expression-invariant face recognition: Topics by Science.gov

Sample records for expression-invariant face recognition

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.
Expression-invariant representations of faces.

PubMed

Bronstein, Alexander M; Bronstein, Michael M; Kimmel, Ron

2007-01-01

Addressed here is the problem of constructing and analyzing expression-invariant representations of human faces. We demonstrate and justify experimentally a simple geometric model that allows to describe facial expressions as isometric deformations of the facial surface. The main step in the construction of expression-invariant representation of a face involves embedding of the facial intrinsic geometric structure into some low-dimensional space. We study the influence of the embedding space geometry and dimensionality choice on the representation accuracy and argue that compared to its Euclidean counterpart, spherical embedding leads to notably smaller metric distortions. We experimentally support our claim showing that a smaller embedding error leads to better recognition.
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View.

PubMed

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

2016-08-08

Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.
Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View

PubMed Central

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

2016-01-01

Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition. PMID:27499252
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.
Robust kernel representation with statistical local features for face recognition.

PubMed

Yang, Meng; Zhang, Lei; Shiu, Simon Chi-Keung; Zhang, David

2013-06-01

Factors such as misalignment, pose variation, and occlusion make robust face recognition a difficult problem. It is known that statistical features such as local binary pattern are effective for local feature extraction, whereas the recently proposed sparse or collaborative representation-based classification has shown interesting results in robust face recognition. In this paper, we propose a novel robust kernel representation model with statistical local features (SLF) for robust face recognition. Initially, multipartition max pooling is used to enhance the invariance of SLF to image registration error. Then, a kernel-based representation model is proposed to fully exploit the discrimination information embedded in the SLF, and robust regression is adopted to effectively handle the occlusion in face images. Extensive experiments are conducted on benchmark face databases, including extended Yale B, AR (A. Martinez and R. Benavente), multiple pose, illumination, and expression (multi-PIE), facial recognition technology (FERET), face recognition grand challenge (FRGC), and labeled faces in the wild (LFW), which have different variations of lighting, expression, pose, and occlusions, demonstrating the promising performance of the proposed method.
Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

NASA Astrophysics Data System (ADS)

Yin, Xi; Liu, Xiaoming

2018-02-01

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.
High-resolution face verification using pore-scale facial features.

PubMed

Li, Dong; Zhou, Huiling; Lam, Kin-Man

2015-08-01

Face recognition methods, which usually represent face images using holistic or local facial features, rely heavily on alignment. Their performances also suffer a severe degradation under variations in expressions or poses, especially when there is one gallery per subject only. With the easy access to high-resolution (HR) face images nowadays, some HR face databases have recently been developed. However, few studies have tackled the use of HR information for face recognition or verification. In this paper, we propose a pose-invariant face-verification method, which is robust to alignment errors, using the HR information based on pore-scale facial features. A new keypoint descriptor, namely, pore-Principal Component Analysis (PCA)-Scale Invariant Feature Transform (PPCASIFT)-adapted from PCA-SIFT-is devised for the extraction of a compact set of distinctive pore-scale facial features. Having matched the pore-scale features of two-face regions, an effective robust-fitting scheme is proposed for the face-verification task. Experiments show that, with one frontal-view gallery only per subject, our proposed method outperforms a number of standard verification methods, and can achieve excellent accuracy even the faces are under large variations in expression and pose.
Behavioral dissociation between emotional and non-emotional facial expressions in congenital prosopagnosia

PubMed Central

Daini, Roberta; Comparetti, Chiara M.; Ricciardelli, Paola

2014-01-01

Neuropsychological and neuroimaging studies have shown that facial recognition and emotional expressions are dissociable. However, it is unknown if a single system supports the processing of emotional and non-emotional facial expressions. We aimed to understand if individuals with impairment in face recognition from birth (congenital prosopagnosia, CP) can use non-emotional facial expressions to recognize a face as an already seen one, and thus, process this facial dimension independently from features (which are impaired in CP), and basic emotional expressions. To this end, we carried out a behavioral study in which we compared the performance of 6 CP individuals to that of typical development individuals, using upright and inverted faces. Four avatar faces with a neutral expression were presented in the initial phase. The target faces presented in the recognition phase, in which a recognition task was requested (2AFC paradigm), could be identical (neutral) to those of the initial phase or present biologically plausible changes to features, non-emotional expressions, or emotional expressions. After this task, a second task was performed, in which the participants had to detect whether or not the recognized face exactly matched the study face or showed any difference. The results confirmed the CPs' impairment in the configural processing of the invariant aspects of the face, but also showed a spared configural processing of non-emotional facial expression (task 1). Interestingly and unlike the non-emotional expressions, the configural processing of emotional expressions was compromised in CPs and did not improve their change detection ability (task 2). These new results have theoretical implications for face perception models since they suggest that, at least in CPs, non-emotional expressions are processed configurally, can be dissociated from other facial dimensions, and may serve as a compensatory strategy to achieve face recognition. PMID:25520643
Behavioral dissociation between emotional and non-emotional facial expressions in congenital prosopagnosia.

PubMed

Daini, Roberta; Comparetti, Chiara M; Ricciardelli, Paola

2014-01-01

Neuropsychological and neuroimaging studies have shown that facial recognition and emotional expressions are dissociable. However, it is unknown if a single system supports the processing of emotional and non-emotional facial expressions. We aimed to understand if individuals with impairment in face recognition from birth (congenital prosopagnosia, CP) can use non-emotional facial expressions to recognize a face as an already seen one, and thus, process this facial dimension independently from features (which are impaired in CP), and basic emotional expressions. To this end, we carried out a behavioral study in which we compared the performance of 6 CP individuals to that of typical development individuals, using upright and inverted faces. Four avatar faces with a neutral expression were presented in the initial phase. The target faces presented in the recognition phase, in which a recognition task was requested (2AFC paradigm), could be identical (neutral) to those of the initial phase or present biologically plausible changes to features, non-emotional expressions, or emotional expressions. After this task, a second task was performed, in which the participants had to detect whether or not the recognized face exactly matched the study face or showed any difference. The results confirmed the CPs' impairment in the configural processing of the invariant aspects of the face, but also showed a spared configural processing of non-emotional facial expression (task 1). Interestingly and unlike the non-emotional expressions, the configural processing of emotional expressions was compromised in CPs and did not improve their change detection ability (task 2). These new results have theoretical implications for face perception models since they suggest that, at least in CPs, non-emotional expressions are processed configurally, can be dissociated from other facial dimensions, and may serve as a compensatory strategy to achieve face recognition.
Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

PubMed

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

2016-12-01

Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.
Face Recognition Using Local Quantized Patterns and Gabor Filters

NASA Astrophysics Data System (ADS)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.
Face or body? Oxytocin improves perception of emotions from facial expressions in incongruent emotional body context.

PubMed

Perry, Anat; Aviezer, Hillel; Goldstein, Pavel; Palgi, Sharon; Klein, Ehud; Shamay-Tsoory, Simone G

2013-11-01

The neuropeptide oxytocin (OT) has been repeatedly reported to play an essential role in the regulation of social cognition in humans in general, and specifically in enhancing the recognition of emotions from facial expressions. The later was assessed in different paradigms that rely primarily on isolated and decontextualized emotional faces. However, recent evidence has indicated that the perception of basic facial expressions is not context invariant and can be categorically altered by context, especially body context, at early perceptual levels. Body context has a strong effect on our perception of emotional expressions, especially when the actual target face and the contextually expected face are perceptually similar. To examine whether and how OT affects emotion recognition, we investigated the role of OT in categorizing facial expressions in incongruent body contexts. Our results show that in the combined process of deciphering emotions from facial expressions and from context, OT gives an advantage to the face. This advantage is most evident when the target face and the contextually expected face are perceptually similar. Copyright © 2013 Elsevier Ltd. All rights reserved.
False match elimination for face recognition based on SIFT algorithm

NASA Astrophysics Data System (ADS)

Gu, Xuyuan; Shi, Ping; Shao, Meide

2011-06-01

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.
Pose-Invariant Face Recognition via RGB-D Images.

PubMed

Sang, Gaoli; Li, Jing; Zhao, Qijun

2016-01-01

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.
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.
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.
Are face representations depth cue invariant?

PubMed

Dehmoobadsharifabadi, Armita; Farivar, Reza

2016-06-01

The visual system can process three-dimensional depth cues defining surfaces of objects, but it is unclear whether such information contributes to complex object recognition, including face recognition. The processing of different depth cues involves both dorsal and ventral visual pathways. We investigated whether facial surfaces defined by individual depth cues resulted in meaningful face representations-representations that maintain the relationship between the population of faces as defined in a multidimensional face space. We measured face identity aftereffects for facial surfaces defined by individual depth cues (Experiments 1 and 2) and tested whether the aftereffect transfers across depth cues (Experiments 3 and 4). Facial surfaces and their morphs to the average face were defined purely by one of shading, texture, motion, or binocular disparity. We obtained identification thresholds for matched (matched identity between adapting and test stimuli), non-matched (non-matched identity between adapting and test stimuli), and no-adaptation (showing only the test stimuli) conditions for each cue and across different depth cues. We found robust face identity aftereffect in both experiments. Our results suggest that depth cues do contribute to forming meaningful face representations that are depth cue invariant. Depth cue invariance would require integration of information across different areas and different pathways for object recognition, and this in turn has important implications for cortical models of visual object recognition.
Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition.

PubMed

Ding, Changxing; Choi, Jonghyun; Tao, Dacheng; Davis, Larry S

2016-03-01

To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract "Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face images. Specifically, the MDML-DCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of computing local binary patterns, yet is extremely robust to pose and expression variations. MDML-DCPs comprehensively yet efficiently encodes the invariant characteristics of a face image from multiple levels into patterns that are highly discriminative of inter-personal differences but robust to intra-personal variations. Experimental results on the FERET, CAS-PERL-R1, FRGC 2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local descriptors (e.g., LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face identification and face verification tasks. More impressively, the best performance is achieved on the challenging LFW and FRGC 2.0 databases by deploying MDML-DCPs in a simple recognition scheme.
Evidence for view-invariant face recognition units in unfamiliar face learning.

PubMed

Etchells, David B; Brooks, Joseph L; Johnston, Robert A

2017-05-01

Many models of face recognition incorporate the idea of a face recognition unit (FRU), an abstracted representation formed from each experience of a face which aids recognition under novel viewing conditions. Some previous studies have failed to find evidence of this FRU representation. Here, we report three experiments which investigated this theoretical construct by modifying the face learning procedure from that in previous work. During learning, one or two views of previously unfamiliar faces were shown to participants in a serial matching task. Later, participants attempted to recognize both seen and novel views of the learned faces (recognition phase). Experiment 1 tested participants' recognition of a novel view, a day after learning. Experiment 2 was identical, but tested participants on the same day as learning. Experiment 3 repeated Experiment 1, but tested participants on a novel view that was outside the rotation of those views learned. Results revealed a significant advantage, across all experiments, for recognizing a novel view when two views had been learned compared to single view learning. The observed view invariance supports the notion that an FRU representation is established during multi-view face learning under particular learning conditions.

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.
Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

NASA Astrophysics Data System (ADS)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image. Experiments conducted on various popular face databases show promising performance of the proposed algorithm in varying lighting, expression, and partial occlusion conditions. Four databases were used for testing the performance of the proposed system: Yale Face database, Extended Yale Face database B, Japanese Female Facial Expression database, and CMU AMP Facial Expression database. The experimental results in all four databases show the effectiveness of the proposed system. Also, the computation cost is lower because of the simplified calculation steps. Research work is progressing to investigate the effectiveness of the proposed face recognition method on pose-varying conditions as well. It is envisaged that a multilane approach of trained frameworks at different pose bins and an appropriate voting strategy would lead to a good recognition rate in such situation.
Face recognition: a convolutional neural-network approach.

PubMed

Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

1997-01-01

We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.
Orientation Encoding and Viewpoint Invariance in Face Recognition: Inferring Neural Properties from Large-Scale Signals.

PubMed

Ramírez, Fernando M

2018-05-01

Viewpoint-invariant face recognition is thought to be subserved by a distributed network of occipitotemporal face-selective areas that, except for the human anterior temporal lobe, have been shown to also contain face-orientation information. This review begins by highlighting the importance of bilateral symmetry for viewpoint-invariant recognition and face-orientation perception. Then, monkey electrophysiological evidence is surveyed describing key tuning properties of face-selective neurons-including neurons bimodally tuned to mirror-symmetric face-views-followed by studies combining functional magnetic resonance imaging (fMRI) and multivariate pattern analyses to probe the representation of face-orientation and identity information in humans. Altogether, neuroimaging studies suggest that face-identity is gradually disentangled from face-orientation information along the ventral visual processing stream. The evidence seems to diverge, however, regarding the prevalent form of tuning of neural populations in human face-selective areas. In this context, caveats possibly leading to erroneous inferences regarding mirror-symmetric coding are exposed, including the need to distinguish angular from Euclidean distances when interpreting multivariate pattern analyses. On this basis, this review argues that evidence from the fusiform face area is best explained by a view-sensitive code reflecting head angular disparity, consistent with a role of this area in face-orientation perception. Finally, the importance is stressed of explicit models relating neural properties to large-scale signals.
Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz A.

1985-01-01

A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.
The roles of perceptual and conceptual information in face recognition.

PubMed

Schwartz, Linoy; Yovel, Galit

2016-11-01

The representation of familiar objects is comprised of perceptual information about their visual properties as well as the conceptual knowledge that we have about them. What is the relative contribution of perceptual and conceptual information to object recognition? Here, we examined this question by designing a face familiarization protocol during which participants were either exposed to rich perceptual information (viewing each face in different angles and illuminations) or with conceptual information (associating each face with a different name). Both conditions were compared with single-view faces presented with no labels. Recognition was tested on new images of the same identities to assess whether learning generated a view-invariant representation. Results showed better recognition of novel images of the learned identities following association of a face with a name label, but no enhancement following exposure to multiple face views. Whereas these findings may be consistent with the role of category learning in object recognition, face recognition was better for labeled faces only when faces were associated with person-related labels (name, occupation), but not with person-unrelated labels (object names or symbols). These findings suggest that association of meaningful conceptual information with an image shifts its representation from an image-based percept to a view-invariant concept. They further indicate that the role of conceptual information should be considered to account for the superior recognition that we have for familiar faces and objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Impaired perception of facial emotion in developmental prosopagnosia.

PubMed

Biotti, Federica; Cook, Richard

2016-08-01

Developmental prosopagnosia (DP) is a neurodevelopmental condition characterised by difficulties recognising faces. Despite severe difficulties recognising facial identity, expression recognition is typically thought to be intact in DP; case studies have described individuals who are able to correctly label photographic displays of facial emotion, and no group differences have been reported. This pattern of deficits suggests a locus of impairment relatively late in the face processing stream, after the divergence of expression and identity analysis pathways. To date, however, there has been little attempt to investigate emotion recognition systematically in a large sample of developmental prosopagnosics using sensitive tests. In the present study, we describe three complementary experiments that examine emotion recognition in a sample of 17 developmental prosopagnosics. In Experiment 1, we investigated observers' ability to make binary classifications of whole-face expression stimuli drawn from morph continua. In Experiment 2, observers judged facial emotion using only the eye-region (the rest of the face was occluded). Analyses of both experiments revealed diminished ability to classify facial expressions in our sample of developmental prosopagnosics, relative to typical observers. Imprecise expression categorisation was particularly evident in those individuals exhibiting apperceptive profiles, associated with problems encoding facial shape accurately. Having split the sample of prosopagnosics into apperceptive and non-apperceptive subgroups, only the apperceptive prosopagnosics were impaired relative to typical observers. In our third experiment, we examined the ability of observers' to classify the emotion present within segments of vocal affect. Despite difficulties judging facial emotion, the prosopagnosics exhibited excellent recognition of vocal affect. Contrary to the prevailing view, our results suggest that many prosopagnosics do experience difficulties classifying expressions, particularly those with apperceptive profiles. These individuals may have difficulties forming view-invariant structural descriptions at an early stage in the face processing stream, before identity and expression pathways diverge. Copyright © 2016 Elsevier Ltd. All rights reserved.
Face identity matching is selectively impaired in developmental prosopagnosia.

