negative facial emotions: cerebellar transcranial DC stimulation specifically enhances the emotional recognition of facial anger and sadness.

PubMed

Ferrucci, Roberta; Giannicola, Gaia; Rosa, Manuela; Fumagalli, Manuela; Boggio, Paulo Sergio; Hallett, Mark; Zago, Stefano; Priori, Alberto

2012-01-01

Some evidence suggests that the cerebellum participates in the complex network processing emotional facial expression. To evaluate the role of the cerebellum in recognising facial expressions we delivered transcranial direct current stimulation (tDCS) over the cerebellum and prefrontal cortex. A facial emotion recognition task was administered to 21 healthy subjects before and after cerebellar tDCS; we also tested subjects with a visual attention task and a visual analogue scale (VAS) for mood. Anodal and cathodal cerebellar tDCS both significantly enhanced sensory processing in response to negative facial expressions (anodal tDCS, p=.0021; cathodal tDCS, p=.018), but left positive emotion and neutral facial expressions unchanged (p>.05). tDCS over the right prefrontal cortex left facial expressions of both negative and positive emotion unchanged. These findings suggest that the cerebellum is specifically involved in processing facial expressions of negative emotion.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

Visual Scan Paths and Recognition of Facial Identity in Autism Spectrum Disorder and Typical Development

PubMed Central

Wilson, C. Ellie; Palermo, Romina; Brock, Jon

2012-01-01

Background Previous research suggests that many individuals with autism spectrum disorder (ASD) have impaired facial identity recognition, and also exhibit abnormal visual scanning of faces. Here, two hypotheses accounting for an association between these observations were tested: i) better facial identity recognition is associated with increased gaze time on the Eye region; ii) better facial identity recognition is associated with increased eye-movements around the face. Methodology and Principal Findings Eye-movements of 11 children with ASD and 11 age-matched typically developing (TD) controls were recorded whilst they viewed a series of faces, and then completed a two alternative forced-choice recognition memory test for the faces. Scores on the memory task were standardized according to age. In both groups, there was no evidence of an association between the proportion of time spent looking at the Eye region of faces and age-standardized recognition performance, thus the first hypothesis was rejected. However, the ‘Dynamic Scanning Index’ – which was incremented each time the participant saccaded into and out of one of the core-feature interest areas – was strongly associated with age-standardized face recognition scores in both groups, even after controlling for various other potential predictors of performance. Conclusions and Significance In support of the second hypothesis, results suggested that increased saccading between core-features was associated with more accurate face recognition ability, both in typical development and ASD. Causal directions of this relationship remain undetermined. PMID:22666378

Luminance sticker based facial expression recognition using discrete wavelet transform for physically disabled persons.

PubMed

Nagarajan, R; Hariharan, M; Satiyan, M

2012-08-01

Developing tools to assist physically disabled and immobilized people through facial expression is a challenging area of research and has attracted many researchers recently. In this paper, luminance stickers based facial expression recognition is proposed. Recognition of facial expression is carried out by employing Discrete Wavelet Transform (DWT) as a feature extraction method. Different wavelet families with their different orders (db1 to db20, Coif1 to Coif 5 and Sym2 to Sym8) are utilized to investigate their performance in recognizing facial expression and to evaluate their computational time. Standard deviation is computed for the coefficients of first level of wavelet decomposition for every order of wavelet family. This standard deviation is used to form a set of feature vectors for classification. In this study, conventional validation and cross validation are performed to evaluate the efficiency of the suggested feature vectors. Three different classifiers namely Artificial Neural Network (ANN), k-Nearest Neighborhood (kNN) and Linear Discriminant Analysis (LDA) are used to classify a set of eight facial expressions. The experimental results demonstrate that the proposed method gives very promising classification accuracies.

Differential amygdala response during facial recognition in patients with schizophrenia: an fMRI study.

PubMed

Kosaka, H; Omori, M; Murata, T; Iidaka, T; Yamada, H; Okada, T; Takahashi, T; Sadato, N; Itoh, H; Yonekura, Y; Wada, Y

2002-09-01

Human lesion or neuroimaging studies suggest that amygdala is involved in facial emotion recognition. Although impairments in recognition of facial and/or emotional expression have been reported in schizophrenia, there are few neuroimaging studies that have examined differential brain activation during facial recognition between patients with schizophrenia and normal controls. To investigate amygdala responses during facial recognition in schizophrenia, we conducted a functional magnetic resonance imaging (fMRI) study with 12 right-handed medicated patients with schizophrenia and 12 age- and sex-matched healthy controls. The experiment task was a type of emotional intensity judgment task. During the task period, subjects were asked to view happy (or angry/disgusting/sad) and neutral faces simultaneously presented every 3 s and to judge which face was more emotional (positive or negative face discrimination). Imaging data were investigated in voxel-by-voxel basis for single-group analysis and for between-group analysis according to the random effect model using Statistical Parametric Mapping (SPM). No significant difference in task accuracy was found between the schizophrenic and control groups. Positive face discrimination activated the bilateral amygdalae of both controls and schizophrenics, with more prominent activation of the right amygdala shown in the schizophrenic group. Negative face discrimination activated the bilateral amygdalae in the schizophrenic group whereas the right amygdala alone in the control group, although no significant group difference was found. Exaggerated amygdala activation during emotional intensity judgment found in the schizophrenic patients may reflect impaired gating of sensory input containing emotion. Copyright 2002 Elsevier Science B.V.

Gaze Dynamics in the Recognition of Facial Expressions of Emotion.

PubMed

Barabanschikov, Vladimir A

2015-01-01

We studied preferably fixated parts and features of human face in the process of recognition of facial expressions of emotion. Photographs of facial expressions were used. Participants were to categorize these as basic emotions; during this process, eye movements were registered. It was found that variation in the intensity of an expression is mirrored in accuracy of emotion recognition; it was also reflected by several indices of oculomotor function: duration of inspection of certain areas of the face, its upper and bottom or right parts, right and left sides; location, number and duration of fixations, viewing trajectory. In particular, for low-intensity expressions, right side of the face was found to be attended predominantly (right-side dominance); the right-side dominance effect, was, however, absent for expressions of high intensity. For both low- and high-intensity expressions, upper face part was predominantly fixated, though with greater fixation of high-intensity expressions. The majority of trials (70%), in line with findings in previous studies, revealed a V-shaped pattern of inspection trajectory. No relationship, between accuracy of recognition of emotional expressions, was found, though, with either location and duration of fixations or pattern of gaze directedness in the face. © The Author(s) 2015.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters.

PubMed

Rempel, David; Camilleri, Matt J; Lee, David L

2015-10-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

PubMed Central

Rempel, David; Camilleri, Matt J.; Lee, David L.

2015-01-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input. PMID:26028955

Unspoken vowel recognition using facial electromyogram.

PubMed

Arjunan, Sridhar P; Kumar, Dinesh K; Yau, Wai C; Weghorn, Hans

2006-01-01

The paper aims to identify speech using the facial muscle activity without the audio signals. The paper presents an effective technique that measures the relative muscle activity of the articulatory muscles. Five English vowels were used as recognition variables. This paper reports using moving root mean square (RMS) of surface electromyogram (SEMG) of four facial muscles to segment the signal and identify the start and end of the utterance. The RMS of the signal between the start and end markers was integrated and normalised. This represented the relative muscle activity of the four muscles. These were classified using back propagation neural network to identify the speech. The technique was successfully used to classify 5 vowels into three classes and was not sensitive to the variation in speed and the style of speaking of the different subjects. The results also show that this technique was suitable for classifying the 5 vowels into 5 classes when trained for each of the subjects. It is suggested that such a technology may be used for the user to give simple unvoiced commands when trained for the specific user.

Training industrial robots with gesture recognition techniques

NASA Astrophysics Data System (ADS)

Piane, Jennifer; Raicu, Daniela; Furst, Jacob

2013-01-01

In this paper we propose to use gesture recognition approaches to track a human hand in 3D space and, without the use of special clothing or markers, be able to accurately generate code for training an industrial robot to perform the same motion. The proposed hand tracking component includes three methods: a color-thresholding model, naïve Bayes analysis and Support Vector Machine (SVM) to detect the human hand. Next, it performs stereo matching on the region where the hand was detected to find relative 3D coordinates. The list of coordinates returned is expectedly noisy due to the way the human hand can alter its apparent shape while moving, the inconsistencies in human motion and detection failures in the cluttered environment. Therefore, the system analyzes the list of coordinates to determine a path for the robot to move, by smoothing the data to reduce noise and looking for significant points used to determine the path the robot will ultimately take. The proposed system was applied to pairs of videos recording the motion of a human hand in a „real‟ environment to move the end-affector of a SCARA robot along the same path as the hand of the person in the video. The correctness of the robot motion was determined by observers indicating that motion of the robot appeared to match the motion of the video.

Facial recognition of happiness among older adults with active and remitted major depression.

PubMed

Shiroma, Paulo R; Thuras, Paul; Johns, Brian; Lim, Kelvin O

2016-09-30

Biased emotion processing in depression might be a trait characteristic independent of mood improvement and a vulnerable factor to develop further depressive episodes. This phenomenon of among older adults with depression has not been adequately examined. In a 2-year cross-sectional study, 59 older patients with either active or remitted major depression, or never-depressed, completed a facial emotion recognition task (FERT) to probe perceptual bias of happiness. The results showed that depressed patients, compared with never depressed subjects, had a significant lower sensitivity to identify happiness particularly at moderate intensity of facial stimuli. Patients in remission from a previous major depressive episode but with none or minimal symptoms had similar sensitivity rate to identify happy facial expressions as compared to patients with an active depressive episode. Further studies would be necessary to confirm whether recognition of happy expression reflects a persistent perceptual bias of major depression in older adults. Published by Elsevier Ireland Ltd.

Implementation of facial recognition with Microsoft Kinect v2 sensor for patient verification.

PubMed

Silverstein, Evan; Snyder, Michael

2017-06-01

The aim of this study was to present a straightforward implementation of facial recognition using the Microsoft Kinect v2 sensor for patient identification in a radiotherapy setting. A facial recognition system was created with the Microsoft Kinect v2 using a facial mapping library distributed with the Kinect v2 SDK as a basis for the algorithm. The system extracts 31 fiducial points representing various facial landmarks which are used in both the creation of a reference data set and subsequent evaluations of real-time sensor data in the matching algorithm. To test the algorithm, a database of 39 faces was created, each with 465 vectors derived from the fiducial points, and a one-to-one matching procedure was performed to obtain sensitivity and specificity data of the facial identification system. ROC curves were plotted to display system performance and identify thresholds for match determination. In addition, system performance as a function of ambient light intensity was tested. Using optimized parameters in the matching algorithm, the sensitivity of the system for 5299 trials was 96.5% and the specificity was 96.7%. The results indicate a fairly robust methodology for verifying, in real-time, a specific face through comparison from a precollected reference data set. In its current implementation, the process of data collection for each face and subsequent matching session averaged approximately 30 s, which may be too onerous to provide a realistic supplement to patient identification in a clinical setting. Despite the time commitment, the data collection process was well tolerated by all participants and most robust when consistent ambient light conditions were maintained across both the reference recording session and subsequent real-time identification sessions. A facial recognition system can be implemented for patient identification using the Microsoft Kinect v2 sensor and the distributed SDK. In its present form, the system is accurate-if time consuming

Speech and gesture interfaces for squad-level human-robot teaming

NASA Astrophysics Data System (ADS)

Harris, Jonathan; Barber, Daniel

2014-06-01

As the military increasingly adopts semi-autonomous unmanned systems for military operations, utilizing redundant and intuitive interfaces for communication between Soldiers and robots is vital to mission success. Currently, Soldiers use a common lexicon to verbally and visually communicate maneuvers between teammates. In order for robots to be seamlessly integrated within mixed-initiative teams, they must be able to understand this lexicon. Recent innovations in gaming platforms have led to advancements in speech and gesture recognition technologies, but the reliability of these technologies for enabling communication in human robot teaming is unclear. The purpose for the present study is to investigate the performance of Commercial-Off-The-Shelf (COTS) speech and gesture recognition tools in classifying a Squad Level Vocabulary (SLV) for a spatial navigation reconnaissance and surveillance task. The SLV for this study was based on findings from a survey conducted with Soldiers at Fort Benning, GA. The items of the survey focused on the communication between the Soldier and the robot, specifically in regards to verbally instructing them to execute reconnaissance and surveillance tasks. Resulting commands, identified from the survey, were then converted to equivalent arm and hand gestures, leveraging existing visual signals (e.g. U.S. Army Field Manual for Visual Signaling). A study was then run to test the ability of commercially available automated speech recognition technologies and a gesture recognition glove to classify these commands in a simulated intelligence, surveillance, and reconnaissance task. This paper presents classification accuracy of these devices for both speech and gesture modalities independently.

Predicting the Accuracy of Facial Affect Recognition: The Interaction of Child Maltreatment and Intellectual Functioning

ERIC Educational Resources Information Center

Shenk, Chad E.; Putnam, Frank W.; Noll, Jennie G.

2013-01-01

Previous research demonstrates that both child maltreatment and intellectual performance contribute uniquely to the accurate identification of facial affect by children and adolescents. The purpose of this study was to extend this research by examining whether child maltreatment affects the accuracy of facial recognition differently at varying…

Facial Recognition of Happiness Is Impaired in Musicians with High Music Performance Anxiety.

PubMed

Sabino, Alini Daniéli Viana; Camargo, Cristielli M; Chagas, Marcos Hortes N; Osório, Flávia L

2018-01-01

Music performance anxiety (MPA) can be defined as a lasting and intense apprehension connected with musical performance in public. Studies suggest that MPA can be regarded as a subtype of social anxiety. Since individuals with social anxiety have deficits in the recognition of facial emotion, we hypothesized that musicians with high levels of MPA would share similar impairments. The aim of this study was to compare parameters of facial emotion recognition (FER) between musicians with high and low MPA. 150 amateur and professional musicians with different musical backgrounds were assessed in respect to their level of MPA and completed a dynamic FER task. The outcomes investigated were accuracy, response time, emotional intensity, and response bias. Musicians with high MPA were less accurate in the recognition of happiness ( p  = 0.04; d  = 0.34), had increased response bias toward fear ( p  = 0.03), and increased response time to facial emotions as a whole ( p  = 0.02; d  = 0.39). Musicians with high MPA displayed FER deficits that were independent of general anxiety levels and possibly of general cognitive capacity. These deficits may favor the maintenance and exacerbation of experiences of anxiety during public performance, since cues of approval, satisfaction, and encouragement are not adequately recognized.

A voxel-based lesion study on facial emotion recognition after penetrating brain injury

PubMed Central

Dal Monte, Olga; Solomon, Jeffrey M.; Schintu, Selene; Knutson, Kristine M.; Strenziok, Maren; Pardini, Matteo; Leopold, Anne; Raymont, Vanessa; Grafman, Jordan

2013-01-01

The ability to read emotions in the face of another person is an important social skill that can be impaired in subjects with traumatic brain injury (TBI). To determine the brain regions that modulate facial emotion recognition, we conducted a whole-brain analysis using a well-validated facial emotion recognition task and voxel-based lesion symptom mapping (VLSM) in a large sample of patients with focal penetrating TBIs (pTBIs). Our results revealed that individuals with pTBI performed significantly worse than normal controls in recognizing unpleasant emotions. VLSM mapping results showed that impairment in facial emotion recognition was due to damage in a bilateral fronto-temporo-limbic network, including medial prefrontal cortex (PFC), anterior cingulate cortex, left insula and temporal areas. Beside those common areas, damage to the bilateral and anterior regions of PFC led to impairment in recognizing unpleasant emotions, whereas bilateral posterior PFC and left temporal areas led to impairment in recognizing pleasant emotions. Our findings add empirical evidence that the ability to read pleasant and unpleasant emotions in other people's faces is a complex process involving not only a common network that includes bilateral fronto-temporo-limbic lobes, but also other regions depending on emotional valence. PMID:22496440

The integration of visual context information in facial emotion recognition in 5- to 15-year-olds.

PubMed

Theurel, Anne; Witt, Arnaud; Malsert, Jennifer; Lejeune, Fleur; Fiorentini, Chiara; Barisnikov, Koviljka; Gentaz, Edouard

2016-10-01

The current study investigated the role of congruent visual context information in the recognition of facial emotional expression in 190 participants from 5 to 15years of age. Children performed a matching task that presented pictures with different facial emotional expressions (anger, disgust, happiness, fear, and sadness) in two conditions: with and without a visual context. The results showed that emotions presented with visual context information were recognized more accurately than those presented in the absence of visual context. The context effect remained steady with age but varied according to the emotion presented and the gender of participants. The findings demonstrated for the first time that children from the age of 5years are able to integrate facial expression and visual context information, and this integration improves facial emotion recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

NASA Astrophysics Data System (ADS)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

Functional connectivity between amygdala and facial regions involved in recognition of facial threat

PubMed Central

Harada, Tokiko; Ruffman, Ted; Sadato, Norihiro; Iidaka, Tetsuya

2013-01-01

The recognition of threatening faces is important for making social judgments. For example, threatening facial features of defendants could affect the decisions of jurors during a trial. Previous neuroimaging studies using faces of members of the general public have identified a pivotal role of the amygdala in perceiving threat. This functional magnetic resonance imaging study used face photographs of male prisoners who had been convicted of first-degree murder (MUR) as threatening facial stimuli. We compared the subjective ratings of MUR faces with those of control (CON) faces and examined how they were related to brain activation, particularly, the modulation of the functional connectivity between the amygdala and other brain regions. The MUR faces were perceived to be more threatening than the CON faces. The bilateral amygdala was shown to respond to both MUR and CON faces, but subtraction analysis revealed no significant difference between the two. Functional connectivity analysis indicated that the extent of connectivity between the left amygdala and the face-related regions (i.e. the superior temporal sulcus, inferior temporal gyrus and fusiform gyrus) was correlated with the subjective threat rating for the faces. We have demonstrated that the functional connectivity is modulated by vigilance for threatening facial features. PMID:22156740

Psychopathy and facial emotion recognition ability in patients with bipolar affective disorder with or without delinquent behaviors.

PubMed

Demirel, Husrev; Yesilbas, Dilek; Ozver, Ismail; Yuksek, Erhan; Sahin, Feyzi; Aliustaoglu, Suheyla; Emul, Murat

2014-04-01

It is well known that patients with bipolar disorder are more prone to violence and have more criminal behaviors than general population. A strong relationship between criminal behavior and inability to empathize and imperceptions to other person's feelings and facial expressions increases the risk of delinquent behaviors. In this study, we aimed to investigate the deficits of facial emotion recognition ability in euthymic bipolar patients who committed an offense and compare with non-delinquent euthymic patients with bipolar disorder. Fifty-five euthymic patients with delinquent behaviors and 54 non-delinquent euthymic bipolar patients as a control group were included in the study. Ekman's Facial Emotion Recognition Test, sociodemographic data, Hare Psychopathy Checklist, Hamilton Depression Rating Scale and Young Mania Rating Scale were applied to both groups. There were no significant differences between case and control groups in the meaning of average age, gender, level of education, mean age onset of disease and suicide attempt (p>0.05). The three types of most committed delinquent behaviors in patients with euthymic bipolar disorder were as follows: injury (30.8%), threat or insult (20%) and homicide (12.7%). The best accurate percentage of identified facial emotion was "happy" (>99%, for both) while the worst misidentified facial emotion was "fear" in both groups (<50%, for both). The total accuracy rate of recognition toward facial emotions was significantly impaired in patients with delinquent behaviors than non-delinquent ones (p<0.05). The accuracy rate of recognizing the fear expressions was significantly worse in the case group than in the control group (p<0.05). In addition, it tended to be worse toward angry facial expressions in criminal euthymic bipolar patients. The response times toward happy, fear, disgusted and angry expressions had been significantly longer in the case group than in the control group (p<0.05). This study is the first

Impact of Social Cognition on Alcohol Dependence Treatment Outcome: Poorer Facial Emotion Recognition Predicts Relapse/Dropout.