PubMed

Fisher, Katie; Towler, John; Eimer, Martin

2017-04-01

Individuals with developmental prosopagnosia (DP) have severe face recognition deficits, but the mechanisms that are responsible for these deficits have not yet been fully identified. We assessed whether the activation of visual working memory for individual faces is selectively impaired in DP. Twelve DPs and twelve age-matched control participants were tested in a task where they reported whether successively presented faces showed the same or two different individuals, and another task where they judged whether the faces showed the same or different facial expressions. Repetitions versus changes of the other currently irrelevant attribute were varied independently. DPs showed impaired performance in the identity task, but performed at the same level as controls in the expression task. An electrophysiological marker for the activation of visual face memory by identity matches (N250r component) was strongly attenuated in the DP group, and the size of this attenuation was correlated with poor performance in a standardized face recognition test. Results demonstrate an identity-specific deficit of visual face memory in DPs. Their reduced sensitivity to identity matches in the presence of other image changes could result from earlier deficits in the perceptual extraction of image-invariant visual identity cues from face images. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
Age Invariance in Semantic and Episodic Metamemory: Both Younger and Older Adults Provide Accurate Feeling of Knowing For Names of Faces

PubMed Central

Eakin, Deborah K.; Hertzog, Christopher; Harris, William

2013-01-01

Age differences in feeling-of-knowing (FOK) accuracy were examined for both episodic memory and semantic memory. Younger and older adults either viewed pictures of famous faces (semantic memory) or associated nonfamous faces and names (episodic memory) and were tested on their memory for the name of the presented face. Participants viewed the faces again and made a FOK prediction about future recognition of the name associated with the presented face. Finally, four-alternative forced-choice recognition memory for the name, cued by the face, was tested and confidence judgments (CJs) were collected for each recognition response. Age differences were not obtained in semantic memory or the resolution of semantic FOKs, defined by within-person correlations of FOKs with recognition memory performance. Although age differences were obtained in level of episodic memory, there were no age differences in the resolution of episodic FOKs. FOKs for correctly recognized items correlated reliably with CJs for both types of materials, and did not differ by age group. The results indicate age invariance in monitoring of retrieval processes for name-face associations. PMID:23537379
Age invariance in semantic and episodic metamemory: both younger and older adults provide accurate feeling-of-knowing for names of faces.

PubMed

Eakin, Deborah K; Hertzog, Christopher; Harris, William

2014-01-01

Age differences in feeling-of-knowing (FOK) accuracy were examined for both episodic memory and semantic memory. Younger and older adults either viewed pictures of famous faces (semantic memory) or associated non-famous faces and names (episodic memory) and were tested on their memory for the name of the presented face. Participants viewed the faces again and made a FOK prediction about future recognition of the name associated with the presented face. Finally, four-alternative forced-choice recognition memory for the name, cued by the face, was tested and confidence judgments (CJs) were collected for each recognition response. Age differences were not obtained in semantic memory or the resolution of semantic FOKs, defined by within-person correlations of FOKs with recognition memory performance. Although age differences were obtained in level of episodic memory, there were no age differences in the resolution of episodic FOKs. FOKs for correctly recognized items correlated reliably with CJs for both types of materials, and did not differ by age group. The results indicate age invariance in monitoring of retrieval processes for name-face associations.
Pose Invariant Face Recognition Based on Hybrid Dominant Frequency Features

NASA Astrophysics Data System (ADS)

Wijaya, I. Gede Pasek Suta; Uchimura, Keiichi; Hu, Zhencheng

Face recognition is one of the most active research areas in pattern recognition, not only because the face is a human biometric characteristics of human being but also because there are many potential applications of the face recognition which range from human-computer interactions to authentication, security, and surveillance. This paper presents an approach to pose invariant human face image recognition. The proposed scheme is based on the analysis of discrete cosine transforms (DCT) and discrete wavelet transforms (DWT) of face images. From both the DCT and DWT domain coefficients, which describe the facial information, we build compact and meaningful features vector, using simple statistical measures and quantization. This feature vector is called as the hybrid dominant frequency features. Then, we apply a combination of the L2 and Lq metric to classify the hybrid dominant frequency features to a person's class. The aim of the proposed system is to overcome the high memory space requirement, the high computational load, and the retraining problems of previous methods. The proposed system is tested using several face databases and the experimental results are compared to a well-known Eigenface method. The proposed method shows good performance, robustness, stability, and accuracy without requiring geometrical normalization. Furthermore, the purposed method has low computational cost, requires little memory space, and can overcome retraining problem.
Recognizing Age-Separated Face Images: Humans and Machines

PubMed Central

Yadav, Daksha; Singh, Richa; Vatsa, Mayank; Noore, Afzel

2014-01-01

Humans utilize facial appearance, gender, expression, aging pattern, and other ancillary information to recognize individuals. It is interesting to observe how humans perceive facial age. Analyzing these properties can help in understanding the phenomenon of facial aging and incorporating the findings can help in designing effective algorithms. Such a study has two components - facial age estimation and age-separated face recognition. Age estimation involves predicting the age of an individual given his/her facial image. On the other hand, age-separated face recognition consists of recognizing an individual given his/her age-separated images. In this research, we investigate which facial cues are utilized by humans for estimating the age of people belonging to various age groups along with analyzing the effect of one's gender, age, and ethnicity on age estimation skills. We also analyze how various facial regions such as binocular and mouth regions influence age estimation and recognition capabilities. Finally, we propose an age-invariant face recognition algorithm that incorporates the knowledge learned from these observations. Key observations of our research are: (1) the age group of newborns and toddlers is easiest to estimate, (2) gender and ethnicity do not affect the judgment of age group estimation, (3) face as a global feature, is essential to achieve good performance in age-separated face recognition, and (4) the proposed algorithm yields improved recognition performance compared to existing algorithms and also outperforms a commercial system in the young image as probe scenario. PMID:25474200
Recognizing age-separated face images: humans and machines.

PubMed

Yadav, Daksha; Singh, Richa; Vatsa, Mayank; Noore, Afzel

2014-01-01

Humans utilize facial appearance, gender, expression, aging pattern, and other ancillary information to recognize individuals. It is interesting to observe how humans perceive facial age. Analyzing these properties can help in understanding the phenomenon of facial aging and incorporating the findings can help in designing effective algorithms. Such a study has two components--facial age estimation and age-separated face recognition. Age estimation involves predicting the age of an individual given his/her facial image. On the other hand, age-separated face recognition consists of recognizing an individual given his/her age-separated images. In this research, we investigate which facial cues are utilized by humans for estimating the age of people belonging to various age groups along with analyzing the effect of one's gender, age, and ethnicity on age estimation skills. We also analyze how various facial regions such as binocular and mouth regions influence age estimation and recognition capabilities. Finally, we propose an age-invariant face recognition algorithm that incorporates the knowledge learned from these observations. Key observations of our research are: (1) the age group of newborns and toddlers is easiest to estimate, (2) gender and ethnicity do not affect the judgment of age group estimation, (3) face as a global feature, is essential to achieve good performance in age-separated face recognition, and (4) the proposed algorithm yields improved recognition performance compared to existing algorithms and also outperforms a commercial system in the young image as probe scenario.
Age-related increase of image-invariance in the fusiform face area.

PubMed

Nordt, Marisa; Semmelmann, Kilian; Genç, Erhan; Weigelt, Sarah

2018-06-01

Face recognition undergoes prolonged development from childhood to adulthood, thereby raising the question which neural underpinnings are driving this development. Here, we address the development of the neural foundation of the ability to recognize a face across naturally varying images. Fourteen children (ages, 7-10) and 14 adults (ages, 20-23) watched images of either the same or different faces in a functional magnetic resonance imaging adaptation paradigm. The same face was either presented in exact image repetitions or in varying images. Additionally, a subset of participants completed a behavioral task, in which they decided if the face in consecutively presented images belonged to the same person. Results revealed age-related increases in neural sensitivity to face identity in the fusiform face area. Importantly, ventral temporal face-selective regions exhibited more image-invariance - as indicated by stronger adaptation for different images of the same person - in adults compared to children. Crucially, the amount of adaptation to face identity across varying images was correlated with the ability to recognize individual faces in different images. These results suggest that the increase of image-invariance in face-selective regions might be related to the development of face recognition skills. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
How a Hat May Affect 3-Month-Olds' Recognition of a Face: An Eye-Tracking Study

PubMed Central

Bulf, Hermann; Valenza, Eloisa; Turati, Chiara

2013-01-01

Recent studies have shown that infants’ face recognition rests on a robust face representation that is resilient to a variety of facial transformations such as rotations in depth, motion, occlusion or deprivation of inner/outer features. Here, we investigated whether 3-month-old infants’ ability to represent the invariant aspects of a face is affected by the presence of an external add-on element, i.e. a hat. Using a visual habituation task, three experiments were carried out in which face recognition was investigated by manipulating the presence/absence of a hat during face encoding (i.e. habituation phase) and face recognition (i.e. test phase). An eye-tracker system was used to record the time infants spent looking at face-relevant information compared to the hat. The results showed that infants’ face recognition was not affected by the presence of the external element when the type of the hat did not vary between the habituation and test phases, and when both the novel and the familiar face wore the same hat during the test phase (Experiment 1). Infants’ ability to recognize the invariant aspects of a face was preserved also when the hat was absent in the habituation phase and the same hat was shown only during the test phase (Experiment 2). Conversely, when the novel face identity competed with a novel hat, the hat triggered the infants’ attention, interfering with the recognition process and preventing the infants’ preference for the novel face during the test phase (Experiment 3). Findings from the current study shed light on how faces and objects are processed when they are simultaneously presented in the same visual scene, contributing to an understanding of how infants respond to the multiple and composite information available in their surrounding environment. PMID:24349378
How a hat may affect 3-month-olds' recognition of a face: an eye-tracking study.

PubMed

Bulf, Hermann; Valenza, Eloisa; Turati, Chiara

2013-01-01

Recent studies have shown that infants' face recognition rests on a robust face representation that is resilient to a variety of facial transformations such as rotations in depth, motion, occlusion or deprivation of inner/outer features. Here, we investigated whether 3-month-old infants' ability to represent the invariant aspects of a face is affected by the presence of an external add-on element, i.e. a hat. Using a visual habituation task, three experiments were carried out in which face recognition was investigated by manipulating the presence/absence of a hat during face encoding (i.e. habituation phase) and face recognition (i.e. test phase). An eye-tracker system was used to record the time infants spent looking at face-relevant information compared to the hat. The results showed that infants' face recognition was not affected by the presence of the external element when the type of the hat did not vary between the habituation and test phases, and when both the novel and the familiar face wore the same hat during the test phase (Experiment 1). Infants' ability to recognize the invariant aspects of a face was preserved also when the hat was absent in the habituation phase and the same hat was shown only during the test phase (Experiment 2). Conversely, when the novel face identity competed with a novel hat, the hat triggered the infants' attention, interfering with the recognition process and preventing the infants' preference for the novel face during the test phase (Experiment 3). Findings from the current study shed light on how faces and objects are processed when they are simultaneously presented in the same visual scene, contributing to an understanding of how infants respond to the multiple and composite information available in their surrounding environment.
System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database

NASA Astrophysics Data System (ADS)

Petpairote, Chayanut; Madarasmi, Suthep; Chamnongthai, Kosin

2018-01-01

The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn-Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.
Recognition of rotated images using the multi-valued neuron and rotation-invariant 2D Fourier descriptors

NASA Astrophysics Data System (ADS)

Aizenberg, Evgeni; Bigio, Irving J.; Rodriguez-Diaz, Eladio

2012-03-01

The Fourier descriptors paradigm is a well-established approach for affine-invariant characterization of shape contours. In the work presented here, we extend this method to images, and obtain a 2D Fourier representation that is invariant to image rotation. The proposed technique retains phase uniqueness, and therefore structural image information is not lost. Rotation-invariant phase coefficients were used to train a single multi-valued neuron (MVN) to recognize satellite and human face images rotated by a wide range of angles. Experiments yielded 100% and 96.43% classification rate for each data set, respectively. Recognition performance was additionally evaluated under effects of lossy JPEG compression and additive Gaussian noise. Preliminary results show that the derived rotation-invariant features combined with the MVN provide a promising scheme for efficient recognition of rotated images.
Random-Profiles-Based 3D Face Recognition System

PubMed Central

Joongrock, Kim; Sunjin, Yu; Sangyoun, Lee

2014-01-01

In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation. PMID:24691101
A biologically inspired neural network model to transformation invariant object recognition

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

2007-09-01

Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to perform a successful recognition task in general. Further, the residual critic error in DHP is generally smaller than that of HDP, and DHP achieves a 100% success rate more frequently than HDP for individual objects/subjects. On the other hand, HDP is more robust than the DHP as far as success rate across the database is concerned when applied in a stochastic and uncertain environment, and the computational time involved in DHP is more.

Age differences in accuracy and choosing in eyewitness identification and face recognition.

PubMed

Searcy, J H; Bartlett, J C; Memon, A

1999-05-01

Studies of aging and face recognition show age-related increases in false recognitions of new faces. To explore implications of this false alarm effect, we had young and senior adults perform (1) three eye-witness identification tasks, using both target present and target absent lineups, and (2) and old/new recognition task in which a study list of faces was followed by a test including old and new faces, along with conjunctions of old faces. Compared with the young, seniors had lower accuracy and higher choosing rates on the lineups, and they also falsely recognized more new faces on the recognition test. However, after screening for perceptual processing deficits, there was no age difference in false recognition of conjunctions, or in discriminating old faces from conjunctions. We conclude that the false alarm effect generalizes to lineup identification, but does not extend to conjunction faces. The findings are consistent with age-related deficits in recollection of context and relative age invariance in perceptual integrative processes underlying the experience of familiarity.
A framework for the recognition of 3D faces and expressions

NASA Astrophysics Data System (ADS)

Li, Chao; Barreto, Armando

2006-04-01

Face recognition technology has been a focus both in academia and industry for the last couple of years because of its wide potential applications and its importance to meet the security needs of today's world. Most of the systems developed are based on 2D face recognition technology, which uses pictures for data processing. With the development of 3D imaging technology, 3D face recognition emerges as an alternative to overcome the difficulties inherent with 2D face recognition, i.e. sensitivity to illumination conditions and orientation positioning of the subject. But 3D face recognition still needs to tackle the problem of deformation of facial geometry that results from the expression changes of a subject. To deal with this issue, a 3D face recognition framework is proposed in this paper. It is composed of three subsystems: an expression recognition system, a system for the identification of faces with expression, and neutral face recognition system. A system for the recognition of faces with one type of expression (happiness) and neutral faces was implemented and tested on a database of 30 subjects. The results proved the feasibility of this framework.
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.
Qualitatively similar processing for own- and other-race faces: Evidence from efficiency and equivalent input noise.