PubMed

Rupp, Claudia I; Derntl, Birgit; Osthaus, Friederike; Kemmler, Georg; Fleischhacker, W Wolfgang

2017-12-01

Despite growing evidence for neurobehavioral deficits in social cognition in alcohol use disorder (AUD), the clinical relevance remains unclear, and little is known about its impact on treatment outcome. This study prospectively investigated the impact of neurocognitive social abilities at treatment onset on treatment completion. Fifty-nine alcohol-dependent patients were assessed with measures of social cognition including 3 core components of empathy via paradigms measuring: (i) emotion recognition (the ability to recognize emotions via facial expression), (ii) emotional perspective taking, and (iii) affective responsiveness at the beginning of inpatient treatment for alcohol dependence. Subjective measures were also obtained, including estimates of task performance and a self-report measure of empathic abilities (Interpersonal Reactivity Index). According to treatment outcomes, patients were divided into a patient group with a regular treatment course (e.g., with planned discharge and without relapse during treatment) or an irregular treatment course (e.g., relapse and/or premature and unplanned termination of treatment, "dropout"). Compared with patients completing treatment in a regular fashion, patients with relapse and/or dropout of treatment had significantly poorer facial emotion recognition ability at treatment onset. Additional logistic regression analyses confirmed these results and identified poor emotion recognition performance as a significant predictor for relapse/dropout. Self-report (subjective) measures did not correspond with neurobehavioral social cognition measures, respectively objective task performance. Analyses of individual subtypes of facial emotions revealed poorer recognition particularly of disgust, anger, and no (neutral faces) emotion in patients with relapse/dropout. Social cognition in AUD is clinically relevant. Less successful treatment outcome was associated with poorer facial emotion recognition ability at the beginning of

Comprehension of iconic gestures by chimpanzees and human children.

PubMed

Bohn, Manuel; Call, Josep; Tomasello, Michael

2016-02-01

Iconic gestures-communicative acts using hand or body movements that resemble their referent-figure prominently in theories of language evolution and development. This study contrasted the abilities of chimpanzees (N=11) and 4-year-old human children (N=24) to comprehend novel iconic gestures. Participants learned to retrieve rewards from apparatuses in two distinct locations, each requiring a different action. In the test, a human adult informed the participant where to go by miming the action needed to obtain the reward. Children used the iconic gestures (more than arbitrary gestures) to locate the reward, whereas chimpanzees did not. Some children also used arbitrary gestures in the same way, but only after they had previously shown comprehension for iconic gestures. Over time, chimpanzees learned to associate iconic gestures with the appropriate location faster than arbitrary gestures, suggesting at least some recognition of the iconicity involved. These results demonstrate the importance of iconicity in referential communication. Copyright © 2015 Elsevier Inc. All rights reserved.

Influence of gender in the recognition of basic facial expressions: A critical literature review

PubMed Central

Forni-Santos, Larissa; Osório, Flávia L

2015-01-01

AIM: To conduct a systematic literature review about the influence of gender on the recognition of facial expressions of six basic emotions. METHODS: We made a systematic search with the search terms (face OR facial) AND (processing OR recognition OR perception) AND (emotional OR emotion) AND (gender or sex) in PubMed, PsycINFO, LILACS, and SciELO electronic databases for articles assessing outcomes related to response accuracy and latency and emotional intensity. The articles selection was performed according to parameters set by COCHRANE. The reference lists of the articles found through the database search were checked for additional references of interest. RESULTS: In respect to accuracy, women tend to perform better than men when all emotions are considered as a set. Regarding specific emotions, there seems to be no gender-related differences in the recognition of happiness, whereas results are quite heterogeneous in respect to the remaining emotions, especially sadness, anger, and disgust. Fewer articles dealt with the parameters of response latency and emotional intensity, which hinders the generalization of their findings, especially in the face of their methodological differences. CONCLUSION: The analysis of the studies conducted to date do not allow for definite conclusions concerning the role of the observer’s gender in the recognition of facial emotion, mostly because of the absence of standardized methods of investigation. PMID:26425447

[Assessment of gestures and their psychiatric relevance].

PubMed

Bulucz, Judit; Simon, Lajos

2008-01-01

Analyzing and investigating non-verbal behavior and gestures has been receiving much attention since the last century. Thanks to the pioneer work of Ekman and Friesen we have a number of descriptive-analytic, categorizing and semantic content related scales and scoring systems. Generation of gestures, the integrative system with speech and the inter-cultural differences are in the focus of interest. Furthermore, analysis of the gestural changes caused by lesions of distinct neurological areas point toward to formation of new diagnostic approaches. The more widespread application of computerized methods resulted in an increasing number of experiments which study gesture generation, reproduction in mechanical and virtual reality. Increasing efforts are directed towards the understanding of human and computerized recognition of human gestures. In this review we describe the results emphasizing the relations of those results with psychiatric and neuropsychiatric disorders, specifically schizophrenia and affective spectrum.

Comparing Facial Emotional Recognition in Patients with Borderline Personality Disorder and Patients with Schizotypal Personality Disorder with a Normal Group

PubMed Central

Farsham, Aida; Abbaslou, Tahereh; Bidaki, Reza; Bozorg, Bonnie

2017-01-01

Objective: No research has been conducted on facial emotional recognition on patients with borderline personality disorder (BPD) and schizotypal personality disorder (SPD). The present study aimed at comparing facial emotion recognition in these patients with the general population. The neurocognitive processing of emotions can show the pathologic style of these 2 disorders. Method: Twenty BPD patients, 16 SPD patients, and 20 healthy individuals were selected by available sampling method. Structural Clinical Interview for Axis II, Millon Personality Inventory, Beck Depression Inventory and Facial Emotional Recognition Test was were conducted for all participants. Discussion: The results of one way ANOVA and Scheffe’s post hoc test analysis revealed significant differences in neuropsychology assessment of facial emotional recognition between BPD and SPD patients with normal group (p = 0/001). A significant difference was found in emotion recognition of fear between the 2 groups of BPD and normal population (p = 0/008). A significant difference was observed between SPD patients and control group in emotion recognition of wonder (p = 0/04(. The obtained results indicated a deficit in negative emotion recognition, especially disgust emotion, thus, it can be concluded that these patients have the same neurocognitive profile in the emotion domain. PMID:28659980

[Emotion Recognition in Patients with Peripheral Facial Paralysis - A Pilot Study].

PubMed

Konnerth, V; Mohr, G; von Piekartz, H

2016-02-01

The perception of emotions is an important component in enabling human beings to social interaction in everyday life. Thus, the ability to recognize the emotions of the other one's mime is a key prerequisite for this. The following study aimed at evaluating the ability of subjects with 'peripheral facial paresis' to perceive emotions in healthy individuals. A pilot study was conducted in which 13 people with 'peripheral facial paresis' participated. This assessment included the 'Facially Expressed Emotion Labeling-Test' (FEEL-Test), the 'Facial-Laterality-Recognition Test' (FLR-Test) and the 'Toronto-Alexithymie-Scale 26' (TAS 26). The results were compared with data of healthy people from other studies. In contrast to healthy patients, the subjects with 'facial paresis' show more difficulties in recognizing basic emotions; however the results are not significant. The participants show a significant lower level of speed (right/left: p<0.001) concerning the perception of facial laterality compared to healthy people. With regard to the alexithymia, the tested group reveals significantly higher results (p<0.001) compared to the unimpaired people. The present pilot study does not prove any impact on this specific patient group's ability to recognize emotions and facial laterality. For future studies the research question should be verified in a larger sample size. © Georg Thieme Verlag KG Stuttgart · New York.

Quality of life differences in patients with right- versus left-sided facial paralysis: Universal preference of right-sided human face recognition.

PubMed

Ryu, Nam Gyu; Lim, Byung Woo; Cho, Jae Keun; Kim, Jin

2016-09-01

We investigated whether experiencing right- or left-sided facial paralysis would affect an individual's ability to recognize one side of the human face using hybrid hemi-facial photos by preliminary study. Further investigation looked at the relationship between facial recognition ability, stress, and quality of life. To investigate predominance of one side of the human face for face recognition, 100 normal participants (right-handed: n = 97, left-handed: n = 3, right brain dominance: n = 56, left brain dominance: n = 44) answered a questionnaire that included hybrid hemi-facial photos developed to determine decide superiority of one side for human face recognition. To determine differences of stress level and quality of life between individuals experiencing right- and left-sided facial paralysis, 100 patients (right side:50, left side:50, not including traumatic facial nerve paralysis) answered a questionnaire about facial disability index test and quality of life (SF-36 Korean version). Regardless of handedness or hemispheric dominance, the proportion of predominance of the right side in human face recognition was larger than the left side (71% versus 12%, neutral: 17%). Facial distress index of the patients with right-sided facial paralysis was lower than that of left-sided patients (68.8 ± 9.42 versus 76.4 ± 8.28), and the SF-36 scores of right-sided patients were lower than left-sided patients (119.07 ± 15.24 versus 123.25 ± 16.48, total score: 166). Universal preference for the right side in human face recognition showed worse psychological mood and social interaction in patients with right-side facial paralysis than left-sided paralysis. This information is helpful to clinicians in that psychological and social factors should be considered when treating patients with facial-paralysis. Copyright © 2016 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Affective theory of mind inferences contextually influence the recognition of emotional facial expressions.

PubMed

Stewart, Suzanne L K; Schepman, Astrid; Haigh, Matthew; McHugh, Rhian; Stewart, Andrew J

2018-03-14

The recognition of emotional facial expressions is often subject to contextual influence, particularly when the face and the context convey similar emotions. We investigated whether spontaneous, incidental affective theory of mind inferences made while reading vignettes describing social situations would produce context effects on the identification of same-valenced emotions (Experiment 1) as well as differently-valenced emotions (Experiment 2) conveyed by subsequently presented faces. Crucially, we found an effect of context on reaction times in both experiments while, in line with previous work, we found evidence for a context effect on accuracy only in Experiment 1. This demonstrates that affective theory of mind inferences made at the pragmatic level of a text can automatically, contextually influence the perceptual processing of emotional facial expressions in a separate task even when those emotions are of a distinctive valence. Thus, our novel findings suggest that language acts as a contextual influence to the recognition of emotional facial expressions for both same and different valences.