PubMed

Shafai, Fakhri; Oruc, Ipek

2018-02-01

The other-race effect is the finding of diminished performance in recognition of other-race faces compared to those of own-race. It has been suggested that the other-race effect stems from specialized expert processes being tuned exclusively to own-race faces. In the present study, we measured recognition contrast thresholds for own- and other-race faces as well as houses for Caucasian observers. We have factored face recognition performance into two invariant aspects of visual function: efficiency, which is related to neural computations and processing demanded by the task, and equivalent input noise, related to signal degradation within the visual system. We hypothesized that if expert processes are available only to own-race faces, this should translate into substantially greater recognition efficiencies for own-race compared to other-race faces. Instead, we found similar recognition efficiencies for both own- and other-race faces. The other-race effect manifested as increased equivalent input noise. These results argue against qualitatively distinct perceptual processes. Instead they suggest that for Caucasian observers, similar neural computations underlie recognition of own- and other-race faces. Copyright © 2018 Elsevier Ltd. All rights reserved.
Newborns' Face Recognition over Changes in Viewpoint

ERIC Educational Resources Information Center

Turati, Chiara; Bulf, Hermann; Simion, Francesca

2008-01-01

The study investigated the origins of the ability to recognize faces despite rotations in depth. Four experiments are reported that tested, using the habituation technique, whether 1-to-3-day-old infants are able to recognize the invariant aspects of a face over changes in viewpoint. Newborns failed to recognize facial perceptual invariances…
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.
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. PMID:21734904
Face in profile view reduces perceived facial expression intensity: an eye-tracking study.

PubMed

Guo, Kun; Shaw, Heather

2015-02-01

Recent studies measuring the facial expressions of emotion have focused primarily on the perception of frontal face images. As we frequently encounter expressive faces from different viewing angles, having a mechanism which allows invariant expression perception would be advantageous to our social interactions. Although a couple of studies have indicated comparable expression categorization accuracy across viewpoints, it is unknown how perceived expression intensity and associated gaze behaviour change across viewing angles. Differences could arise because diagnostic cues from local facial features for decoding expressions could vary with viewpoints. Here we manipulated orientation of faces (frontal, mid-profile, and profile view) displaying six common facial expressions of emotion, and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. In comparison with frontal faces, profile faces slightly reduced identification rates for disgust and sad expressions, but significantly decreased perceived intensity for all tested expressions. Although quantitatively viewpoint had expression-specific influence on the proportion of fixations directed at local facial features, the qualitative gaze distribution within facial features (e.g., the eyes tended to attract the highest proportion of fixations, followed by the nose and then the mouth region) was independent of viewpoint and expression type. Our results suggest that the viewpoint-invariant facial expression processing is categorical perception, which could be linked to a viewpoint-invariant holistic gaze strategy for extracting expressive facial cues. Copyright © 2014 Elsevier B.V. All rights reserved.
No childhood development of viewpoint-invariant face recognition: evidence from 8-year-olds and adults.

PubMed

Crookes, Kate; Robbins, Rachel A

2014-10-01

Performance on laboratory face tasks improves across childhood, not reaching adult levels until adolescence. Debate surrounds the source of this development, with recent reviews suggesting that underlying face processing mechanisms are mature early in childhood and that the improvement seen on experimental tasks instead results from general cognitive/perceptual development. One face processing mechanism that has been argued to develop slowly is the ability to encode faces in a view-invariant manner (i.e., allowing recognition across changes in viewpoint). However, many previous studies have not controlled for general cognitive factors. In the current study, 8-year-olds and adults performed a recognition memory task with two study-test viewpoint conditions: same view (study front view, test front view) and change view (study front view, test three-quarter view). To allow quantitative comparison between children and adults, performance in the same view condition was matched across the groups by increasing the learning set size for adults. Results showed poorer memory in the change view condition than in the same view condition for both adults and children. Importantly, there was no quantitative difference between children and adults in the size of decrement in memory performance resulting from a change in viewpoint. This finding adds to growing evidence that face processing mechanisms are mature early in childhood. Copyright © 2014 Elsevier Inc. All rights reserved.
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.
Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864
The recognition of emotional expression in prosopagnosia: decoding whole and part faces.

PubMed

Stephan, Blossom Christa Maree; Breen, Nora; Caine, Diana

2006-11-01

Prosopagnosia is currently viewed within the constraints of two competing theories of face recognition, one highlighting the analysis of features, the other focusing on configural processing of the whole face. This study investigated the role of feature analysis versus whole face configural processing in the recognition of facial expression. A prosopagnosic patient, SC made expression decisions from whole and incomplete (eyes-only and mouth-only) faces where features had been obscured. SC was impaired at recognizing some (e.g., anger, sadness, and fear), but not all (e.g., happiness) emotional expressions from the whole face. Analyses of his performance on incomplete faces indicated that his recognition of some expressions actually improved relative to his performance on the whole face condition. We argue that in SC interference from damaged configural processes seem to override an intact ability to utilize part-based or local feature cues.
Transfer between pose and expression training in face recognition.

PubMed

Chen, Wenfeng; Liu, Chang Hong

2009-02-01

Prior research has shown that recognition of unfamiliar faces is susceptible to image variations due to pose and expression changes. However, little is known about how these variations on a new face are learnt and handled. We aimed to investigate whether exposures to one type of variation facilitate recognition in the untrained variation. In Experiment 1, faces were trained in multiple or single pose but were tested with a new expression. In Experiment 2, faces were trained in multiple or single expression but were tested in a new pose. We found that higher level of exposure to pose information facilitated recognition of the trained face in a new expression. However, multiple-expression training failed to transfer to a new pose. The findings suggest that generalisation of pose training may be extended to different types of variation whereas generalisation of expression training is largely confined within the trained type of variation.
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…
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.
Orienting to face expression during encoding improves men's recognition of own gender faces.

PubMed

Fulton, Erika K; Bulluck, Megan; Hertzog, Christopher

2015-10-01

It is unclear why women have superior episodic memory of faces, but the benefit may be partially the result of women engaging in superior processing of facial expressions. Therefore, we hypothesized that orienting instructions to attend to facial expression at encoding would significantly improve men's memory of faces and possibly reduce gender differences. We directed 203 college students (122 women) to study 120 faces under instructions to orient to either the person's gender or their emotional expression. They later took a recognition test of these faces by either judging whether they had previously studied the same person or that person with the exact same expression; the latter test evaluated recollection of specific facial details. Orienting to facial expressions during encoding significantly improved men's recognition of own-gender faces and eliminated the advantage that women had for male faces under gender orienting instructions. Although gender differences in spontaneous strategy use when orienting to faces cannot fully account for gender differences in face recognition, orienting men to facial expression during encoding is one way to significantly improve their episodic memory for male faces. Copyright © 2015 Elsevier B.V. All rights reserved.
The Right Place at the Right Time: Priming Facial Expressions with Emotional Face Components in Developmental Visual Agnosia

PubMed Central

Aviezer, Hillel; Hassin, Ran. R.; Perry, Anat; Dudarev, Veronica; Bentin, Shlomo

2012-01-01

The current study examined the nature of deficits in emotion recognition from facial expressions in case LG, an individual with a rare form of developmental visual agnosia (DVA). LG presents with profoundly impaired recognition of facial expressions, yet the underlying nature of his deficit remains unknown. During typical face processing, normal sighted individuals extract information about expressed emotions from face regions with activity diagnostic for specific emotion categories. Given LG’s impairment, we sought to shed light on his emotion perception by examining if priming facial expressions with diagnostic emotional face components would facilitate his recognition of the emotion expressed by the face. LG and control participants matched isolated face components with components appearing in a subsequently presented full-face and then categorized the face’s emotion. Critically, the matched components were from regions which were diagnostic or non-diagnostic of the emotion portrayed by the full face. In experiment 1, when the full faces were briefly presented (150 ms), LG’s performance was strongly influenced by the diagnosticity of the components: His emotion recognition was boosted within normal limits when diagnostic components were used and was obliterated when non-diagnostic components were used. By contrast, in experiment 2, when the face-exposure duration was extended (2000 ms), the beneficial effect of the diagnostic matching was diminished as was the detrimental effect of the non-diagnostic matching. These data highlight the impact of diagnostic facial features in normal expression recognition and suggest that impaired emotion recognition in DVA results from deficient visual integration across diagnostic face components. PMID:22349446
Good match exploration for infrared face recognition

NASA Astrophysics Data System (ADS)

Yang, Changcai; Zhou, Huabing; Sun, Sheng; Liu, Renfeng; Zhao, Ji; Ma, Jiayi

2014-11-01

Establishing good feature correspondence is a critical prerequisite and a challenging task for infrared (IR) face recognition. Recent studies revealed that the scale invariant feature transform (SIFT) descriptor outperforms other local descriptors for feature matching. However, it only uses local appearance information for matching, and hence inevitably leads to a number of false matches. To address this issue, this paper explores global structure information (GSI) among SIFT correspondences, and proposes a new method SIFT-GSI for good match exploration. This is achieved by fitting a smooth mapping function for the underlying correct matches, which involves softassign and deterministic annealing. Quantitative comparisons with state-of-the-art methods on a publicly available IR human face database demonstrate that SIFT-GSI significantly outperforms other methods for feature matching, and hence it is able to improve the reliability of IR face recognition systems.
The right place at the right time: priming facial expressions with emotional face components in developmental visual agnosia.

PubMed

Aviezer, Hillel; Hassin, Ran R; Perry, Anat; Dudarev, Veronica; Bentin, Shlomo

2012-04-01

The current study examined the nature of deficits in emotion recognition from facial expressions in case LG, an individual with a rare form of developmental visual agnosia (DVA). LG presents with profoundly impaired recognition of facial expressions, yet the underlying nature of his deficit remains unknown. During typical face processing, normal sighted individuals extract information about expressed emotions from face regions with activity diagnostic for specific emotion categories. Given LG's impairment, we sought to shed light on his emotion perception by examining if priming facial expressions with diagnostic emotional face components would facilitate his recognition of the emotion expressed by the face. LG and control participants matched isolated face components with components appearing in a subsequently presented full-face and then categorized the face's emotion. Critically, the matched components were from regions which were diagnostic or non-diagnostic of the emotion portrayed by the full face. In experiment 1, when the full faces were briefly presented (150 ms), LG's performance was strongly influenced by the diagnosticity of the components: his emotion recognition was boosted within normal limits when diagnostic components were used and was obliterated when non-diagnostic components were used. By contrast, in experiment 2, when the face-exposure duration was extended (2000 ms), the beneficial effect of the diagnostic matching was diminished as was the detrimental effect of the non-diagnostic matching. These data highlight the impact of diagnostic facial features in normal expression recognition and suggest that impaired emotion recognition in DVA results from deficient visual integration across diagnostic face components. Copyright © 2012 Elsevier Ltd. All rights reserved.

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).
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.
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso

2015-01-01

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457
Emotion-independent face recognition

NASA Astrophysics Data System (ADS)

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

2000-12-01

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

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved
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.
A general framework for face reconstruction using single still image based on 2D-to-3D transformation kernel.

PubMed

Fooprateepsiri, Rerkchai; Kurutach, Werasak

2014-03-01

Face authentication is a biometric classification method that verifies the identity of a user based on image of their face. Accuracy of the authentication is reduced when the pose, illumination and expression of the training face images are different than the testing image. The methods in this paper are designed to improve the accuracy of a features-based face recognition system when the pose between the input images and training images are different. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination. Second, realistic virtual faces with different poses are synthesized based on the personalized 3D face to characterize the face subspace. Finally, face recognition is conducted based on these representative virtual faces. Compared with other related works, this framework has the following advantages: (1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; and (2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex pose, illumination and expression. From the experimental results, we conclude that the proposed method improves the accuracy of face recognition by varying the pose, illumination and expression. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Different underlying mechanisms for face emotion and gender processing during feature-selective attention: Evidence from event-related potential studies.

PubMed

Wang, Hailing; Ip, Chengteng; Fu, Shimin; Sun, Pei

2017-05-01

Face recognition theories suggest that our brains process invariant (e.g., gender) and changeable (e.g., emotion) facial dimensions separately. To investigate whether these two dimensions are processed in different time courses, we analyzed the selection negativity (SN, an event-related potential component reflecting attentional modulation) elicited by face gender and emotion during a feature selective attention task. Participants were instructed to attend to a combination of face emotion and gender attributes in Experiment 1 (bi-dimensional task) and to either face emotion or gender in Experiment 2 (uni-dimensional task). The results revealed that face emotion did not elicit a substantial SN, whereas face gender consistently generated a substantial SN in both experiments. These results suggest that face gender is more sensitive to feature-selective attention and that face emotion is encoded relatively automatically on SN, implying the existence of different underlying processing mechanisms for invariant and changeable facial dimensions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Emotional face processing deficit in schizophrenia: A replication study in a South African Xhosa population.

PubMed

Leppänen, J M; Niehaus, D J H; Koen, L; Du Toit, E; Schoeman, R; Emsley, R

2006-06-01

Schizophrenia is associated with a deficit in the recognition of negative emotions from facial expressions. The present study examined the universality of this finding by studying facial expression recognition in African Xhosa population. Forty-four Xhosa patients with schizophrenia and forty healthy controls were tested with a computerized task requiring rapid perceptual discrimination of matched positive (i.e. happy), negative (i.e. angry), and neutral faces. Patients were equally accurate as controls in recognizing happy faces but showed a marked impairment in recognition of angry faces. The impairment was particularly pronounced for high-intensity (open-mouth) angry faces. Patients also exhibited more false happy and angry responses to neutral faces than controls. No correlation between level of education or illness duration and emotion recognition was found but the deficit in the recognition of negative emotions was more pronounced in familial compared to non-familial cases of schizophrenia. These findings suggest that the deficit in the recognition of negative facial expressions may constitute a universal neurocognitive marker of schizophrenia.
Recognition of Immaturity and Emotional Expressions in Blended Faces by Children with Autism and Other Developmental Disabilities

ERIC Educational Resources Information Center

Gross, Thomas F.

2008-01-01

The recognition of facial immaturity and emotional expression by children with autism, language disorders, mental retardation, and non-disabled controls was studied in two experiments. Children identified immaturity and expression in upright and inverted faces. The autism group identified fewer immature faces and expressions than control (Exp. 1 &…
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.
Support vector machine for automatic pain recognition

NASA Astrophysics Data System (ADS)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.
Learning Rotation-Invariant Local Binary Descriptor.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.
The within-subjects design in the study of facial expressions.

PubMed

Yik, Michelle; Widen, Sherri C; Russell, James A

2013-01-01

The common within-subjects design of studies on the recognition of emotion from facial expressions allows the judgement of one face to be influenced by previous faces, thus introducing the potential for artefacts. The present study (N=344) showed that the canonical "disgust face" was judged as disgusted, provided that the preceding set of faces included "anger expressions", but was judged as angry when the preceding set of faces excluded anger but instead included persons who looked sad or about to be sick. Chinese observers showed lower recognition of the "disgust face" than did American observers. Chinese observers also showed lower recognition of the "fear face" when responding in Chinese than in English.
Automatic integration of social information in emotion recognition.