Effects of levodopa-carbidopa-entacapone and smoked cocaine on facial affect recognition in cocaine smokers.

PubMed

Bedi, Gillinder; Shiffrin, Laura; Vadhan, Nehal P; Nunes, Edward V; Foltin, Richard W; Bisaga, Adam

2016-04-01

In addition to difficulties in daily social functioning, regular cocaine users have decrements in social processing (the cognitive and affective processes underlying social behavior) relative to non-users. Little is known, however, about the effects of clinically-relevant pharmacological agents, such as cocaine and potential treatment medications, on social processing in cocaine users. Such drug effects could potentially alleviate or compound baseline social processing decrements in cocaine abusers. Here, we assessed the individual and combined effects of smoked cocaine and a potential treatment medication, levodopa-carbidopa-entacapone (LCE), on facial emotion recognition in cocaine smokers. Healthy non-treatment-seeking cocaine smokers (N = 14; two female) completed this 11-day inpatient within-subjects study. Participants received LCE (titrated to 400mg/100mg/200mg b.i.d.) for five days with the remaining time on placebo. The order of medication administration was counterbalanced. Facial emotion recognition was measured twice during target LCE dosing and twice on placebo: once without cocaine and once after repeated cocaine doses. LCE increased the response threshold for identification of facial fear, biasing responses away from fear identification. Cocaine had no effect on facial emotion recognition. Results highlight the possibility for candidate pharmacotherapies to have unintended impacts on social processing in cocaine users, potentially exacerbating already existing difficulties in this population. © The Author(s) 2016.

Facial emotion recognition, socio-occupational functioning and expressed emotions in schizophrenia versus bipolar disorder.

PubMed

Thonse, Umesh; Behere, Rishikesh V; Praharaj, Samir Kumar; Sharma, Podila Sathya Venkata Narasimha

2018-06-01

Facial emotion recognition deficits have been consistently demonstrated in patients with severe mental disorders. Expressed emotion is found to be an important predictor of relapse. However, the relationship between facial emotion recognition abilities and expressed emotions and its influence on socio-occupational functioning in schizophrenia versus bipolar disorder has not been studied. In this study we examined 91 patients with schizophrenia and 71 with bipolar disorder for psychopathology, socio occupational functioning and emotion recognition abilities. Primary caregivers of 62 patients with schizophrenia and 49 with bipolar disorder were assessed on Family Attitude Questionnaire to assess their expressed emotions. Patients of schizophrenia and bipolar disorder performed similarly on the emotion recognition task. Patients with schizophrenia group experienced higher critical comments and had a poorer socio-occupational functioning as compared to patients with bipolar disorder. Poorer socio-occupational functioning in patients with schizophrenia was significantly associated with greater dissatisfaction in their caregivers. In patients with bipolar disorder, poorer emotion recognition scores significantly correlated with poorer adaptive living skills and greater hostility and dissatisfaction in their caregivers. The findings of our study suggest that emotion recognition abilities in patients with bipolar disorder are associated with negative expressed emotions leading to problems in adaptive living skills. Copyright © 2018 Elsevier B.V. All rights reserved.

Face Processing and Facial Emotion Recognition in Adults with Down Syndrome

ERIC Educational Resources Information Center

Barisnikov, Koviljka; Hippolyte, Loyse; Van der Linden, Martial

2008-01-01

Face processing and facial expression recognition was investigated in 17 adults with Down syndrome, and results were compared with those of a child control group matched for receptive vocabulary. On the tasks involving faces without emotional content, the adults with Down syndrome performed significantly worse than did the controls. However, their…

Recognition of Facial Expressions and Prosodic Cues with Graded Emotional Intensities in Adults with Asperger Syndrome

ERIC Educational Resources Information Center

Doi, Hirokazu; Fujisawa, Takashi X.; Kanai, Chieko; Ohta, Haruhisa; Yokoi, Hideki; Iwanami, Akira; Kato, Nobumasa; Shinohara, Kazuyuki

2013-01-01

This study investigated the ability of adults with Asperger syndrome to recognize emotional categories of facial expressions and emotional prosodies with graded emotional intensities. The individuals with Asperger syndrome showed poorer recognition performance for angry and sad expressions from both facial and vocal information. The group…

Empathy, but not mimicry restriction, influences the recognition of change in emotional facial expressions.

PubMed

Kosonogov, Vladimir; Titova, Alisa; Vorobyeva, Elena

2015-01-01

The current study addressed the hypothesis that empathy and the restriction of facial muscles of observers can influence recognition of emotional facial expressions. A sample of 74 participants recognized the subjective onset of emotional facial expressions (anger, disgust, fear, happiness, sadness, surprise, and neutral) in a series of morphed face photographs showing a gradual change (frame by frame) from one expression to another. The high-empathy (as measured by the Empathy Quotient) participants recognized emotional facial expressions at earlier photographs from the series than did low-empathy ones, but there was no difference in the exploration time. Restriction of facial muscles of observers (with plasters and a stick in mouth) did not influence the responses. We discuss these findings in the context of the embodied simulation theory and previous data on empathy.

Depth Camera-Based 3D Hand Gesture Controls with Immersive Tactile Feedback for Natural Mid-Air Gesture Interactions

PubMed Central

Kim, Kwangtaek; Kim, Joongrock; Choi, Jaesung; Kim, Junghyun; Lee, Sangyoun

2015-01-01

Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback. PMID:25580901

Depth camera-based 3D hand gesture controls with immersive tactile feedback for natural mid-air gesture interactions.

PubMed

Kim, Kwangtaek; Kim, Joongrock; Choi, Jaesung; Kim, Junghyun; Lee, Sangyoun

2015-01-08

Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.

A facial expression of pax: Assessing children's "recognition" of emotion from faces.

PubMed

Nelson, Nicole L; Russell, James A

2016-01-01

In a classic study, children were shown an array of facial expressions and asked to choose the person who expressed a specific emotion. Children were later asked to name the emotion in the face with any label they wanted. Subsequent research often relied on the same two tasks--choice from array and free labeling--to support the conclusion that children recognize basic emotions from facial expressions. Here five studies (N=120, 2- to 10-year-olds) showed that these two tasks produce illusory recognition; a novel nonsense facial expression was included in the array. Children "recognized" a nonsense emotion (pax or tolen) and two familiar emotions (fear and jealousy) from the same nonsense face. Children likely used a process of elimination; they paired the unknown facial expression with a label given in the choice-from-array task and, after just two trials, freely labeled the new facial expression with the new label. These data indicate that past studies using this method may have overestimated children's expression knowledge. Copyright © 2015 Elsevier Inc. All rights reserved.

An Interactive Astronaut-Robot System with Gesture Control

PubMed Central

Liu, Jinguo; Luo, Yifan; Ju, Zhaojie

2016-01-01

Human-robot interaction (HRI) plays an important role in future planetary exploration mission, where astronauts with extravehicular activities (EVA) have to communicate with robot assistants by speech-type or gesture-type user interfaces embedded in their space suits. This paper presents an interactive astronaut-robot system integrating a data-glove with a space suit for the astronaut to use hand gestures to control a snake-like robot. Support vector machine (SVM) is employed to recognize hand gestures and particle swarm optimization (PSO) algorithm is used to optimize the parameters of SVM to further improve its recognition accuracy. Various hand gestures from American Sign Language (ASL) have been selected and used to test and validate the performance of the proposed system. PMID:27190503

Nonverbal Social Communication and Gesture Control in Schizophrenia

PubMed Central

Walther, Sebastian; Stegmayer, Katharina; Sulzbacher, Jeanne; Vanbellingen, Tim; Müri, René; Strik, Werner; Bohlhalter, Stephan

2015-01-01

Schizophrenia patients are severely impaired in nonverbal communication, including social perception and gesture production. However, the impact of nonverbal social perception on gestural behavior remains unknown, as is the contribution of negative symptoms, working memory, and abnormal motor behavior. Thus, the study tested whether poor nonverbal social perception was related to impaired gesture performance, gestural knowledge, or motor abnormalities. Forty-six patients with schizophrenia (80%), schizophreniform (15%), or schizoaffective disorder (5%) and 44 healthy controls matched for age, gender, and education were included. Participants completed 4 tasks on nonverbal communication including nonverbal social perception, gesture performance, gesture recognition, and tool use. In addition, they underwent comprehensive clinical and motor assessments. Patients presented impaired nonverbal communication in all tasks compared with controls. Furthermore, in contrast to controls, performance in patients was highly correlated between tasks, not explained by supramodal cognitive deficits such as working memory. Schizophrenia patients with impaired gesture performance also demonstrated poor nonverbal social perception, gestural knowledge, and tool use. Importantly, motor/frontal abnormalities negatively mediated the strong association between nonverbal social perception and gesture performance. The factors negative symptoms and antipsychotic dosage were unrelated to the nonverbal tasks. The study confirmed a generalized nonverbal communication deficit in schizophrenia. Specifically, the findings suggested that nonverbal social perception in schizophrenia has a relevant impact on gestural impairment beyond the negative influence of motor/frontal abnormalities. PMID:25646526

Joint recognition-expression impairment of facial emotions in Huntington's disease despite intact understanding of feelings.