PubMed

Mumenthaler, Christian; Sander, David

2015-04-01

This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. (c) 2015 APA, all rights reserved).
Eye-movement assessment of the time course in facial expression recognition: Neurophysiological implications.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2009-12-01

Happy, surprised, disgusted, angry, sad, fearful, and neutral faces were presented extrafoveally, with fixations on faces allowed or not. The faces were preceded by a cue word that designated the face to be saccaded in a two-alternative forced-choice discrimination task (2AFC; Experiments 1 and 2), or were followed by a probe word for recognition (Experiment 3). Eye tracking was used to decompose the recognition process into stages. Relative to the other expressions, happy faces (1) were identified faster (as early as 160 msec from stimulus onset) in extrafoveal vision, as revealed by shorter saccade latencies in the 2AFC task; (2) required less encoding effort, as indexed by shorter first fixations and dwell times; and (3) required less decision-making effort, as indicated by fewer refixations on the face after the recognition probe was presented. This reveals a happy-face identification advantage both prior to and during overt attentional processing. The results are discussed in relation to prior neurophysiological findings on latencies in facial expression recognition.
Orientation and Affective Expression Effects on Face Recognition in Williams Syndrome and Autism

ERIC Educational Resources Information Center

Rose, Fredric E.; Lincoln, Alan J.; Lai, Zona; Ene, Michaela; Searcy, Yvonne M.; Bellugi, Ursula

2007-01-01

We sought to clarify the nature of the face processing strength commonly observed in individuals with Williams syndrome (WS) by comparing the face recognition ability of persons with WS to that of persons with autism and to healthy controls under three conditions: Upright faces with neutral expressions, upright faces with varying affective…
A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.
Constrained Metric Learning by Permutation Inducing Isometries.

PubMed

Bosveld, Joel; Mahmood, Arif; Huynh, Du Q; Noakes, Lyle

2016-01-01

The choice of metric critically affects the performance of classification and clustering algorithms. Metric learning algorithms attempt to improve performance, by learning a more appropriate metric. Unfortunately, most of the current algorithms learn a distance function which is not invariant to rigid transformations of images. Therefore, the distances between two images and their rigidly transformed pair may differ, leading to inconsistent classification or clustering results. We propose to constrain the learned metric to be invariant to the geometry preserving transformations of images that induce permutations in the feature space. The constraint that these transformations are isometries of the metric ensures consistent results and improves accuracy. Our second contribution is a dimension reduction technique that is consistent with the isometry constraints. Our third contribution is the formulation of the isometry constrained logistic discriminant metric learning (IC-LDML) algorithm, by incorporating the isometry constraints within the objective function of the LDML algorithm. The proposed algorithm is compared with the existing techniques on the publicly available labeled faces in the wild, viewpoint-invariant pedestrian recognition, and Toy Cars data sets. The IC-LDML algorithm has outperformed existing techniques for the tasks of face recognition, person identification, and object classification by a significant margin.
Mismatched expressions decrease face recognition and corresponding ERP old/new effects in schizophrenia.

PubMed

Guillaume, Fabrice; Guillem, François; Tiberghien, Guy; Stip, Emmanuel

2012-09-01

The objective was to investigate the electrophysiological (ERP) correlates of mismatched expression on face recognition in schizophrenia. Expression-change effects and associated ERPs were explored in patients with schizophrenia (n = 20) and paired comparison participants (n = 20) on a long-term face-recognition task. A facial-expression change decreased discriminability for patients with schizophrenia than for healthy participants. The patients' recognition deficit was accompanied by the absence of the midfrontal FN400 and late parietal ERP old/new effects in the mismatched-expression condition. By contrast, preserved midfrontal FN400 and late parietal ERP old/new effects were found in both groups in the unchanged-expression condition. Thus, the preserved parietal old/new effect previously observed in schizophrenia was no longer found here in the situation in which expression changes took place between the study and recognition phases. These findings suggest that, when they are not supposed to take the change of expression into account, the recognition deficit observed here in patients with schizophrenia resulted from an impairment in the mechanisms underlying the emergence, assessment, or utilization of familiarity--as indexed by the ERP old/new effects. In these natural conditions, the impact of the expression change on the implementation of retrieval processes offers new insight into schizophrenia-linked deficits in face recognition, with substantial phenomenological differences with respect to the emergence of familiarity.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713
Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion.

PubMed

Guo, Kun; Soornack, Yoshi; Settle, Rebecca

2018-03-05

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. Copyright © 2018 Elsevier Ltd. All rights reserved.
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.
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.
Not on the Face Alone: Perception of Contextualized Face Expressions in Huntington's Disease

ERIC Educational Resources Information Center

Aviezer, Hillel; Bentin, Shlomo; Hassin, Ran R.; Meschino, Wendy S.; Kennedy, Jeanne; Grewal, Sonya; Esmail, Sherali; Cohen, Sharon; Moscovitch, Morris

2009-01-01

Numerous studies have demonstrated that Huntington's disease mutation-carriers have deficient explicit recognition of isolated facial expressions. There are no studies, however, which have investigated the recognition of facial expressions embedded within an emotional body and scene context. Real life facial expressions are typically embedded in…
[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.
Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544
Recognition profile of emotions in natural and virtual faces.

PubMed

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Ruben C; Gur, Rurben C; Mathiak, Klaus

2008-01-01

Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.
Recognition Profile of Emotions in Natural and Virtual Faces

PubMed Central

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Rurben C.; Mathiak, Klaus

2008-01-01

Background Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Methodology/Principal Findings Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Conclusions/Significance Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications. PMID:18985152
Quest Hierarchy for Hyperspectral Face Recognition

DTIC Science & Technology

2011-03-01

numerous face recognition algorithms available, several very good literature surveys are available that include Abate [29], Samal [110], Kong [18], Zou...Perception, Japan (January 1994). [110] Samal , Ashok and P. Iyengar, Automatic Recognition and Analysis of Human Faces and Facial Expressions: A Survey
Dynamic Encoding of Face Information in the Human Fusiform Gyrus

PubMed Central

Ghuman, Avniel Singh; Brunet, Nicolas M.; Li, Yuanning; Konecky, Roma O.; Pyles, John A.; Walls, Shawn A.; Destefino, Vincent; Wang, Wei; Richardson, R. Mark

2014-01-01

Humans’ ability to rapidly and accurately detect, identify, and classify faces under variable conditions derives from a network of brain regions highly tuned to face information. The fusiform face area (FFA) is thought to be a computational hub for face processing, however temporal dynamics of face information processing in FFA remains unclear. Here we use multivariate pattern classification to decode the temporal dynamics of expression-invariant face information processing using electrodes placed directly upon FFA in humans. Early FFA activity (50-75 ms) contained information regarding whether participants were viewing a face. Activity between 200-500 ms contained expression-invariant information about which of 70 faces participants were viewing along with the individual differences in facial features and their configurations. Long-lasting (500+ ms) broadband gamma frequency activity predicted task performance. These results elucidate the dynamic computational role FFA plays in multiple face processing stages and indicate what information is used in performing these visual analyses. PMID:25482825
Dynamic encoding of face information in the human fusiform gyrus.

PubMed

Ghuman, Avniel Singh; Brunet, Nicolas M; Li, Yuanning; Konecky, Roma O; Pyles, John A; Walls, Shawn A; Destefino, Vincent; Wang, Wei; Richardson, R Mark

2014-12-08

Humans' ability to rapidly and accurately detect, identify and classify faces under variable conditions derives from a network of brain regions highly tuned to face information. The fusiform face area (FFA) is thought to be a computational hub for face processing; however, temporal dynamics of face information processing in FFA remains unclear. Here we use multivariate pattern classification to decode the temporal dynamics of expression-invariant face information processing using electrodes placed directly on FFA in humans. Early FFA activity (50-75 ms) contained information regarding whether participants were viewing a face. Activity between 200 and 500 ms contained expression-invariant information about which of 70 faces participants were viewing along with the individual differences in facial features and their configurations. Long-lasting (500+ms) broadband gamma frequency activity predicted task performance. These results elucidate the dynamic computational role FFA plays in multiple face processing stages and indicate what information is used in performing these visual analyses.
Impaired recognition of body expressions in the behavioral variant of frontotemporal dementia.

PubMed

Van den Stock, Jan; De Winter, François-Laurent; de Gelder, Beatrice; Rangarajan, Janaki Raman; Cypers, Gert; Maes, Frederik; Sunaert, Stefan; Goffin, Karolien; Vandenberghe, Rik; Vandenbulcke, Mathieu

2015-08-01

Progressive deterioration of social cognition and emotion processing are core symptoms of the behavioral variant of frontotemporal dementia (bvFTD). Here we investigate whether bvFTD is also associated with impaired recognition of static (Experiment 1) and dynamic (Experiment 2) bodily expressions. In addition, we compared body expression processing with processing of static (Experiment 3) and dynamic (Experiment 4) facial expressions, as well as with face identity processing (Experiment 5). The results reveal that bvFTD is associated with impaired recognition of static and dynamic bodily and facial expressions, while identity processing was intact. No differential impairments were observed regarding motion (static vs. dynamic) or category (body vs. face). Within the bvFTD group, we observed a significant partial correlation between body and face expression recognition, when controlling for performance on the identity task. Voxel-Based Morphometry (VBM) analysis revealed that body emotion recognition was positively associated with gray matter volume in a region of the inferior frontal gyrus (pars orbitalis/triangularis). The results are in line with a supramodal emotion recognition deficit in bvFTD. Copyright © 2015 Elsevier Ltd. All rights reserved.
The representation of information about faces in the temporal and frontal lobes.

PubMed

Rolls, Edmund T

2007-01-07

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

PubMed

Rybak, I A; Gusakova, V I; Golovan, A V; Podladchikova, L N; Shevtsova, N A

1998-08-01

A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.
Pubface: Celebrity face identification based on deep learning

NASA Astrophysics Data System (ADS)

Ouanan, H.; Ouanan, M.; Aksasse, B.

2018-05-01

In this paper, we describe a new real time application called PubFace, which allows to recognize celebrities in public spaces by employs a new pose invariant face recognition deep neural network algorithm with an extremely low error rate. To build this application, we make the following contributions: firstly, we build a novel dataset with over five million faces labelled. Secondly, we fine tuning the deep convolutional neural network (CNN) VGG-16 architecture on our new dataset that we have built. Finally, we deploy this model on the Raspberry Pi 3 model B using the OpenCv dnn module (OpenCV 3.3).
Social categories shape the neural representation of emotion: evidence from a visual face adaptation task

PubMed Central

Otten, Marte; Banaji, Mahzarin R.

2012-01-01

A number of recent behavioral studies have shown that emotional expressions are differently perceived depending on the race of a face, and that perception of race cues is influenced by emotional expressions. However, neural processes related to the perception of invariant cues that indicate the identity of a face (such as race) are often described to proceed independently of processes related to the perception of cues that can vary over time (such as emotion). Using a visual face adaptation paradigm, we tested whether these behavioral interactions between emotion and race also reflect interdependent neural representation of emotion and race. We compared visual emotion aftereffects when the adapting face and ambiguous test face differed in race or not. Emotion aftereffects were much smaller in different race (DR) trials than same race (SR) trials, indicating that the neural representation of a facial expression is significantly different depending on whether the emotional face is black or white. It thus seems that invariable cues such as race interact with variable face cues such as emotion not just at a response level, but also at the level of perception and neural representation. PMID:22403531
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.
Seeing Life through Positive-Tinted Glasses: Color–Meaning Associations

PubMed Central

Gil, Sandrine; Le Bigot, Ludovic

2014-01-01

There is a growing body of literature to show that color can convey information, owing to its emotionally meaningful associations. Most research so far has focused on negative hue–meaning associations (e.g., red) with the exception of the positive aspects associated with green. We therefore set out to investigate the positive associations of two colors (i.e., green and pink), using an emotional facial expression recognition task in which colors provided the emotional contextual information for the face processing. In two experiments, green and pink backgrounds enhanced happy face recognition and impaired sad face recognition, compared with a control color (gray). Our findings therefore suggest that because green and pink both convey positive information, they facilitate the processing of emotionally congruent facial expressions (i.e., faces expressing happiness) and interfere with that of incongruent facial expressions (i.e., faces expressing sadness). Data also revealed a positive association for white. Results are discussed within the theoretical framework of emotional cue processing and color meaning. PMID:25098167

Seeing life through positive-tinted glasses: color-meaning associations.

PubMed

Gil, Sandrine; Le Bigot, Ludovic

2014-01-01

There is a growing body of literature to show that color can convey information, owing to its emotionally meaningful associations. Most research so far has focused on negative hue-meaning associations (e.g., red) with the exception of the positive aspects associated with green. We therefore set out to investigate the positive associations of two colors (i.e., green and pink), using an emotional facial expression recognition task in which colors provided the emotional contextual information for the face processing. In two experiments, green and pink backgrounds enhanced happy face recognition and impaired sad face recognition, compared with a control color (gray). Our findings therefore suggest that because green and pink both convey positive information, they facilitate the processing of emotionally congruent facial expressions (i.e., faces expressing happiness) and interfere with that of incongruent facial expressions (i.e., faces expressing sadness). Data also revealed a positive association for white. Results are discussed within the theoretical framework of emotional cue processing and color meaning.
Face memory and face recognition in children and adolescents with attention deficit hyperactivity disorder: A systematic review.

PubMed

Romani, Maria; Vigliante, Miriam; Faedda, Noemi; Rossetti, Serena; Pezzuti, Lina; Guidetti, Vincenzo; Cardona, Francesco

2018-06-01

This review focuses on facial recognition abilities in children and adolescents with attention deficit hyperactivity disorder (ADHD). A systematic review, using PRISMA guidelines, was conducted to identify original articles published prior to May 2017 pertaining to memory, face recognition, affect recognition, facial expression recognition and recall of faces in children and adolescents with ADHD. The qualitative synthesis based on different studies shows a particular focus of the research on facial affect recognition without paying similar attention to the structural encoding of facial recognition. In this review, we further investigate facial recognition abilities in children and adolescents with ADHD, providing synthesis of the results observed in the literature, while detecting face recognition tasks used on face processing abilities in ADHD and identifying aspects not yet explored. Copyright © 2018 Elsevier Ltd. All rights reserved.
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.
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
Locally linear regression for pose-invariant face recognition.

PubMed

Chai, Xiujuan; Shan, Shiguang; Chen, Xilin; Gao, Wen

2007-07-01

The variation of facial appearance due to the viewpoint (/pose) degrades face recognition systems considerably, which is one of the bottlenecks in face recognition. One of the possible solutions is generating virtual frontal view from any given nonfrontal view to obtain a virtual gallery/probe face. Following this idea, this paper proposes a simple, but efficient, novel locally linear regression (LLR) method, which generates the virtual frontal view from a given nonfrontal face image. We first justify the basic assumption of the paper that there exists an approximate linear mapping between a nonfrontal face image and its frontal counterpart. Then, by formulating the estimation of the linear mapping as a prediction problem, we present the regression-based solution, i.e., globally linear regression. To improve the prediction accuracy in the case of coarse alignment, LLR is further proposed. In LLR, we first perform dense sampling in the nonfrontal face image to obtain many overlapped local patches. Then, the linear regression technique is applied to each small patch for the prediction of its virtual frontal patch. Through the combination of all these patches, the virtual frontal view is generated. The experimental results on the CMU PIE database show distinct advantage of the proposed method over Eigen light-field method.
Efficient visual information for unfamiliar face matching despite viewpoint variations: It's not in the eyes!

PubMed

Royer, Jessica; Blais, Caroline; Barnabé-Lortie, Vincent; Carré, Mélissa; Leclerc, Josiane; Fiset, Daniel

2016-06-01

Faces are encountered in highly diverse angles in real-world settings. Despite this considerable diversity, most individuals are able to easily recognize familiar faces. The vast majority of studies in the field of face recognition have nonetheless focused almost exclusively on frontal views of faces. Indeed, a number of authors have investigated the diagnostic facial features for the recognition of frontal views of faces previously encoded in this same view. However, the nature of the information useful for identity matching when the encoded face and test face differ in viewing angle remains mostly unexplored. The present study addresses this issue using individual differences and bubbles, a method that pinpoints the facial features effectively used in a visual categorization task. Our results indicate that the use of features located in the center of the face, the lower left portion of the nose area and the center of the mouth, are significantly associated with individual efficiency to generalize a face's identity across different viewpoints. However, as faces become more familiar, the reliance on this area decreases, while the diagnosticity of the eye region increases. This suggests that a certain distinction can be made between the visual mechanisms subtending viewpoint invariance and face recognition in the case of unfamiliar face identification. Our results further support the idea that the eye area may only come into play when the face stimulus is particularly familiar to the observer. Copyright © 2016 Elsevier Ltd. All rights reserved.
Exposure to the self-face facilitates identification of dynamic facial expressions: influences on individual differences.

PubMed

Li, Yuan Hang; Tottenham, Nim

2013-04-01

A growing literature suggests that the self-face is involved in processing the facial expressions of others. The authors experimentally activated self-face representations to assess its effects on the recognition of dynamically emerging facial expressions of others. They exposed participants to videos of either their own faces (self-face prime) or faces of others (nonself-face prime) prior to a facial expression judgment task. Their results show that experimentally activating self-face representations results in earlier recognition of dynamically emerging facial expression. As a group, participants in the self-face prime condition recognized expressions earlier (when less affective perceptual information was available) compared to participants in the nonself-face prime condition. There were individual differences in performance, such that poorer expression identification was associated with higher autism traits (in this neurocognitively healthy sample). However, when randomized into the self-face prime condition, participants with high autism traits performed as well as those with low autism traits. Taken together, these data suggest that the ability to recognize facial expressions in others is linked with the internal representations of our own faces. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach

PubMed Central

Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

2015-01-01

The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT) along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA). PMID:26368566
Positive, but Not Negative, Facial Expressions Facilitate 3-Month-Olds' Recognition of an Individual Face

ERIC Educational Resources Information Center

Brenna, Viola; Proietti, Valentina; Montirosso, Rosario; Turati, Chiara

2013-01-01

The current study examined whether and how the presence of a positive or a negative emotional expression may affect the face recognition process at 3 months of age. Using a familiarization procedure, Experiment 1 demonstrated that positive (i.e., happiness), but not negative (i.e., fear and anger) facial expressions facilitate infants' ability to…
Behavioral model of visual perception and recognition

NASA Astrophysics Data System (ADS)

Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

1993-09-01

In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and successive verification of the expected sets of features (stored in Sensory Memory). The model shows the ability of recognition of complex objects (such as faces) in gray-level images invariant with respect to shift, rotation, and scale.
[Face recognition in patients with schizophrenia].

PubMed

Doi, Hirokazu; Shinohara, Kazuyuki

2012-07-01

It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.
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.
Neurocomputational bases of object and face recognition.

PubMed Central

Biederman, I; Kalocsai, P

1997-01-01

A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in a two-dimensional (2D) coordinate space, as proposed by C. von der Malsburg and his associates, may account for many of the phenomena associated with face recognition. An additional refinement, in which each column of filters (termed a 'jet') is centred on a particular facial feature (or fiducial point), allows selectivity of the input into the holistic representation to avoid incorporation of occluding or nearby surfaces. The initial hypercolumn representation also characterizes the first stage of object perception, but the image variation for objects at a given location in a 2D coordinate space may be too great to yield sufficient predictability directly from the output of spatial kernels. Consequently, objects can be represented by a structural description specifying qualitative (typically, non-accidental) characterizations of an object's parts, the attributes of the parts, and the relations among the parts, largely based on orientation and depth discontinuities (as shown by Hummel & Biederman). A series of experiments on the name priming or physical matching of complementary images (in the Fourier domain) of objects and faces documents that whereas face recognition is strongly dependent on the original spatial filter values, evidence from object recognition indicates strong invariance to these values, even when distinguishing among objects that are as similar as faces. PMID:9304687
Cognitive mechanisms of false facial recognition in older adults.

PubMed

Edmonds, Emily C; Glisky, Elizabeth L; Bartlett, James C; Rapcsak, Steven Z

2012-03-01

Older adults show elevated false alarm rates on recognition memory tests involving faces in comparison to younger adults. It has been proposed that this age-related increase in false facial recognition reflects a deficit in recollection and a corresponding increase in the use of familiarity when making memory decisions. To test this hypothesis, we examined the performance of 40 older adults and 40 younger adults on a face recognition memory paradigm involving three different types of lures with varying levels of familiarity. A robust age effect was found, with older adults demonstrating a markedly heightened false alarm rate in comparison to younger adults for "familiarized lures" that were exact repetitions of faces encountered earlier in the experiment, but outside the study list, and therefore required accurate recollection of contextual information to reject. By contrast, there were no age differences in false alarms to "conjunction lures" that recombined parts of study list faces, or to entirely new faces. Overall, the pattern of false recognition errors observed in older adults was consistent with excessive reliance on a familiarity-based response strategy. Specifically, in the absence of recollection older adults appeared to base their memory decisions on item familiarity, as evidenced by a linear increase in false alarm rates with increasing familiarity of the lures. These findings support the notion that automatic memory processes such as familiarity remain invariant with age, while more controlled memory processes such as recollection show age-related decline.
Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems.

PubMed

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-07-23

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other.
Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems

PubMed Central

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-01-01

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other. PMID:26213932
Mapping the impairment in decoding static facial expressions of emotion in prosopagnosia.

PubMed

Fiset, Daniel; Blais, Caroline; Royer, Jessica; Richoz, Anne-Raphaëlle; Dugas, Gabrielle; Caldara, Roberto

2017-08-01

Acquired prosopagnosia is characterized by a deficit in face recognition due to diverse brain lesions, but interestingly most prosopagnosic patients suffering from posterior lesions use the mouth instead of the eyes for face identification. Whether this bias is present for the recognition of facial expressions of emotion has not yet been addressed. We tested PS, a pure case of acquired prosopagnosia with bilateral occipitotemporal lesions anatomically sparing the regions dedicated for facial expression recognition. PS used mostly the mouth to recognize facial expressions even when the eye area was the most diagnostic. Moreover, PS directed most of her fixations towards the mouth. Her impairment was still largely present when she was instructed to look at the eyes, or when she was forced to look at them. Control participants showed a performance comparable to PS when only the lower part of the face was available. These observations suggest that the deficits observed in PS with static images are not solely attentional, but are rooted at the level of facial information use. This study corroborates neuroimaging findings suggesting that the Occipital Face Area might play a critical role in extracting facial features that are integrated for both face identification and facial expression recognition in static images. © The Author (2017). Published by Oxford University Press.
No differences in emotion recognition strategies in children with autism spectrum disorder: evidence from hybrid faces.

PubMed

Evers, Kris; Kerkhof, Inneke; Steyaert, Jean; Noens, Ilse; Wagemans, Johan

2014-01-01

Emotion recognition problems are frequently reported in individuals with an autism spectrum disorder (ASD). However, this research area is characterized by inconsistent findings, with atypical emotion processing strategies possibly contributing to existing contradictions. In addition, an attenuated saliency of the eyes region is often demonstrated in ASD during face identity processing. We wanted to compare reliance on mouth versus eyes information in children with and without ASD, using hybrid facial expressions. A group of six-to-eight-year-old boys with ASD and an age- and intelligence-matched typically developing (TD) group without intellectual disability performed an emotion labelling task with hybrid facial expressions. Five static expressions were used: one neutral expression and four emotional expressions, namely, anger, fear, happiness, and sadness. Hybrid faces were created, consisting of an emotional face half (upper or lower face region) with the other face half showing a neutral expression. Results showed no emotion recognition problem in ASD. Moreover, we provided evidence for the existence of top- and bottom-emotions in children: correct identification of expressions mainly depends on information in the eyes (so-called top-emotions: happiness) or in the mouth region (so-called bottom-emotions: sadness, anger, and fear). No stronger reliance on mouth information was found in children with ASD.

Reassessing the 3/4 view effect in face recognition.

PubMed

Liu, Chang Hong; Chaudhuri, Avi

2002-02-01

It is generally accepted that unfamiliar faces are better recognized if presented in 3/4 view. A common interpretation of this result is that the 3/4 view represents a canonical view for faces. This article presents a critical review of this claim. Two kinds of advantage, in which a 3/4 view either generalizes better to a different view or produces better recognition in the same view, are discussed. Our analysis of the literature shows that the first effect almost invariably depended on different amounts of angular rotation that was present between learning and test views. The advantage usually vanished when angular rotation was equalized between conditions. Reports in favor of the second effect are scant and can be countered by studies reporting negative findings. To clarify this ambiguity, we conducted a recognition experiment. Subjects were trained and tested on the same three views (full-face, 3/4 and profile). The results showed no difference between the three view conditions. Our analysis of the literature, along with the new results, shows that the evidence for a 3/4 view advantage in both categories is weak at best. We suggest that a better predictor of performance for recognition in different views is the angular difference between learning and test views. For recognition in the same view, there may be a wide range of views whose effectiveness is comparable to the 3/4 view.
Face Processing: Models For Recognition

NASA Astrophysics Data System (ADS)

Turk, Matthew A.; Pentland, Alexander P.

1990-03-01

The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.
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.
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.
Emotion Recognition in Faces and the Use of Visual Context in Young People with High-Functioning Autism Spectrum Disorders

ERIC Educational Resources Information Center

Wright, Barry; Clarke, Natalie; Jordan, Jo; Young, Andrew W.; Clarke, Paula; Miles, Jeremy; Nation, Kate; Clarke, Leesa; Williams, Christine

2008-01-01

We compared young people with high-functioning autism spectrum disorders (ASDs) with age, sex and IQ matched controls on emotion recognition of faces and pictorial context. Each participant completed two tests of emotion recognition. The first used Ekman series faces. The second used facial expressions in visual context. A control task involved…
Superior Recognition Performance for Happy Masked and Unmasked Faces in Both Younger and Older Adults

PubMed Central

Svärd, Joakim; Wiens, Stefan; Fischer, Håkan

2012-01-01

In the aging literature it has been shown that even though emotion recognition performance decreases with age, the decrease is less for happiness than other facial expressions. Studies in younger adults have also revealed that happy faces are more strongly attended to and better recognized than other emotional facial expressions. Thus, there might be a more age independent happy face advantage in facial expression recognition. By using a backward masking paradigm and varying stimulus onset asynchronies (17–267 ms) the temporal development of a happy face advantage, on a continuum from low to high levels of visibility, was examined in younger and older adults. Results showed that across age groups, recognition performance for happy faces was better than for neutral and fearful faces at durations longer than 50 ms. Importantly, the results showed a happy face advantage already during early processing of emotional faces in both younger and older adults. This advantage is discussed in terms of processing of salient perceptual features and elaborative processing of the happy face. We also investigate the combined effect of age and neuroticism on emotional face processing. The rationale was previous findings of age-related differences in physiological arousal to emotional pictures and a relation between arousal and neuroticism. Across all durations, there was an interaction between age and neuroticism, showing that being high in neuroticism might be disadvantageous for younger, but not older adults’ emotion recognition performance during arousal enhancing tasks. These results indicate that there is a relation between aging, neuroticism, and performance, potentially related to physiological arousal. PMID:23226135
A rodent model for the study of invariant visual object recognition

PubMed Central

Zoccolan, Davide; Oertelt, Nadja; DiCarlo, James J.; Cox, David D.

2009-01-01

The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability—known as “invariant” object recognition—is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing. PMID:19429704
Adaptation to Antifaces and the Perception of Correct Famous Identity in an Average Face

PubMed Central

Little, Anthony C.; Hancock, Peter J. B.; DeBruine, Lisa M.; Jones, Benedict C.

2011-01-01

Previous experiments have examined exposure to anti-identities (faces that possess traits opposite to an identity through a population average), finding that exposure to antifaces enhances recognition of the plus-identity images. Here we examine adaptation to antifaces using famous female celebrities. We demonstrate: that exposure to a color and shape transformed antiface of a celebrity increases the likelihood of perceiving the identity from which the antiface was manufactured in a composite face and that the effect shows size invariance (experiment 1), equivalent effects are seen in internet and laboratory-based studies (experiment 2), adaptation to shape-only antifaces has stronger effects on identity recognition than adaptation to color-only antifaces (experiment 3), and exposure to male versions of the antifaces does not influence the perception of female faces (experiment 4). Across these studies we found an effect of order where aftereffects were more pronounced in early than later trials. Overall, our studies delineate several aspects of identity aftereffects and support the proposal that identity is coded relative to other faces with special reference to a relatively sex-specific mean face representation. PMID:22363301
Mapping the emotional face. How individual face parts contribute to successful emotion recognition.

PubMed

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation.
Mapping the emotional face. How individual face parts contribute to successful emotion recognition

PubMed Central

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation. PMID:28493921
Robust kernel collaborative representation for face recognition

NASA Astrophysics Data System (ADS)

Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

2015-05-01

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.
The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.
Face processing in different brain areas, and critical band masking.

PubMed

Rolls, Edmund T

2008-09-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size, view, and spatial frequency of faces and objects, and that these neurons show rapid processing and rapid learning. Critical band spatial frequency masking is shown to be a property of these face-selective neurons and of the human visual perception of faces. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximizing the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalization, and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses generalize to other views of the same face. A theory is described of how such invariant representations may be produced by self-organizing learning in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory utilizes either temporal or spatial continuity with an associative synaptic modification rule. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye-gaze, face view, and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the human orbitofrontal and pregenual cingulate cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.
Designing a composite correlation filter based on iterative optimization of training images for distortion invariant face recognition

NASA Astrophysics Data System (ADS)

Wang, Q.; Elbouz, M.; Alfalou, A.; Brosseau, C.

2017-06-01

We present a novel method to optimize the discrimination ability and noise robustness of composite filters. This method is based on the iterative preprocessing of training images which can extract boundary and detailed feature information of authentic training faces, thereby improving the peak-to-correlation energy (PCE) ratio of authentic faces and to be immune to intra-class variance and noise interference. By adding the training images directly, one can obtain a composite template with high discrimination ability and robustness for face recognition task. The proposed composite correlation filter does not involve any complicated mathematical analysis and computation which are often required in the design of correlation algorithms. Simulation tests have been conducted to check the effectiveness and feasibility of our proposal. Moreover, to assess robustness of composite filters using receiver operating characteristic (ROC) curves, we devise a new method to count the true positive and false positive rates for which the difference between PCE and threshold is involved.
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.
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.
Facelock: familiarity-based graphical authentication.