PubMed

Trinkler, Iris; Cleret de Langavant, Laurent; Bachoud-Lévi, Anne-Catherine

2013-02-01

Patients with Huntington's disease (HD), a neurodegenerative disorder that causes major motor impairments, also show cognitive and emotional deficits. While their deficit in recognising emotions has been explored in depth, little is known about their ability to express emotions and understand their feelings. If these faculties were impaired, patients might not only mis-read emotion expressions in others but their own emotions might be mis-interpreted by others as well, or thirdly, they might have difficulties understanding and describing their feelings. We compared the performance of recognition and expression of facial emotions in 13 HD patients with mild motor impairments but without significant bucco-facial abnormalities, and 13 controls matched for age and education. Emotion recognition was investigated in a forced-choice recognition test (FCR), and emotion expression by filming participants while they mimed the six basic emotional facial expressions (anger, disgust, fear, surprise, sadness and joy) to the experimenter. The films were then segmented into 60 stimuli per participant and four external raters performed a FCR on this material. Further, we tested understanding of feelings in self (alexithymia) and others (empathy) using questionnaires. Both recognition and expression were impaired across different emotions in HD compared to controls and recognition and expression scores were correlated. By contrast, alexithymia and empathy scores were very similar in HD and controls. This might suggest that emotion deficits in HD might be tied to the expression itself. Because similar emotion recognition-expression deficits are also found in Parkinson's Disease and vascular lesions of the striatum, our results further confirm the importance of the striatum for emotion recognition and expression, while access to the meaning of feelings relies on a different brain network, and is spared in HD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Generating Control Commands From Gestures Sensed by EMG

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Jorgensen, Charles

2006-01-01

An effort is under way to develop noninvasive neuro-electric interfaces through which human operators could control systems as diverse as simple mechanical devices, computers, aircraft, and even spacecraft. The basic idea is to use electrodes on the surface of the skin to acquire electromyographic (EMG) signals associated with gestures, digitize and process the EMG signals to recognize the gestures, and generate digital commands to perform the actions signified by the gestures. In an experimental prototype of such an interface, the EMG signals associated with hand gestures are acquired by use of several pairs of electrodes mounted in sleeves on a subject s forearm (see figure). The EMG signals are sampled and digitized. The resulting time-series data are fed as input to pattern-recognition software that has been trained to distinguish gestures from a given gesture set. The software implements, among other things, hidden Markov models, which are used to recognize the gestures as they are being performed in real time. Thus far, two experiments have been performed on the prototype interface to demonstrate feasibility: an experiment in synthesizing the output of a joystick and an experiment in synthesizing the output of a computer or typewriter keyboard. In the joystick experiment, the EMG signals were processed into joystick commands for a realistic flight simulator for an airplane. The acting pilot reached out into the air, grabbed an imaginary joystick, and pretended to manipulate the joystick to achieve left and right banks and up and down pitches of the simulated airplane. In the keyboard experiment, the subject pretended to type on a numerical keypad, and the EMG signals were processed into keystrokes. The results of the experiments demonstrate the basic feasibility of this method while indicating the need for further research to reduce the incidence of errors (including confusion among gestures). Topics that must be addressed include the numbers and arrangements

Seeing Iconic Gestures While Encoding Events Facilitates Children's Memory of These Events.

PubMed

Aussems, Suzanne; Kita, Sotaro

2017-11-08

An experiment with 72 three-year-olds investigated whether encoding events while seeing iconic gestures boosts children's memory representation of these events. The events, shown in videos of actors moving in an unusual manner, were presented with either iconic gestures depicting how the actors performed these actions, interactive gestures, or no gesture. In a recognition memory task, children in the iconic gesture condition remembered actors and actions better than children in the control conditions. Iconic gestures were categorized based on how much of the actors was represented by the hands (feet, legs, or body). Only iconic hand-as-body gestures boosted actor memory. Thus, seeing iconic gestures while encoding events facilitates children's memory of those aspects of events that are schematically highlighted by gesture. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Assessing the Utility of a Virtual Environment for Enhancing Facial Affect Recognition in Adolescents with Autism

ERIC Educational Resources Information Center

Bekele, Esubalew; Crittendon, Julie; Zheng, Zhi; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

2014-01-01

Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e.,…

Genetic variations in the dopamine system and facial expression recognition in healthy chinese college students.

PubMed

Zhu, Bi; Chen, Chuansheng; Moyzis, Robert K; Dong, Qi; Chen, Chunhui; He, Qinghua; Stern, Hal S; Li, He; Li, Jin; Li, Jun; Lessard, Jared; Lin, Chongde

2012-01-01

This study investigated the relation between genetic variations in the dopamine system and facial expression recognition. A sample of Chinese college students (n = 478) was given a facial expression recognition task. Subjects were genotyped for 98 loci [96 single-nucleotide polymorphisms (SNPs) and 2 variable number tandem repeats] in 16 genes involved in the dopamine neurotransmitter system, including its 4 subsystems: synthesis (TH, DDC, and DBH), degradation/transport (COMT,MAOA,MAOB, and SLC6A3), receptors (DRD1,DRD2,DRD3,DRD4, and DRD5), and modulation (NTS,NTSR1,NTSR2, and NLN). To quantify the total contributions of the dopamine system to emotion recognition, we used a series of multiple regression models. Permutation analyses were performed to assess the posterior probabilities of obtaining such results. Among the 78 loci that were included in the final analyses (after excluding 12 SNPs that were in high linkage disequilibrium and 8 that were not in Hardy-Weinberg equilibrium), 1 (for fear), 3 (for sadness), 5 (for anger), 13 (for surprise), and 15 (for disgust) loci exhibited main effects on the recognition of facial expressions. Genetic variations in the dopamine system accounted for 3% for fear, 6% for sadness, 7% for anger, 10% for surprise, and 18% for disgust, with the latter surviving a stringent permutation test. Genetic variations in the dopamine system (especially the dopamine synthesis and modulation subsystems) made significant contributions to individual differences in the recognition of disgust faces. Copyright © 2012 S. Karger AG, Basel.

Facial and prosodic emotion recognition in social anxiety disorder.

PubMed

Tseng, Huai-Hsuan; Huang, Yu-Lien; Chen, Jian-Ting; Liang, Kuei-Yu; Lin, Chao-Cheng; Chen, Sue-Huei

2017-07-01

Patients with social anxiety disorder (SAD) have a cognitive preference to negatively evaluate emotional information. In particular, the preferential biases in prosodic emotion recognition in SAD have been much less explored. The present study aims to investigate whether SAD patients retain negative evaluation biases across visual and auditory modalities when given sufficient response time to recognise emotions. Thirty-one SAD patients and 31 age- and gender-matched healthy participants completed a culturally suitable non-verbal emotion recognition task and received clinical assessments for social anxiety and depressive symptoms. A repeated measures analysis of variance was conducted to examine group differences in emotion recognition. Compared to healthy participants, SAD patients were significantly less accurate at recognising facial and prosodic emotions, and spent more time on emotion recognition. The differences were mainly driven by the lower accuracy and longer reaction times for recognising fearful emotions in SAD patients. Within the SAD patients, lower accuracy of sad face recognition was associated with higher severity of depressive and social anxiety symptoms, particularly with avoidance symptoms. These findings may represent a cross-modality pattern of avoidance in the later stage of identifying negative emotions in SAD. This pattern may be linked to clinical symptom severity.

Emotional facial expressions differentially influence predictions and performance for face recognition.

PubMed

Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

2013-01-01

This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

[Emotional facial recognition difficulties as primary deficit in children with attention deficit hyperactivity disorder: a systematic review].

PubMed

Rodrigo-Ruiz, D; Perez-Gonzalez, J C; Cejudo, J

2017-08-16

It has recently been warned that children with attention deficit hyperactivity disorder (ADHD) show a deficit in emotional competence and emotional intelligence, specifically in their ability to emotional recognition. A systematic review of the scientific literature in reference to the emotional recognition of facial expressions in children with ADHD is presented in order to establish or rule the existence of emotional deficits as primary dysfunction in this disorder and, where appropriate, the effect size of the differences against normal development or neurotypical children. The results reveal the recent interest in the issue and the lack of information. Although there is no complete agreement, most of the studies show that emotional recognition of facial expressions is affected in children with ADHD, showing them significantly less accurate than children from control groups in recognizing emotions communicated through facial expressions. A part of these studies make comparisons on the recognition of different discrete emotions; having observed that children with ADHD tend to a greater difficulty recognizing negative emotions, especially anger, fear, and disgust. These results have direct implications for the educational and clinical diagnosis of ADHD; and for the educational intervention for children with ADHD, emotional education might entail an advantageous aid.

Test battery for measuring the perception and recognition of facial expressions of emotion

PubMed Central

Wilhelm, Oliver; Hildebrandt, Andrea; Manske, Karsten; Schacht, Annekathrin; Sommer, Werner

2014-01-01

Despite the importance of perceiving and recognizing facial expressions in everyday life, there is no comprehensive test battery for the multivariate assessment of these abilities. As a first step toward such a compilation, we present 16 tasks that measure the perception and recognition of facial emotion expressions, and data illustrating each task's difficulty and reliability. The scoring of these tasks focuses on either the speed or accuracy of performance. A sample of 269 healthy young adults completed all tasks. In general, accuracy and reaction time measures for emotion-general scores showed acceptable and high estimates of internal consistency and factor reliability. Emotion-specific scores yielded lower reliabilities, yet high enough to encourage further studies with such measures. Analyses of task difficulty revealed that all tasks are suitable for measuring emotion perception and emotion recognition related abilities in normal populations. PMID:24860528

Anxiety disorders in adolescence are associated with impaired facial expression recognition to negative valence.