PubMed

Jenkins, Rob; McLachlan, Jane L; Renaud, Karen

2014-01-01

Authentication codes such as passwords and PIN numbers are widely used to control access to resources. One major drawback of these codes is that they are difficult to remember. Account holders are often faced with a choice between forgetting a code, which can be inconvenient, or writing it down, which compromises security. In two studies, we test a new knowledge-based authentication method that does not impose memory load on the user. Psychological research on face recognition has revealed an important distinction between familiar and unfamiliar face perception: When a face is familiar to the observer, it can be identified across a wide range of images. However, when the face is unfamiliar, generalisation across images is poor. This contrast can be used as the basis for a personalised 'facelock', in which authentication succeeds or fails based on image-invariant recognition of faces that are familiar to the account holder. In Study 1, account holders authenticated easily by detecting familiar targets among other faces (97.5% success rate), even after a one-year delay (86.1% success rate). Zero-acquaintance attackers were reduced to guessing (<1% success rate). Even personal attackers who knew the account holder well were rarely able to authenticate (6.6% success rate). In Study 2, we found that shoulder-surfing attacks by strangers could be defeated by presenting different photos of the same target faces in observed and attacked grids (1.9% success rate). Our findings suggest that the contrast between familiar and unfamiliar face recognition may be useful for developers of graphical authentication systems.
Individual differences in the ability to recognise facial identity are associated with social anxiety.

PubMed

Davis, Joshua M; McKone, Elinor; Dennett, Hugh; O'Connor, Kirsty B; O'Kearney, Richard; Palermo, Romina

2011-01-01

Previous research has been concerned with the relationship between social anxiety and the recognition of face expression but the question of whether there is a relationship between social anxiety and the recognition of face identity has been neglected. Here, we report the first evidence that social anxiety is associated with recognition of face identity, across the population range of individual differences in recognition abilities. Results showed poorer face identity recognition (on the Cambridge Face Memory Test) was correlated with a small but significant increase in social anxiety (Social Interaction Anxiety Scale) but not general anxiety (State-Trait Anxiety Inventory). The correlation was also independent of general visual memory (Cambridge Car Memory Test) and IQ. Theoretically, the correlation could arise because correct identification of people, typically achieved via faces, is important for successful social interactions, extending evidence that individuals with clinical-level deficits in face identity recognition (prosopagnosia) often report social stress due to their inability to recognise others. Equally, the relationship could arise if social anxiety causes reduced exposure or attention to people's faces, and thus to poor development of face recognition mechanisms.
Individual Differences in the Ability to Recognise Facial Identity Are Associated with Social Anxiety

PubMed Central

Davis, Joshua M.; McKone, Elinor; Dennett, Hugh; O'Connor, Kirsty B.; O'Kearney, Richard; Palermo, Romina

2011-01-01

Previous research has been concerned with the relationship between social anxiety and the recognition of face expression but the question of whether there is a relationship between social anxiety and the recognition of face identity has been neglected. Here, we report the first evidence that social anxiety is associated with recognition of face identity, across the population range of individual differences in recognition abilities. Results showed poorer face identity recognition (on the Cambridge Face Memory Test) was correlated with a small but significant increase in social anxiety (Social Interaction Anxiety Scale) but not general anxiety (State-Trait Anxiety Inventory). The correlation was also independent of general visual memory (Cambridge Car Memory Test) and IQ. Theoretically, the correlation could arise because correct identification of people, typically achieved via faces, is important for successful social interactions, extending evidence that individuals with clinical-level deficits in face identity recognition (prosopagnosia) often report social stress due to their inability to recognise others. Equally, the relationship could arise if social anxiety causes reduced exposure or attention to people's faces, and thus to poor development of face recognition mechanisms. PMID:22194916
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.

Decoding Face Information in Time, Frequency and Space from Direct Intracranial Recordings of the Human Brain

PubMed Central

Oya, Hiroyuki; Howard, Matthew A.; Adolphs, Ralph

2008-01-01

Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity) in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion) in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG) from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60–150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus. PMID:19065268
Sad people are more accurate at expression identification with a smaller own-ethnicity bias than happy people.

PubMed

Hills, Peter J; Hill, Dominic M

2017-07-12

Sad individuals perform more accurately at face identity recognition (Hills, Werno, & Lewis, 2011), possibly because they scan more of the face during encoding. During expression identification tasks, sad individuals do not fixate on the eyes as much as happier individuals (Wu, Pu, Allen, & Pauli, 2012). Fixating on features other than the eyes leads to a reduced own-ethnicity bias (Hills & Lewis, 2006). This background indicates that sad individuals would not view the eyes as much as happy individuals and this would result in improved expression recognition and a reduced own-ethnicity bias. This prediction was tested using an expression identification task, with eye tracking. We demonstrate that sad-induced participants show enhanced expression recognition and a reduced own-ethnicity bias than happy-induced participants due to scanning more facial features. We conclude that mood affects eye movements and face encoding by causing a wider sampling strategy and deeper encoding of facial features diagnostic for expression identification.
Oxytocin Reduces Face Processing Time but Leaves Recognition Accuracy and Eye-Gaze Unaffected.

PubMed

Hubble, Kelly; Daughters, Katie; Manstead, Antony S R; Rees, Aled; Thapar, Anita; van Goozen, Stephanie H M

2017-01-01

Previous studies have found that oxytocin (OXT) can improve the recognition of emotional facial expressions; it has been proposed that this effect is mediated by an increase in attention to the eye-region of faces. Nevertheless, evidence in support of this claim is inconsistent, and few studies have directly tested the effect of oxytocin on emotion recognition via altered eye-gaze Methods: In a double-blind, within-subjects, randomized control experiment, 40 healthy male participants received 24 IU intranasal OXT and placebo in two identical experimental sessions separated by a 2-week interval. Visual attention to the eye-region was assessed on both occasions while participants completed a static facial emotion recognition task using medium intensity facial expressions. Although OXT had no effect on emotion recognition accuracy, recognition performance was improved because face processing was faster across emotions under the influence of OXT. This effect was marginally significant (p<.06). Consistent with a previous study using dynamic stimuli, OXT had no effect on eye-gaze patterns when viewing static emotional faces and this was not related to recognition accuracy or face processing time. These findings suggest that OXT-induced enhanced facial emotion recognition is not necessarily mediated by an increase in attention to the eye-region of faces, as previously assumed. We discuss several methodological issues which may explain discrepant findings and suggest the effect of OXT on visual attention may differ depending on task requirements. (JINS, 2017, 23, 23-33).
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.
The face of fear and anger: Facial width-to-height ratio biases recognition of angry and fearful expressions.

PubMed

Deska, Jason C; Lloyd, E Paige; Hugenberg, Kurt

2018-04-01

The ability to rapidly and accurately decode facial expressions is adaptive for human sociality. Although judgments of emotion are primarily determined by musculature, static face structure can also impact emotion judgments. The current work investigates how facial width-to-height ratio (fWHR), a stable feature of all faces, influences perceivers' judgments of expressive displays of anger and fear (Studies 1a, 1b, & 2), and anger and happiness (Study 3). Across 4 studies, we provide evidence consistent with the hypothesis that perceivers more readily see anger on faces with high fWHR compared with those with low fWHR, which instead facilitates the recognition of fear and happiness. This bias emerges when participants are led to believe that targets displaying otherwise neutral faces are attempting to mask an emotion (Studies 1a & 1b), and is evident when faces display an emotion (Studies 2 & 3). Together, these studies suggest that target facial width-to-height ratio biases ascriptions of emotion with consequences for emotion recognition speed and accuracy. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Multi-stream face recognition for crime-fighting

NASA Astrophysics Data System (ADS)

Jassim, Sabah A.; Sellahewa, Harin

2007-04-01

Automatic face recognition (AFR) is a challenging task that is increasingly becoming the preferred biometric trait for identification and has the potential of becoming an essential tool in the fight against crime and terrorism. Closed-circuit television (CCTV) cameras have increasingly been used over the last few years for surveillance in public places such as airports, train stations and shopping centers. They are used to detect and prevent crime, shoplifting, public disorder and terrorism. The work of law-enforcing and intelligence agencies is becoming more reliant on the use of databases of biometric data for large section of the population. Face is one of the most natural biometric traits that can be used for identification and surveillance. However, variations in lighting conditions, facial expressions, face size and pose are a great obstacle to AFR. This paper is concerned with using waveletbased face recognition schemes in the presence of variations of expressions and illumination. In particular, we will investigate the use of a combination of wavelet frequency channels for a multi-stream face recognition using various wavelet subbands as different face signal streams. The proposed schemes extend our recently developed face veri.cation scheme for implementation on mobile devices. We shall present experimental results on the performance of our proposed schemes for a number of face databases including a new AV database recorded on a PDA. By analyzing the various experimental data, we shall demonstrate that the multi-stream approach is robust against variations in illumination and facial expressions than the previous single-stream approach.
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…
Sex Differences in Facial Scanning: Similarities and Dissimilarities between Infants and Adults

ERIC Educational Resources Information Center

Rennels, Jennifer L.; Cummings, Andrew J.

2013-01-01

When face processing studies find sex differences, male infants appear better at face recognition than female infants, whereas female adults appear better at face recognition than male adults. Both female infants and adults, however, discriminate emotional expressions better than males. To investigate if sex and age differences in facial scanning…
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.
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).
Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

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

NASA Technical Reports Server (NTRS)

Spirkovska, L.; Reid, M. B.

1993-01-01

HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.
Enhanced Visual Short-Term Memory for Angry Faces

ERIC Educational Resources Information Center

Jackson, Margaret C.; Wu, Chia-Yun; Linden, David E. J.; Raymond, Jane E.

2009-01-01

Although some views of face perception posit independent processing of face identity and expression, recent studies suggest interactive processing of these 2 domains. The authors examined expression-identity interactions in visual short-term memory (VSTM) by assessing recognition performance in a VSTM task in which face identity was relevant and…
3D face recognition based on multiple keypoint descriptors and sparse representation.

PubMed

Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

2014-01-01

Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm.
Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

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

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.
Decoding facial expressions based on face-selective and motion-sensitive areas.

PubMed

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

2017-06-01

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

PubMed

Dapelo, Marcela Marin; Surguladze, Simon; Morris, Robin; Tchanturia, Kate

2017-11-01

Social cognition has been studied extensively in anorexia nervosa (AN), but there are few studies in bulimia nervosa (BN). This study investigated the ability of people with BN to recognise emotions in ambiguous facial expressions and in body movement. Participants were 26 women with BN, who were compared with 35 with AN, and 42 healthy controls. Participants completed an emotion recognition task by using faces portraying blended emotions, along with a body emotion recognition task by using videos of point-light walkers. The results indicated that BN participants exhibited difficulties recognising disgust in less-ambiguous facial expressions, and a tendency to interpret non-angry faces as anger, compared with healthy controls. These difficulties were similar to those found in AN. There were no significant differences amongst the groups in body motion emotion recognition. The findings suggest that difficulties with disgust and anger recognition in facial expressions may be shared transdiagnostically in people with eating disorders. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.
Computation of pattern invariance in brain-like structures.

PubMed

Ullman, S; Soloviev, S

1999-10-01

A fundamental capacity of the perceptual systems and the brain in general is to deal with the novel and the unexpected. In vision, we can effortlessly recognize a familiar object under novel viewing conditions, or recognize a new object as a member of a familiar class, such as a house, a face, or a car. This ability to generalize and deal efficiently with novel stimuli has long been considered a challenging example of brain-like computation that proved extremely difficult to replicate in artificial systems. In this paper we present an approach to generalization and invariant recognition. We focus our discussion on the problem of invariance to position in the visual field, but also sketch how similar principles could apply to other domains.The approach is based on the use of a large repertoire of partial generalizations that are built upon past experience. In the case of shift invariance, visual patterns are described as the conjunction of multiple overlapping image fragments. The invariance to the more primitive fragments is built into the system by past experience. Shift invariance of complex shapes is obtained from the invariance of their constituent fragments. We study by simulations aspects of this shift invariance method and then consider its extensions to invariant perception and classification by brain-like structures.
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
Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Oxytocin enhances attentional bias for neutral and positive expression faces in individuals with higher autistic traits.

PubMed

Xu, Lei; Ma, Xiaole; Zhao, Weihua; Luo, Lizhu; Yao, Shuxia; Kendrick, Keith M

2015-12-01

There is considerable interest in the potential therapeutic role of the neuropeptide oxytocin in altering attentional bias towards emotional social stimuli in psychiatric disorders. However, it is still unclear whether oxytocin primarily influences attention towards positive or negative valence social stimuli. Here in a double-blind, placebo controlled, between subject design experiment in 60 healthy male subjects we have used the highly sensitive dual-target rapid serial visual presentation (RSVP) paradigm to investigate whether intranasal oxytocin (40IU) treatment alters attentional bias for emotional faces. Results show that oxytocin improved recognition accuracy of neutral and happy expression faces presented in the second target position (T2) during the period of reduced attentional capacity following prior presentation of a first neutral face target (T1), but had no effect on recognition of negative expression faces (angry, fearful, sad). Oxytocin also had no effect on recognition of non-social stimuli (digits) in this task. Recognition accuracy for neutral faces at T2 was negatively associated with autism spectrum quotient (ASQ) scores in the placebo group, and oxytocin's facilitatory effects were restricted to a sub-group of subjects with higher ASQ scores. Our results therefore indicate that oxytocin primarily enhances the allocation of attentional resources towards faces expressing neutral or positive emotion and does not influence that towards negative emotion ones or non-social stimuli. This effect of oxytocin is strongest in healthy individuals with higher autistic trait scores, thereby providing further support for its potential therapeutic use in autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.
Adaptive Learning and Pruning Using Periodic Packet for Fast Invariance Extraction and Recognition

NASA Astrophysics Data System (ADS)

Chang, Sheng-Jiang; Zhang, Bian-Li; Lin, Lie; Xiong, Tao; Shen, Jin-Yuan

2005-02-01

A new learning scheme using a periodic packet as the neuronal activation function is proposed for invariance extraction and recognition of handwritten digits. Simulation results show that the proposed network can extract the invariant feature effectively and improve both the convergence and the recognition rate.
The development of newborn object recognition in fast and slow visual worlds

PubMed Central

Wood, Justin N.; Wood, Samantha M. W.

2016-01-01

Object recognition is central to perception and cognition. Yet relatively little is known about the environmental factors that cause invariant object recognition to emerge in the newborn brain. Is this ability a hardwired property of vision? Or does the development of invariant object recognition require experience with a particular kind of visual environment? Here, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) require visual experience with slowly changing objects to develop invariant object recognition abilities. When newborn chicks were raised with a slowly rotating virtual object, the chicks built invariant object representations that generalized across novel viewpoints and rotation speeds. In contrast, when newborn chicks were raised with a virtual object that rotated more quickly, the chicks built viewpoint-specific object representations that failed to generalize to novel viewpoints and rotation speeds. Moreover, there was a direct relationship between the speed of the object and the amount of invariance in the chick's object representation. Thus, visual experience with slowly changing objects plays a critical role in the development of invariant object recognition. These results indicate that invariant object recognition is not a hardwired property of vision, but is learned rapidly when newborns encounter a slowly changing visual world. PMID:27097925
Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.
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…
Facelock: familiarity-based graphical authentication

PubMed Central

McLachlan, Jane L.; Renaud, Karen

2014-01-01

Authentication codes such as passwords and PIN numbers are widely used to control access to resources. One major drawback of these codes is that they are difficult to remember. Account holders are often faced with a choice between forgetting a code, which can be inconvenient, or writing it down, which compromises security. In two studies, we test a new knowledge-based authentication method that does not impose memory load on the user. Psychological research on face recognition has revealed an important distinction between familiar and unfamiliar face perception: When a face is familiar to the observer, it can be identified across a wide range of images. However, when the face is unfamiliar, generalisation across images is poor. This contrast can be used as the basis for a personalised ‘facelock’, in which authentication succeeds or fails based on image-invariant recognition of faces that are familiar to the account holder. In Study 1, account holders authenticated easily by detecting familiar targets among other faces (97.5% success rate), even after a one-year delay (86.1% success rate). Zero-acquaintance attackers were reduced to guessing (<1% success rate). Even personal attackers who knew the account holder well were rarely able to authenticate (6.6% success rate). In Study 2, we found that shoulder-surfing attacks by strangers could be defeated by presenting different photos of the same target faces in observed and attacked grids (1.9% success rate). Our findings suggest that the contrast between familiar and unfamiliar face recognition may be useful for developers of graphical authentication systems. PMID:25024913
Gender differences in facial emotion recognition in persons with chronic schizophrenia.

PubMed

Weiss, Elisabeth M; Kohler, Christian G; Brensinger, Colleen M; Bilker, Warren B; Loughead, James; Delazer, Margarete; Nolan, Karen A

2007-03-01

The aim of the present study was to investigate possible sex differences in the recognition of facial expressions of emotion and to investigate the pattern of classification errors in schizophrenic males and females. Such an approach provides an opportunity to inspect the degree to which males and females differ in perceiving and interpreting the different emotions displayed to them and to analyze which emotions are most susceptible to recognition errors. Fifty six chronically hospitalized schizophrenic patients (38 men and 18 women) completed the Penn Emotion Recognition Test (ER40), a computerized emotion discrimination test presenting 40 color photographs of evoked happy, sad, anger, fear expressions and neutral expressions balanced for poser gender and ethnicity. We found a significant sex difference in the patterns of error rates in the Penn Emotion Recognition Test. Neutral faces were more commonly mistaken as angry in schizophrenic men, whereas schizophrenic women misinterpreted neutral faces more frequently as sad. Moreover, female faces were better recognized overall, but fear was better recognized in same gender photographs, whereas anger was better recognized in different gender photographs. The findings of the present study lend support to the notion that sex differences in aggressive behavior could be related to a cognitive style characterized by hostile attributions to neutral faces in schizophrenic men.
Perceiving emotions in neutral faces: expression processing is biased by affective person knowledge.

PubMed

Suess, Franziska; Rabovsky, Milena; Abdel Rahman, Rasha

2015-04-01

According to a widely held view, basic emotions such as happiness or anger are reflected in facial expressions that are invariant and uniquely defined by specific facial muscle movements. Accordingly, expression perception should not be vulnerable to influences outside the face. Here, we test this assumption by manipulating the emotional valence of biographical knowledge associated with individual persons. Faces of well-known and initially unfamiliar persons displaying neutral expressions were associated with socially relevant negative, positive or comparatively neutral biographical information. The expressions of faces associated with negative information were classified as more negative than faces associated with neutral information. Event-related brain potential modulations in the early posterior negativity, a component taken to reflect early sensory processing of affective stimuli such as emotional facial expressions, suggest that negative affective knowledge can bias the perception of faces with neutral expressions toward subjectively displaying negative emotions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Gender interactions in the recognition of emotions and conduct symptoms in adolescents.

PubMed

Halász, József; Aspán, Nikoletta; Bozsik, Csilla; Gádoros, Júlia; Inántsy-Pap, Judit

2014-01-01

According to literature data, impairment in the recognition of emotions might be related to antisocial developmental pathway. In the present study, the relationship between gender-specific interaction of emotion recognition and conduct symptoms were studied in non-clinical adolescents. After informed consent, 29 boys and 24 girls (13-16 years, 14 ± 0.1 years) participated in the study. The parent version of the Strengths and Difficulties Questionnaire was used to assess behavioral problems. The recognition of basic emotions was analyzed according to both the gender of the participants and the gender of the stimulus faces via the "Facial Expressions of Emotion- Stimuli and Tests". Girls were significantly better than boys in the recognition of disgust, irrespective from the gender of the stimulus faces, albeit both genders were significantly better in the recognition of disgust in the case of male stimulus faces compared to female stimulus faces. Both boys and girls were significantly better in the recognition of sadness in the case of female stimulus faces compared to male stimulus faces. There was no gender effect (neither participant nor stimulus faces) in the recognition of other emotions. Conduct scores in boys were inversely correlated with the recognition of fear in male stimulus faces (R=-0.439, p<0.05) and with overall emotion recognition in male stimulus faces (R=-0.558, p<0.01). In girls, conduct scores were shown a tendency for positive correlation with disgust recognition in female stimulus faces (R=0.376, p<0.07). A gender-specific interaction between the recognition of emotions and antisocial developmentalpathway is suggested.
Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.
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.
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
Target-context unitization effect on the familiarity-related FN400: a face recognition exclusion task.

PubMed

Guillaume, Fabrice; Etienne, Yann

2015-03-01

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition. Copyright © 2015 Elsevier B.V. All rights reserved.
The effect of age on memory for emotional faces.

PubMed

Grady, Cheryl L; Hongwanishkul, Donaya; Keightley, Michelle; Lee, Wendy; Hasher, Lynn

2007-05-01

Prior studies of emotion suggest that young adults should have enhanced memory for negative faces and that this enhancement should be reduced in older adults. Several studies have not shown these effects but were conducted with procedures different from those used with other emotional stimuli. In this study, researchers examined age differences in recognition of faces with emotional or neutral expressions, using trial-unique stimuli, as is typically done with other types of emotional stimuli. They also assessed the influence of personality traits and mood on memory. Enhanced recognition for negative faces was found in young adults but not in older adults. Recognition of faces was not influenced by mood or personality traits in young adults, but lower levels of extraversion and better emotional sensitivity predicted better negative face memory in older adults. These results suggest that negative expressions enhance memory for faces in young adults, as negative valence enhances memory for words and scenes. This enhancement is absent in older adults, but memory for emotional faces is modulated in older adults by personality traits that are relevant to emotional processing. (c) 2007 APA, all rights reserved
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.
Utterance independent bimodal emotion recognition in spontaneous communication

NASA Astrophysics Data System (ADS)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.
Experience moderates overlap between object and face recognition, suggesting a common ability

PubMed Central

Gauthier, Isabel; McGugin, Rankin W.; Richler, Jennifer J.; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E.

2014-01-01

Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. PMID:24993021
Experience moderates overlap between object and face recognition, suggesting a common ability.

PubMed

Gauthier, Isabel; McGugin, Rankin W; Richler, Jennifer J; Herzmann, Grit; Speegle, Magen; Van Gulick, Ana E

2014-07-03

Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience. © 2014 ARVO.
Permutation coding technique for image recognition systems.

PubMed

Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

2006-11-01

A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.
Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

PubMed Central

Rolls, Edmund T.

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

PubMed

Rolls, Edmund T

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.
3D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation

PubMed Central

Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

2014-01-01

Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm. PMID:24940876
Reading the lines in the face: The contribution of angularity and roundness to perceptions of facial anger and joy.

PubMed

Franklin, Robert G; Adams, Reginald B; Steiner, Troy G; Zebrowitz, Leslie A

2018-05-14

Through 3 studies, we investigated whether angularity and roundness present in faces contributes to the perception of anger and joyful expressions, respectively. First, in Study 1 we found that angry expressions naturally contain more inward-pointing lines, whereas joyful expressions contain more outward-pointing lines. Then, using image-processing techniques in Studies 2 and 3, we filtered images to contain only inward-pointing or outward-pointing lines as a way to approximate angularity and roundness. We found that filtering images to be more angular increased how threatening and angry a neutral face was rated, increased how intense angry expressions were rated, and enhanced the recognition of anger. Conversely, filtering images to be rounder increased how warm and joyful a neutral face was rated, increased the intensity of joyful expressions, and enhanced recognition of joy. Together these findings show that angularity and roundness play a direct role in the recognition of angry and joyful expressions. Given evidence that angularity and roundness may play a biological role in indicating threat and safety in the environment, this suggests that angularity and roundness represent primitive facial cues used to signal threat-anger and warmth-joy pairings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Impaired Integration of Emotional Faces and Affective Body Context in a Rare Case of Developmental Visual Agnosia

PubMed Central

Aviezer, Hillel; Hassin, Ran. R.; Bentin, Shlomo

2011-01-01

In the current study we examined the recognition of facial expressions embedded in emotionally expressive bodies in case LG, an individual with a rare form of developmental visual agnosia who suffers from severe prosopagnosia. Neuropsychological testing demonstrated that LG‘s agnosia is characterized by profoundly impaired visual integration. Unlike individuals with typical developmental prosopagnosia who display specific difficulties with face identity (but typically not expression) recognition, LG was also impaired at recognizing isolated facial expressions. By contrast, he successfully recognized the expressions portrayed by faceless emotional bodies handling affective paraphernalia. When presented with contextualized faces in emotional bodies his ability to detect the emotion expressed by a face did not improve even if it was embedded in an emotionally-congruent body context. Furthermore, in contrast to controls, LG displayed an abnormal pattern of contextual influence from emotionally-incongruent bodies. The results are interpreted in the context of a general integration deficit in developmental visual agnosia, suggesting that impaired integration may extend from the level of the face to the level of the full person. PMID:21482423
Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze.

PubMed

Wells, Laura Jean; Gillespie, Steven Mark; Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down.
Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze

PubMed Central

Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down. PMID:27942030
Super-resolution method for face recognition using nonlinear mappings on coherent features.

PubMed

Huang, Hua; He, Huiting

2011-01-01

Low-resolution (LR) of face images significantly decreases the performance of face recognition. To address this problem, we present a super-resolution method that uses nonlinear mappings to infer coherent features that favor higher recognition of the nearest neighbor (NN) classifiers for recognition of single LR face image. Canonical correlation analysis is applied to establish the coherent subspaces between the principal component analysis (PCA) based features of high-resolution (HR) and LR face images. Then, a nonlinear mapping between HR/LR features can be built by radial basis functions (RBFs) with lower regression errors in the coherent feature space than in the PCA feature space. Thus, we can compute super-resolved coherent features corresponding to an input LR image according to the trained RBF model efficiently and accurately. And, face identity can be obtained by feeding these super-resolved features to a simple NN classifier. Extensive experiments on the Facial Recognition Technology, University of Manchester Institute of Science and Technology, and Olivetti Research Laboratory databases show that the proposed method outperforms the state-of-the-art face recognition algorithms for single LR image in terms of both recognition rate and robustness to facial variations of pose and expression.
Binary optical filters for scale invariant pattern recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Downie, John D.; Hine, Butler P.

1992-01-01

Binary synthetic discriminant function (BSDF) optical filters which are invariant to scale changes in the target object of more than 50 percent are demonstrated in simulation and experiment. Efficient databases of scale invariant BSDF filters can be designed which discriminate between two very similar objects at any view scaled over a factor of 2 or more. The BSDF technique has considerable advantages over other methods for achieving scale invariant object recognition, as it also allows determination of the object's scale. In addition to scale, the technique can be used to design recognition systems invariant to other geometric distortions.
Familiarity and face emotion recognition in patients with schizophrenia.

PubMed

Lahera, Guillermo; Herrera, Sara; Fernández, Cristina; Bardón, Marta; de los Ángeles, Victoria; Fernández-Liria, Alberto

2014-01-01

To assess the emotion recognition in familiar and unknown faces in a sample of schizophrenic patients and healthy controls. Face emotion recognition of 18 outpatients diagnosed with schizophrenia (DSM-IVTR) and 18 healthy volunteers was assessed with two Emotion Recognition Tasks using familiar faces and unknown faces. Each subject was accompanied by 4 familiar people (parents, siblings or friends), which were photographed by expressing the 6 Ekman's basic emotions. Face emotion recognition in familiar faces was assessed with this ad hoc instrument. In each case, the patient scored (from 1 to 10) the subjective familiarity and affective valence corresponding to each person. Patients with schizophrenia not only showed a deficit in the recognition of emotions on unknown faces (p=.01), but they also showed an even more pronounced deficit on familiar faces (p=.001). Controls had a similar success rate in the unknown faces task (mean: 18 +/- 2.2) and the familiar face task (mean: 17.4 +/- 3). However, patients had a significantly lower score in the familiar faces task (mean: 13.2 +/- 3.8) than in the unknown faces task (mean: 16 +/- 2.4; p<.05). In both tests, the highest number of errors was with emotions of anger and fear. Subjectively, the patient group showed a lower level of familiarity and emotional valence to their respective relatives (p<.01). The sense of familiarity may be a factor involved in the face emotion recognition and it may be disturbed in schizophrenia. © 2013.
[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.
A Smile Enhances 3-Month-Olds' Recognition of an Individual Face

ERIC Educational Resources Information Center

Turati, Chiara; Montirosso, Rosario; Brenna, Viola; Ferrara, Veronica; Borgatti, Renato

2011-01-01

Recent studies demonstrated that in adults and children recognition of face identity and facial expression mutually interact (Bate, Haslam, & Hodgson, 2009; Spangler, Schwarzer, Korell, & Maier-Karius, 2010). Here, using a familiarization paradigm, we explored the relation between these processes in early infancy, investigating whether 3-month-old…
Impact of Intention on the ERP Correlates of Face Recognition

ERIC Educational Resources Information Center

Guillaume, Fabrice; Tiberghien, Guy

2013-01-01

The present study investigated the impact of study-test similarity on face recognition by manipulating, in the same experiment, the expression change (same vs. different) and the task-processing context (inclusion vs. exclusion instructions) as within-subject variables. Consistent with the dual-process framework, the present results showed that…
New technique for real-time distortion-invariant multiobject recognition and classification

NASA Astrophysics Data System (ADS)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.
Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.
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.
Is fear in your head? A comparison of instructed and real-life expressions of emotion in the face and body.

PubMed

Abramson, Lior; Marom, Inbal; Petranker, Rotem; Aviezer, Hillel

2017-04-01

The majority of emotion perception studies utilize instructed and stereotypical expressions of faces or bodies. While such stimuli are highly standardized and well-recognized, their resemblance to real-life expressions of emotion remains unknown. Here we examined facial and body expressions of fear and anger during real-life situations and compared their recognition to that of instructed expressions of the same emotions. In order to examine the source of the affective signal, expressions of emotion were presented as faces alone, bodies alone, and naturally, as faces with bodies. The results demonstrated striking deviations between recognition of instructed and real-life stimuli, which differed as a function of the emotion expressed. In real-life fearful expressions of emotion, bodies were far better recognized than faces, a pattern not found with instructed expressions of emotion. Anger reactions were better recognized from the body than from the face in both real-life and instructed stimuli. However, the real-life stimuli were overall better recognized than their instructed counterparts. These results indicate that differences between instructed and real-life expressions of emotion are prevalent and raise caution against an overreliance of researchers on instructed affective stimuli. The findings also demonstrate that in real life, facial expression perception may rely heavily on information from the contextualizing body. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.
Fear recognition impairment in early-stage Alzheimer's disease: when focusing on the eyes region improves performance.