PubMed

Jarros, Rafaela Behs; Salum, Giovanni Abrahão; Belem da Silva, Cristiano Tschiedel; Toazza, Rudineia; de Abreu Costa, Marianna; Fumagalli de Salles, Jerusa; Manfro, Gisele Gus

2012-02-01

The aim of the present study was to test the ability of adolescents with a current anxiety diagnosis to recognize facial affective expressions, compared to those without an anxiety disorder. Forty cases and 27 controls were selected from a larger cross sectional community sample of adolescents, aged from 10 to 17 years old. Adolescent's facial recognition of six human emotions (sadness, anger, disgust, happy, surprise and fear) and neutral faces was assessed through a facial labeling test using Ekman's Pictures of Facial Affect (POFA). Adolescents with anxiety disorders had a higher mean number of errors in angry faces as compared to controls: 3.1 (SD=1.13) vs. 2.5 (SD=2.5), OR=1.72 (CI95% 1.02 to 2.89; p=0.040). However, they named neutral faces more accurately than adolescents without anxiety diagnosis: 15% of cases vs. 37.1% of controls presented at least one error in neutral faces, OR=3.46 (CI95% 1.02 to 11.7; p=0.047). No differences were found considering other human emotions or on the distribution of errors in each emotional face between the groups. Our findings support an anxiety-mediated influence on the recognition of facial expressions in adolescence. These difficulty in recognizing angry faces and more accuracy in naming neutral faces may lead to misinterpretation of social clues and can explain some aspects of the impairment in social interactions in adolescents with anxiety disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

Visual Scanning Patterns and Executive Function in Relation to Facial Emotion Recognition in Aging

PubMed Central

Circelli, Karishma S.; Clark, Uraina S.; Cronin-Golomb, Alice

2012-01-01

Objective The ability to perceive facial emotion varies with age. Relative to younger adults (YA), older adults (OA) are less accurate at identifying fear, anger, and sadness, and more accurate at identifying disgust. Because different emotions are conveyed by different parts of the face, changes in visual scanning patterns may account for age-related variability. We investigated the relation between scanning patterns and recognition of facial emotions. Additionally, as frontal-lobe changes with age may affect scanning patterns and emotion recognition, we examined correlations between scanning parameters and performance on executive function tests. Methods We recorded eye movements from 16 OA (mean age 68.9) and 16 YA (mean age 19.2) while they categorized facial expressions and non-face control images (landscapes), and administered standard tests of executive function. Results OA were less accurate than YA at identifying fear (p<.05, r=.44) and more accurate at identifying disgust (p<.05, r=.39). OA fixated less than YA on the top half of the face for disgust, fearful, happy, neutral, and sad faces (p’s<.05, r’s≥.38), whereas there was no group difference for landscapes. For OA, executive function was correlated with recognition of sad expressions and with scanning patterns for fearful, sad, and surprised expressions. Conclusion We report significant age-related differences in visual scanning that are specific to faces. The observed relation between scanning patterns and executive function supports the hypothesis that frontal-lobe changes with age may underlie some changes in emotion recognition. PMID:22616800

The effects of acute alcohol intoxication on the cognitive mechanisms underlying false facial recognition.

PubMed

Colloff, Melissa F; Flowe, Heather D

2016-06-01

False face recognition rates are sometimes higher when faces are learned while under the influence of alcohol. Alcohol myopia theory (AMT) proposes that acute alcohol intoxication during face learning causes people to attend to only the most salient features of a face, impairing the encoding of less salient facial features. Yet, there is currently no direct evidence to support this claim. Our objective was to test whether acute alcohol intoxication impairs face learning by causing subjects to attend to a salient (i.e., distinctive) facial feature over other facial features, as per AMT. We employed a balanced placebo design (N = 100). Subjects in the alcohol group were dosed to achieve a blood alcohol concentration (BAC) of 0.06 %, whereas the no alcohol group consumed tonic water. Alcohol expectancy was controlled. Subjects studied faces with or without a distinctive feature (e.g., scar, piercing). An old-new recognition test followed. Some of the test faces were "old" (i.e., previously studied), and some were "new" (i.e., not previously studied). We varied whether the new test faces had a previously studied distinctive feature versus other familiar characteristics. Intoxicated and sober recognition accuracy was comparable, but subjects in the alcohol group made more positive identifications overall compared to the no alcohol group. The results are not in keeping with AMT. Rather, a more general cognitive mechanism appears to underlie false face recognition in intoxicated subjects. Specifically, acute alcohol intoxication during face learning results in more liberal choosing, perhaps because of an increased reliance on familiarity.

The Moving Window Technique: A Window into Developmental Changes in Attention during Facial Emotion Recognition

ERIC Educational Resources Information Center

Birmingham, Elina; Meixner, Tamara; Iarocci, Grace; Kanan, Christopher; Smilek, Daniel; Tanaka, James W.

2013-01-01

The strategies children employ to selectively attend to different parts of the face may reflect important developmental changes in facial emotion recognition. Using the Moving Window Technique (MWT), children aged 5-12 years and adults ("N" = 129) explored faces with a mouse-controlled window in an emotion recognition task. An…

A Modified Sparse Representation Method for Facial Expression Recognition.

PubMed

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.

A Modified Sparse Representation Method for Facial Expression Recognition

PubMed Central

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result. PMID:26880878

Dopamine and light: effects on facial emotion recognition.

PubMed

Cawley, Elizabeth; Tippler, Maria; Coupland, Nicholas J; Benkelfat, Chawki; Boivin, Diane B; Aan Het Rot, Marije; Leyton, Marco

2017-09-01

Bright light can affect mood states and social behaviours. Here, we tested potential interacting effects of light and dopamine on facial emotion recognition. Participants were 32 women with subsyndromal seasonal affective disorder tested in either a bright (3000 lux) or dim light (10 lux) environment. Each participant completed two test days, one following the ingestion of a phenylalanine/tyrosine-deficient mixture and one with a nutritionally balanced control mixture, both administered double blind in a randomised order. Approximately four hours post-ingestion participants completed a self-report measure of mood followed by a facial emotion recognition task. All testing took place between November and March when seasonal symptoms would be present. Following acute phenylalanine/tyrosine depletion (APTD), compared to the nutritionally balanced control mixture, participants in the dim light condition were more accurate at recognising sad faces, less likely to misclassify them, and faster at responding to them, effects that were independent of changes in mood. Effects of APTD on responses to sad faces in the bright light group were less consistent. There were no APTD effects on responses to other emotions, with one exception: a significant light × mixture interaction was seen for the reaction time to fear, but the pattern of effect was not predicted a priori or seen on other measures. Together, the results suggest that the processing of sad emotional stimuli might be greater when dopamine transmission is low. Bright light exposure, used for the treatment of both seasonal and non-seasonal mood disorders, might produce some of its benefits by preventing this effect.

The Impact of Sex Differences on Odor Identification and Facial Affect Recognition in Patients with Schizophrenia Spectrum Disorders.

PubMed

Mossaheb, Nilufar; Kaufmann, Rainer M; Schlögelhofer, Monika; Aninilkumparambil, Thushara; Himmelbauer, Claudia; Gold, Anna; Zehetmayer, Sonja; Hoffmann, Holger; Traue, Harald C; Aschauer, Harald

2018-01-01

Social interactive functions such as facial emotion recognition and smell identification have been shown to differ between women and men. However, little is known about how these differences are mirrored in patients with schizophrenia and how these abilities interact with each other and with other clinical variables in patients vs. healthy controls. Standardized instruments were used to assess facial emotion recognition [Facially Expressed Emotion Labelling (FEEL)] and smell identification [University of Pennsylvania Smell Identification Test (UPSIT)] in 51 patients with schizophrenia spectrum disorders and 79 healthy controls; furthermore, working memory functions and clinical variables were assessed. In both the univariate and the multivariate results, illness showed a significant influence on UPSIT and FEEL. The inclusion of age and working memory in the MANOVA resulted in a differential effect with sex and working memory as remaining significant factors. Duration of illness was correlated with both emotion recognition and smell identification in men only, whereas immediate general psychopathology and negative symptoms were associated with emotion recognition only in women. Being affected by schizophrenia spectrum disorder impacts one's ability to correctly recognize facial affects and identify odors. Converging evidence suggests a link between the investigated basic and social cognitive abilities in patients with schizophrenia spectrum disorders with a strong contribution of working memory and differential effects of modulators in women vs. men.

Associations between facial emotion recognition and young adolescents’ behaviors in bullying

PubMed Central

Gini, Gianluca; Altoè, Gianmarco

2017-01-01

This study investigated whether different behaviors young adolescents can act during bullying episodes were associated with their ability to recognize morphed facial expressions of the six basic emotions, expressed at high and low intensity. The sample included 117 middle-school students (45.3% girls; mean age = 12.4 years) who filled in a peer nomination questionnaire and individually performed a computerized emotion recognition task. Bayesian generalized mixed-effects models showed a complex picture, in which type and intensity of emotions, students’ behavior and gender interacted in explaining recognition accuracy. Results were discussed with a particular focus on negative emotions and suggesting a “neutral” nature of emotion recognition ability, which does not necessarily lead to moral behavior but can also be used for pursuing immoral goals. PMID:29131871

Compensatory premotor activity during affective face processing in subclinical carriers of a single mutant Parkin allele.

PubMed

Anders, Silke; Sack, Benjamin; Pohl, Anna; Münte, Thomas; Pramstaller, Peter; Klein, Christine; Binkofski, Ferdinand

2012-04-01

Patients with Parkinson's disease suffer from significant motor impairments and accompanying cognitive and affective dysfunction due to progressive disturbances of basal ganglia-cortical gating loops. Parkinson's disease has a long presymptomatic stage, which indicates a substantial capacity of the human brain to compensate for dopaminergic nerve degeneration before clinical manifestation of the disease. Neuroimaging studies provide evidence that increased motor-related cortical activity can compensate for progressive dopaminergic nerve degeneration in carriers of a single mutant Parkin or PINK1 gene, who show a mild but significant reduction of dopamine metabolism in the basal ganglia in the complete absence of clinical motor signs. However, it is currently unknown whether similar compensatory mechanisms are effective in non-motor basal ganglia-cortical gating loops. Here, we ask whether asymptomatic Parkin mutation carriers show altered patterns of brain activity during processing of facial gestures, and whether this might compensate for latent facial emotion recognition deficits. Current theories in social neuroscience assume that execution and perception of facial gestures are linked by a special class of visuomotor neurons ('mirror neurons') in the ventrolateral premotor cortex/pars opercularis of the inferior frontal gyrus (Brodmann area 44/6). We hypothesized that asymptomatic Parkin mutation carriers would show increased activity in this area during processing of affective facial gestures, replicating the compensatory motor effects that have previously been observed in these individuals. Additionally, Parkin mutation carriers might show altered activity in other basal ganglia-cortical gating loops. Eight asymptomatic heterozygous Parkin mutation carriers and eight matched controls underwent functional magnetic resonance imaging and a subsequent facial emotion recognition task. As predicted, Parkin mutation carriers showed significantly stronger activity in

Compensatory premotor activity during affective face processing in subclinical carriers of a single mutant Parkin allele

PubMed Central

Sack, Benjamin; Pohl, Anna; Münte, Thomas; Pramstaller, Peter; Klein, Christine; Binkofski, Ferdinand

2012-01-01

Patients with Parkinson's disease suffer from significant motor impairments and accompanying cognitive and affective dysfunction due to progressive disturbances of basal ganglia–cortical gating loops. Parkinson's disease has a long presymptomatic stage, which indicates a substantial capacity of the human brain to compensate for dopaminergic nerve degeneration before clinical manifestation of the disease. Neuroimaging studies provide evidence that increased motor-related cortical activity can compensate for progressive dopaminergic nerve degeneration in carriers of a single mutant Parkin or PINK1 gene, who show a mild but significant reduction of dopamine metabolism in the basal ganglia in the complete absence of clinical motor signs. However, it is currently unknown whether similar compensatory mechanisms are effective in non-motor basal ganglia–cortical gating loops. Here, we ask whether asymptomatic Parkin mutation carriers show altered patterns of brain activity during processing of facial gestures, and whether this might compensate for latent facial emotion recognition deficits. Current theories in social neuroscience assume that execution and perception of facial gestures are linked by a special class of visuomotor neurons (‘mirror neurons’) in the ventrolateral premotor cortex/pars opercularis of the inferior frontal gyrus (Brodmann area 44/6). We hypothesized that asymptomatic Parkin mutation carriers would show increased activity in this area during processing of affective facial gestures, replicating the compensatory motor effects that have previously been observed in these individuals. Additionally, Parkin mutation carriers might show altered activity in other basal ganglia–cortical gating loops. Eight asymptomatic heterozygous Parkin mutation carriers and eight matched controls underwent functional magnetic resonance imaging and a subsequent facial emotion recognition task. As predicted, Parkin mutation carriers showed significantly stronger

Reaction Time of Facial Affect Recognition in Asperger's Disorder for Cartoon and Real, Static and Moving Faces

ERIC Educational Resources Information Center

Miyahara, Motohide; Bray, Anne; Tsujii, Masatsugu; Fujita, Chikako; Sugiyama, Toshiro

2007-01-01

This study used a choice reaction-time paradigm to test the perceived impairment of facial affect recognition in Asperger's disorder. Twenty teenagers with Asperger's disorder and 20 controls were compared with respect to the latency and accuracy of response to happy or disgusted facial expressions, presented in cartoon or real images and in…

The Effects of Sex of Subject, Sex and Attractiveness of Photo on Facial Recognition.

ERIC Educational Resources Information Center

Carroo, Agatha W.; Mozingo, R.

1989-01-01

Assessed effect of sex of subject, and sex and attractiveness of photo on facial recognition with 25 male and 25 female college students. Found male subjects performed better with male faces with d' prime scores. (Author/ABL)

Real time gesture based control: A prototype development

NASA Astrophysics Data System (ADS)

Bhargava, Deepshikha; Solanki, L.; Rai, Satish Kumar

2016-03-01

The computer industry is getting advanced. In a short span of years, industry is growing high with advanced techniques. Robots have been replacing humans, increasing the efficiency, accessibility and accuracy of the system and creating man-machine interaction. Robotic industry is developing many new trends. However, they still need to be controlled by humans itself. This paper presents an approach to control a motor like a robot with hand gestures not by old ways like buttons or physical devices. Controlling robots with hand gestures is very popular now-a-days. Currently, at this level, gesture features are applied for detecting and tracking the hand in real time. A principal component analysis algorithm is being used for identification of a hand gesture by using open CV image processing library. Contours, convex-hull, and convexity defects are the gesture features. PCA is a statistical approach used for reducing the number of variables in hand recognition. While extracting the most relevant information (feature) contained in the images (hand). After detecting and recognizing hand a servo motor is being controlled, which uses hand gesture as an input device (like mouse and keyboard), and reduces human efforts.

Selection of suitable hand gestures for reliable myoelectric human computer interface.

PubMed

Castro, Maria Claudia F; Arjunan, Sridhar P; Kumar, Dinesh K

2015-04-09

Myoelectric controlled prosthetic hand requires machine based identification of hand gestures using surface electromyogram (sEMG) recorded from the forearm muscles. This study has observed that a sub-set of the hand gestures have to be selected for an accurate automated hand gesture recognition, and reports a method to select these gestures to maximize the sensitivity and specificity. Experiments were conducted where sEMG was recorded from the muscles of the forearm while subjects performed hand gestures and then was classified off-line. The performances of ten gestures were ranked using the proposed Positive-Negative Performance Measurement Index (PNM), generated by a series of confusion matrices. When using all the ten gestures, the sensitivity and specificity was 80.0% and 97.8%. After ranking the gestures using the PNM, six gestures were selected and these gave sensitivity and specificity greater than 95% (96.5% and 99.3%); Hand open, Hand close, Little finger flexion, Ring finger flexion, Middle finger flexion and Thumb flexion. This work has shown that reliable myoelectric based human computer interface systems require careful selection of the gestures that have to be recognized and without such selection, the reliability is poor.

Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles.

PubMed

Hughes, Dana; Profita, Halley; Radzihovsky, Sarah; Correll, Nikolaus

2017-01-24

We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures.

Facial recognition using multisensor images based on localized kernel eigen spaces.

PubMed

Gundimada, Satyanadh; Asari, Vijayan K

2009-06-01

A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Does Facial Expression Recognition Provide a Toehold for the Development of Emotion Understanding?

ERIC Educational Resources Information Center

Strand, Paul S.; Downs, Andrew; Barbosa-Leiker, Celestina

2016-01-01

The authors explored predictions from basic emotion theory (BET) that facial emotion expression recognition skills are insular with respect to their own development, and yet foundational to the development of emotional perspective-taking skills. Participants included 417 preschool children for whom estimates of these 2 emotion understanding…

Facial expression recognition and emotional regulation in narcolepsy with cataplexy.

PubMed

Bayard, Sophie; Croisier Langenier, Muriel; Dauvilliers, Yves

2013-04-01

Cataplexy is pathognomonic of narcolepsy with cataplexy, and defined by a transient loss of muscle tone triggered by strong emotions. Recent researches suggest abnormal amygdala function in narcolepsy with cataplexy. Emotion treatment and emotional regulation strategies are complex functions involving cortical and limbic structures, like the amygdala. As the amygdala has been shown to play a role in facial emotion recognition, we tested the hypothesis that patients with narcolepsy with cataplexy would have impaired recognition of facial emotional expressions compared with patients affected with central hypersomnia without cataplexy and healthy controls. We also aimed to determine whether cataplexy modulates emotional regulation strategies. Emotional intensity, arousal and valence ratings on Ekman faces displaying happiness, surprise, fear, anger, disgust, sadness and neutral expressions of 21 drug-free patients with narcolepsy with cataplexy were compared with 23 drug-free sex-, age- and intellectual level-matched adult patients with hypersomnia without cataplexy and 21 healthy controls. All participants underwent polysomnography recording and multiple sleep latency tests, and completed depression, anxiety and emotional regulation questionnaires. Performance of patients with narcolepsy with cataplexy did not differ from patients with hypersomnia without cataplexy or healthy controls on both intensity rating of each emotion on its prototypical label and mean ratings for valence and arousal. Moreover, patients with narcolepsy with cataplexy did not use different emotional regulation strategies. The level of depressive and anxious symptoms in narcolepsy with cataplexy did not differ from the other groups. Our results demonstrate that narcolepsy with cataplexy accurately perceives and discriminates facial emotions, and regulates emotions normally. The absence of alteration of perceived affective valence remains a major clinical interest in narcolepsy with cataplexy

Mapping and Manipulating Facial Expression

ERIC Educational Resources Information Center

Theobald, Barry-John; Matthews, Iain; Mangini, Michael; Spies, Jeffrey R.; Brick, Timothy R.; Cohn, Jeffrey F.; Boker, Steven M.

2009-01-01

Nonverbal visual cues accompany speech to supplement the meaning of spoken words, signify emotional state, indicate position in discourse, and provide back-channel feedback. This visual information includes head movements, facial expressions and body gestures. In this article we describe techniques for manipulating both verbal and nonverbal facial…

Sex differences in emotion recognition: Evidence for a small overall female superiority on facial disgust.

PubMed

Connolly, Hannah L; Lefevre, Carmen E; Young, Andrew W; Lewis, Gary J

2018-05-21

Although it is widely believed that females outperform males in the ability to recognize other people's emotions, this conclusion is not well supported by the extant literature. The current study sought to provide a strong test of the female superiority hypothesis by investigating sex differences in emotion recognition for five basic emotions using stimuli well-calibrated for individual differences assessment, across two expressive domains (face and body), and in a large sample (N = 1,022: Study 1). We also assessed the stability and generalizability of our findings with two independent replication samples (N = 303: Study 2, N = 634: Study 3). In Study 1, we observed that females were superior to males in recognizing facial disgust and sadness. In contrast, males were superior to females in recognizing bodily happiness. The female superiority for recognition of facial disgust was replicated in Studies 2 and 3, and this observation also extended to an independent stimulus set in Study 2. No other sex differences were stable across studies. These findings provide evidence for the presence of sex differences in emotion recognition ability, but show that these differences are modest in magnitude and appear to be limited to facial disgust. We discuss whether this sex difference may reflect human evolutionary imperatives concerning reproductive fitness and child care. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter.

PubMed

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-17

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor's stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

Reduced Reliance on Optimal Facial Information for Identity Recognition in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Leonard, Hayley C.; Annaz, Dagmara; Karmiloff-Smith, Annette; Johnson, Mark H.

2013-01-01

Previous research into face processing in autism spectrum disorder (ASD) has revealed atypical biases toward particular facial information during identity recognition. Specifically, a focus on features (or high spatial frequencies [HSFs]) has been reported for both face and nonface processing in ASD. The current study investigated the development…

Speech-associated gestures, Broca’s area, and the human mirror system

PubMed Central

Skipper, Jeremy I.; Goldin-Meadow, Susan; Nusbaum, Howard C.; Small, Steven L

2009-01-01

Speech-associated gestures are hand and arm movements that not only convey semantic information to listeners but are themselves actions. Broca’s area has been assumed to play an important role both in semantic retrieval or selection (as part of a language comprehension system) and in action recognition (as part of a “mirror” or “observation–execution matching” system). We asked whether the role that Broca’s area plays in processing speech-associated gestures is consistent with the semantic retrieval/selection account (predicting relatively weak interactions between Broca’s area and other cortical areas because the meaningful information that speech-associated gestures convey reduces semantic ambiguity and thus reduces the need for semantic retrieval/selection) or the action recognition account (predicting strong interactions between Broca’s area and other cortical areas because speech-associated gestures are goal-direct actions that are “mirrored”). We compared the functional connectivity of Broca’s area with other cortical areas when participants listened to stories while watching meaningful speech-associated gestures, speech-irrelevant self-grooming hand movements, or no hand movements. A network analysis of neuroimaging data showed that interactions involving Broca’s area and other cortical areas were weakest when spoken language was accompanied by meaningful speech-associated gestures, and strongest when spoken language was accompanied by self-grooming hand movements or by no hand movements at all. Results are discussed with respect to the role that the human mirror system plays in processing speech-associated movements. PMID:17533001

Meta-Analysis of Facial Emotion Recognition in Behavioral Variant Frontotemporal Dementia: Comparison With Alzheimer Disease and Healthy Controls.

PubMed

Bora, Emre; Velakoulis, Dennis; Walterfang, Mark

2016-07-01

Behavioral disturbances and lack of empathy are distinctive clinical features of behavioral variant frontotemporal dementia (bvFTD) in comparison to Alzheimer disease (AD). The aim of this meta-analytic review was to compare facial emotion recognition performances of bvFTD with healthy controls and AD. The current meta-analysis included a total of 19 studies and involved comparisons of 288 individuals with bvFTD and 329 healthy controls and 162 bvFTD and 147 patients with AD. Facial emotion recognition was significantly impaired in bvFTD in comparison to the healthy controls (d = 1.81) and AD (d = 1.23). In bvFTD, recognition of negative emotions, especially anger (d = 1.48) and disgust (d = 1.41), were severely impaired. Emotion recognition was significantly impaired in bvFTD in comparison to AD in all emotions other than happiness. Impairment of emotion recognition is a relatively specific feature of bvFTD. Routine assessment of social-cognitive abilities including emotion recognition can be helpful in better differentiating between cortical dementias such as bvFTD and AD. © The Author(s) 2016.

Shy children are less sensitive to some cues to facial recognition.

PubMed

Brunet, Paul M; Mondloch, Catherine J; Schmidt, Louis A

2010-02-01

Temperamental shyness in children is characterized by avoidance of faces and eye contact, beginning in infancy. We conducted two studies to determine whether temperamental shyness was associated with deficits in sensitivity to some cues to facial identity. In Study 1, 40 typically developing 10-year-old children made same/different judgments about pairs of faces that differed in the appearance of individual features, the shape of the external contour, or the spacing among features; their parent completed the Colorado childhood temperament inventory (CCTI). Children who scored higher on CCTI shyness made more errors than their non-shy counterparts only when discriminating faces based on the spacing of features. Differences in accuracy were not related to other scales of the CCTI. In Study 2, we showed that these differences were face-specific and cannot be attributed to differences in task difficulty. Findings suggest that shy children are less sensitive to some cues to facial recognition possibly underlying their inability to distinguish certain facial emotions in others, leading to a cascade of secondary negative effects in social behaviour.

Eye tracking reveals a crucial role for facial motion in recognition of faces by infants

PubMed Central

Xiao, Naiqi G.; Quinn, Paul C.; Liu, Shaoying; Ge, Liezhong; Pascalis, Olivier; Lee, Kang

2015-01-01

Current knowledge about face processing in infancy comes largely from studies using static face stimuli, but faces that infants see in the real world are mostly moving ones. To bridge this gap, 3-, 6-, and 9-month-old Asian infants (N = 118) were familiarized with either moving or static Asian female faces and then their face recognition was tested with static face images. Eye tracking methodology was used to record eye movements during familiarization and test phases. The results showed a developmental change in eye movement patterns, but only for the moving faces. In addition, the more infants shifted their fixations across facial regions, the better was their face recognition, but only for the moving faces. The results suggest that facial movement influences the way faces are encoded from early in development. PMID:26010387

Facial Expression Recognition: Can Preschoolers with Cochlear Implants and Hearing Aids Catch It?

ERIC Educational Resources Information Center

Wang, Yifang; Su, Yanjie; Fang, Ping; Zhou, Qingxia

2011-01-01

Tager-Flusberg and Sullivan (2000) presented a cognitive model of theory of mind (ToM), in which they thought ToM included two components--a social-perceptual component and a social-cognitive component. Facial expression recognition (FER) is an ability tapping the social-perceptual component. Previous findings suggested that normal hearing…

Attention to Social Stimuli and Facial Identity Recognition Skills in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Wilson, C. E.; Brock, J.; Palermo, R.

2010-01-01

Background: Previous research suggests that individuals with autism spectrum disorder (ASD) have a reduced preference for viewing social stimuli in the environment and impaired facial identity recognition. Methods: Here, we directly tested a link between these two phenomena in 13 ASD children and 13 age-matched typically developing (TD) controls.…

Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles †

PubMed Central

Hughes, Dana; Profita, Halley; Radzihovsky, Sarah; Correll, Nikolaus

2017-01-01

We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures. PMID:28125010

Facial emotion recognition deficits: The new face of schizophrenia

PubMed Central

Behere, Rishikesh V.

2015-01-01

Schizophrenia has been classically described to have positive, negative, and cognitive symptom dimension. Emerging evidence strongly supports a fourth dimension of social cognitive symptoms with facial emotion recognition deficits (FERD) representing a new face in our understanding of this complex disorder. FERD have been described to be one among the important deficits in schizophrenia and could be trait markers for the disorder. FERD are associated with socio-occupational dysfunction and hence are of important clinical relevance. This review discusses FERD in schizophrenia, challenges in its assessment in our cultural context, its implications in understanding neurobiological mechanisms and clinical applications. PMID:26600574

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

PubMed Central

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-01

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity. PMID:28106716

Children's Recognition of Emotional Facial Expressions Through Photographs and Drawings.

PubMed

Brechet, Claire

2017-01-01

The author's purpose was to examine children's recognition of emotional facial expressions, by comparing two types of stimulus: photographs and drawings. The author aimed to investigate whether drawings could be considered as a more evocative material than photographs, as a function of age and emotion. Five- and 7-year-old children were presented with photographs and drawings displaying facial expressions of 4 basic emotions (i.e., happiness, sadness, anger, and fear) and were asked to perform a matching task by pointing to the face corresponding to the target emotion labeled by the experimenter. The photographs we used were selected from the Radboud Faces Database and the drawings were designed on the basis of both the facial components involved in the expression of these emotions and the graphic cues children tend to use when asked to depict these emotions in their own drawings. Our results show that drawings are better recognized than photographs, for sadness, anger, and fear (with no difference for happiness, due to a ceiling effect). And that the difference between the 2 types of stimuli tends to be more important for 5-year-olds compared to 7-year-olds. These results are discussed in view of their implications, both for future research and for practical application.

Development of a Wearable Controller for Gesture-Recognition-Based Applications Using Polyvinylidene Fluoride.

PubMed

Van Volkinburg, Kyle; Washington, Gregory

2017-08-01

This paper reports on a wearable gesture-based controller fabricated using the sensing capabilities of the flexible thin-film piezoelectric polymer polyvinylidene fluoride (PVDF) which is shown to repeatedly and accurately discern, in real time, between right and left hand gestures. The PVDF is affixed to a compression sleeve worn on the forearm to create a wearable device that is flexible, adaptable, and highly shape conforming. Forearm muscle movements, which drive hand motions, are detected by the PVDF which outputs its voltage signal to a developed microcontroller-based board and processed by an artificial neural network that was trained to recognize the generated voltage profile of right and left hand gestures. The PVDF has been spatially shaded (etched) in such a way as to increase sensitivity to expected deformations caused by the specific muscles employed in making the targeted right and left gestures. The device proves to be exceptionally accurate both when positioned as intended and when rotated and translated on the forearm.

The interaction between embodiment and empathy in facial expression recognition

PubMed Central

Jospe, Karine; Flöel, Agnes; Lavidor, Michal

2018-01-01

Abstract Previous research has demonstrated that the Action-Observation Network (AON) is involved in both emotional-embodiment (empathy) and action-embodiment mechanisms. In this study, we hypothesized that interfering with the AON will impair action recognition and that this impairment will be modulated by empathy levels. In Experiment 1 (n = 90), participants were asked to recognize facial expressions while their facial motion was restricted. In Experiment 2 (n = 50), we interfered with the AON by applying transcranial Direct Current Stimulation to the motor cortex. In both experiments, we found that interfering with the AON impaired the performance of participants with high empathy levels; however, for the first time, we demonstrated that the interference enhanced the performance of participants with low empathy. This novel finding suggests that the embodiment module may be flexible, and that it can be enhanced in individuals with low empathy by simple manipulation of motor activation. PMID:29378022

Eye tracking reveals a crucial role for facial motion in recognition of faces by infants.

PubMed

Xiao, Naiqi G; Quinn, Paul C; Liu, Shaoying; Ge, Liezhong; Pascalis, Olivier; Lee, Kang

2015-06-01

Current knowledge about face processing in infancy comes largely from studies using static face stimuli, but faces that infants see in the real world are mostly moving ones. To bridge this gap, 3-, 6-, and 9-month-old Asian infants (N = 118) were familiarized with either moving or static Asian female faces, and then their face recognition was tested with static face images. Eye-tracking methodology was used to record eye movements during the familiarization and test phases. The results showed a developmental change in eye movement patterns, but only for the moving faces. In addition, the more infants shifted their fixations across facial regions, the better their face recognition was, but only for the moving faces. The results suggest that facial movement influences the way faces are encoded from early in development. (c) 2015 APA, all rights reserved).