PubMed

Hot, Pascal; Klein-Koerkamp, Yanica; Borg, Céline; Richard-Mornas, Aurélie; Zsoldos, Isabella; Paignon Adeline, Adeline; Thomas Antérion, Catherine; Baciu, Monica

2013-06-01

A decline in the ability to identify fearful expression has been frequently reported in patients with Alzheimer's disease (AD). In patients with severe destruction of the bilateral amygdala, similar difficulties have been reduced by using an explicit visual exploration strategy focusing on gaze. The current study assessed the possibility of applying a similar strategy in AD patients to improve fear recognition. It also assessed the possibility of improving fear recognition when a visual exploration strategy induced AD patients to process the eyes region. Seventeen patients with mild AD and 34 healthy subjects (17 young adults and 17 older adults) performed a classical task of emotional identification of faces expressing happiness, anger, and fear in two conditions: The face appeared progressively from the eyes region to the periphery (eyes region condition) or it appeared as a whole (global condition). Specific impairment in identifying a fearful expression was shown in AD patients compared with older adult controls during the global condition. Fear expression recognition was significantly improved in AD patients during the eyes region condition, in which they performed similarly to older adult controls. Our results suggest that using a different strategy of face exploration, starting first with processing of the eyes region, may compensate for a fear recognition deficit in AD patients. Findings suggest that a part of this deficit could be related to visuo-perceptual impairments. Additionally, these findings suggest that the decline of fearful face recognition reported in both normal aging and in AD may result from impairment of non-amygdalar processing in both groups and impairment of amygdalar-dependent processing in AD. Copyright © 2013 Elsevier Inc. All rights reserved.
Locality constrained joint dynamic sparse representation for local matching based face recognition.

PubMed

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.
Emotion recognition deficits associated with ventromedial prefrontal cortex lesions are improved by gaze manipulation.

PubMed

Wolf, Richard C; Pujara, Maia; Baskaya, Mustafa K; Koenigs, Michael

2016-09-01

Facial emotion recognition is a critical aspect of human communication. Since abnormalities in facial emotion recognition are associated with social and affective impairment in a variety of psychiatric and neurological conditions, identifying the neural substrates and psychological processes underlying facial emotion recognition will help advance basic and translational research on social-affective function. Ventromedial prefrontal cortex (vmPFC) has recently been implicated in deploying visual attention to the eyes of emotional faces, although there is mixed evidence regarding the importance of this brain region for recognition accuracy. In the present study of neurological patients with vmPFC damage, we used an emotion recognition task with morphed facial expressions of varying intensities to determine (1) whether vmPFC is essential for emotion recognition accuracy, and (2) whether instructed attention to the eyes of faces would be sufficient to improve any accuracy deficits. We found that vmPFC lesion patients are impaired, relative to neurologically healthy adults, at recognizing moderate intensity expressions of anger and that recognition accuracy can be improved by providing instructions of where to fixate. These results suggest that vmPFC may be important for the recognition of facial emotion through a role in guiding visual attention to emotionally salient regions of faces. Copyright © 2016 Elsevier Ltd. All rights reserved.

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

PubMed

De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.
Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.
Unseen stimuli modulate conscious visual experience: evidence from inter-hemispheric summation.

PubMed

de Gelder, B; Pourtois, G; van Raamsdonk, M; Vroomen, J; Weiskrantz, L

2001-02-12

Emotional facial expression can be discriminated despite extensive lesions of striate cortex. Here we report differential performance with recognition of facial stimuli in the intact visual field depending on simultaneous presentation of congruent or incongruent stimuli in the blind field. Three experiments were based on inter-hemispheric summation. Redundant stimulation in the blind field led to shorter latencies for stimulus detection in the intact field. Recognition of the expression of a half-face expression in the intact field was faster when the other half of the face presented to the blind field had a congruent expression. Finally, responses to the expression of whole faces to the intact field were delayed for incongruent facial expressions presented in the blind field. These results indicate that the neuro-anatomical pathways (extra-striate cortical and sub-cortical) sustaining inter-hemispheric summation can operate in the absence of striate cortex.
Configural information in gender categorisation.

PubMed

Baudouin, Jean-Yves; Humphreys, Glyn W

2006-01-01

The role of configural information in gender categorisation was studied by aligning the top half of one face with the bottom half of another. The two faces had the same or different genders. Experiment 1 shows that participants were slower and made more errors in categorising the gender in either half of these composite faces when the two faces had a different gender, relative to control conditions where the two faces were nonaligned or had the same gender. This result parallels the composite effect for face recognition (Young et al, 1987 Perception 16 747-759) and facial-expression recognition (Calder et al, 2000 Journal of Experimental Psychology: Human Perception and Performance 26 527-551). Similarly to responses to face identity and expression, the composite effect on gender discrimination was disrupted by inverting the faces (experiment 2). Both experiments also show that the composite paradigm is sensitive to general contextual interference in gender categorisation.
Face recognition in age related macular degeneration: perceived disability, measured disability, and performance with a bioptic device.

PubMed

Tejeria, L; Harper, R A; Artes, P H; Dickinson, C M

2002-09-01

(1) To explore the relation between performance on tasks of familiar face recognition (FFR) and face expression difference discrimination (FED) with both perceived disability in face recognition and clinical measures of visual function in subjects with age related macular degeneration (AMD). (2) To quantify the gain in performance for face recognition tasks when subjects use a bioptic telescopic low vision device. 30 subjects with AMD (age range 66-90 years; visual acuity 0.4-1.4 logMAR) were recruited for the study. Perceived (self rated) disability in face recognition was assessed by an eight item questionnaire covering a range of issues relating to face recognition. Visual functions measured were distance visual acuity (ETDRS logMAR charts), continuous text reading acuity (MNRead charts), contrast sensitivity (Pelli-Robson chart), and colour vision (large panel D-15). In the FFR task, images of famous people had to be identified. FED was assessed by a forced choice test where subjects had to decide which one of four images showed a different facial expression. These tasks were repeated with subjects using a bioptic device. Overall perceived disability in face recognition did not correlate with performance on either task, although a specific item on difficulty recognising familiar faces did correlate with FFR (r = 0.49, p<0.05). FFR performance was most closely related to distance acuity (r = -0.69, p<0.001), while FED performance was most closely related to continuous text reading acuity (r = -0.79, p<0.001). In multiple regression, neither contrast sensitivity nor colour vision significantly increased the explained variance. When using a bioptic telescope, FFR performance improved in 86% of subjects (median gain = 49%; p<0.001), while FED performance increased in 79% of subjects (median gain = 50%; p<0.01). Distance and reading visual acuity are closely associated with measured task performance in FFR and FED. A bioptic low vision device can offer a significant improvement in performance for face recognition tasks, and may be useful in reducing the handicap associated with this disability. There is, however, little evidence for a correlation between self rated difficulty in face recognition and measured performance for either task. Further work is needed to explore the complex relation between the perception of disability and measured performance.
Face recognition in age related macular degeneration: perceived disability, measured disability, and performance with a bioptic device

PubMed Central

Tejeria, L; Harper, R A; Artes, P H; Dickinson, C M

2002-01-01

Aims: (1) To explore the relation between performance on tasks of familiar face recognition (FFR) and face expression difference discrimination (FED) with both perceived disability in face recognition and clinical measures of visual function in subjects with age related macular degeneration (AMD). (2) To quantify the gain in performance for face recognition tasks when subjects use a bioptic telescopic low vision device. Methods: 30 subjects with AMD (age range 66–90 years; visual acuity 0.4–1.4 logMAR) were recruited for the study. Perceived (self rated) disability in face recognition was assessed by an eight item questionnaire covering a range of issues relating to face recognition. Visual functions measured were distance visual acuity (ETDRS logMAR charts), continuous text reading acuity (MNRead charts), contrast sensitivity (Pelli-Robson chart), and colour vision (large panel D-15). In the FFR task, images of famous people had to be identified. FED was assessed by a forced choice test where subjects had to decide which one of four images showed a different facial expression. These tasks were repeated with subjects using a bioptic device. Results: Overall perceived disability in face recognition did not correlate with performance on either task, although a specific item on difficulty recognising familiar faces did correlate with FFR (r = 0.49, p<0.05). FFR performance was most closely related to distance acuity (r = −0.69, p<0.001), while FED performance was most closely related to continuous text reading acuity (r = −0.79, p<0.001). In multiple regression, neither contrast sensitivity nor colour vision significantly increased the explained variance. When using a bioptic telescope, FFR performance improved in 86% of subjects (median gain = 49%; p<0.001), while FED performance increased in 79% of subjects (median gain = 50%; p<0.01). Conclusion: Distance and reading visual acuity are closely associated with measured task performance in FFR and FED. A bioptic low vision device can offer a significant improvement in performance for face recognition tasks, and may be useful in reducing the handicap associated with this disability. There is, however, little evidence for a correlation between self rated difficulty in face recognition and measured performance for either task. Further work is needed to explore the complex relation between the perception of disability and measured performance. PMID:12185131
Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind

PubMed Central

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T.; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J.; Sadato, Norihiro

2012-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience. PMID:23372547
Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind.

PubMed

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J; Sadato, Norihiro

2013-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience.
The Automaticity of Emotional Face-Context Integration

PubMed Central

Aviezer, Hillel; Dudarev, Veronica; Bentin, Shlomo; Hassin, Ran R.

2011-01-01

Recent studies have demonstrated that context can dramatically influence the recognition of basic facial expressions, yet the nature of this phenomenon is largely unknown. In the present paper we begin to characterize the underlying process of face-context integration. Specifically, we examine whether it is a relatively controlled or automatic process. In Experiment 1 participants were motivated and instructed to avoid using the context while categorizing contextualized facial expression, or they were led to believe that the context was irrelevant. Nevertheless, they were unable to disregard the context, which exerted a strong effect on their emotion recognition. In Experiment 2, participants categorized contextualized facial expressions while engaged in a concurrent working memory task. Despite the load, the context exerted a strong influence on their recognition of facial expressions. These results suggest that facial expressions and their body contexts are integrated in an unintentional, uncontrollable, and relatively effortless manner. PMID:21707150
Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.
Robust Eye Center Localization through Face Alignment and Invariant Isocentric Patterns

PubMed Central

Teng, Dongdong; Chen, Dihu; Tan, Hongzhou

2015-01-01

The localization of eye centers is a very useful cue for numerous applications like face recognition, facial expression recognition, and the early screening of neurological pathologies. Several methods relying on available light for accurate eye-center localization have been exploited. However, despite the considerable improvements that eye-center localization systems have undergone in recent years, only few of these developments deal with the challenges posed by the profile (non-frontal face). In this paper, we first use the explicit shape regression method to obtain the rough location of the eye centers. Because this method extracts global information from the human face, it is robust against any changes in the eye region. We exploit this robustness and utilize it as a constraint. To locate the eye centers accurately, we employ isophote curvature features, the accuracy of which has been demonstrated in a previous study. By applying these features, we obtain a series of eye-center locations which are candidates for the actual position of the eye-center. Among these locations, the estimated locations which minimize the reconstruction error between the two methods mentioned above are taken as the closest approximation for the eye centers locations. Therefore, we combine explicit shape regression and isophote curvature feature analysis to achieve robustness and accuracy, respectively. In practical experiments, we use BioID and FERET datasets to test our approach to obtaining an accurate eye-center location while retaining robustness against changes in scale and pose. In addition, we apply our method to non-frontal faces to test its robustness and accuracy, which are essential in gaze estimation but have seldom been mentioned in previous works. Through extensive experimentation, we show that the proposed method can achieve a significant improvement in accuracy and robustness over state-of-the-art techniques, with our method ranking second in terms of accuracy. According to our implementation on a PC with a Xeon 2.5Ghz CPU, the frame rate of the eye tracking process can achieve 38 Hz. PMID:26426929
Cross-cultural differences and similarities underlying other-race effects for facial identity and expression.

PubMed

Yan, Xiaoqian; Andrews, Timothy J; Jenkins, Rob; Young, Andrew W

2016-01-01

Perceptual advantages for own-race compared to other-race faces have been demonstrated for the recognition of facial identity and expression. However, these effects have not been investigated in the same study with measures that can determine the extent of cross-cultural agreement as well as differences. To address this issue, we used a photo sorting task in which Chinese and Caucasian participants were asked to sort photographs of Chinese or Caucasian faces by identity or by expression. This paradigm matched the task demands of identity and expression recognition and avoided constrained forced-choice or verbal labelling requirements. Other-race effects of comparable magnitude were found across the identity and expression tasks. Caucasian participants made more confusion errors for the identities and expressions of Chinese than Caucasian faces, while Chinese participants made more confusion errors for the identities and expressions of Caucasian than Chinese faces. However, analyses of the patterns of responses across groups of participants revealed a considerable amount of underlying cross-cultural agreement. These findings suggest that widely repeated claims that members of other cultures "all look the same" overstate the cultural differences.
DeitY-TU face database: its design, multiple camera capturing, characteristics, and evaluation

NASA Astrophysics Data System (ADS)

Bhowmik, Mrinal Kanti; Saha, Kankan; Saha, Priya; Bhattacharjee, Debotosh

2014-10-01

The development of the latest face databases is providing researchers different and realistic problems that play an important role in the development of efficient algorithms for solving the difficulties during automatic recognition of human faces. This paper presents the creation of a new visual face database, named the Department of Electronics and Information Technology-Tripura University (DeitY-TU) face database. It contains face images of 524 persons belonging to different nontribes and Mongolian tribes of north-east India, with their anthropometric measurements for identification. Database images are captured within a room with controlled variations in illumination, expression, and pose along with variability in age, gender, accessories, make-up, and partial occlusion. Each image contains the combined primary challenges of face recognition, i.e., illumination, expression, and pose. This database also represents some new features: soft biometric traits such as mole, freckle, scar, etc., and facial anthropometric variations that may be helpful for researchers for biometric recognition. It also gives an equivalent study of the existing two-dimensional face image databases. The database has been tested using two baseline algorithms: linear discriminant analysis and principal component analysis, which may be used by other researchers as the control algorithm performance score.
Emotional face recognition deficits and medication effects in pre-manifest through stage-II Huntington's disease.

PubMed

Labuschagne, Izelle; Jones, Rebecca; Callaghan, Jenny; Whitehead, Daisy; Dumas, Eve M; Say, Miranda J; Hart, Ellen P; Justo, Damian; Coleman, Allison; Dar Santos, Rachelle C; Frost, Chris; Craufurd, David; Tabrizi, Sarah J; Stout, Julie C

2013-05-15

Facial emotion recognition impairments have been reported in Huntington's disease (HD). However, the nature of the impairments across the spectrum of HD remains unclear. We report on emotion recognition data from 344 participants comprising premanifest HD (PreHD) and early HD patients, and controls. In a test of recognition of facial emotions, we examined responses to six basic emotional expressions and neutral expressions. In addition, and within the early HD sample, we tested for differences on emotion recognition performance between those 'on' vs. 'off' neuroleptic or selective serotonin reuptake inhibitor (SSRI) medications. The PreHD groups showed significant (p<0.05) impaired recognition, compared to controls, on fearful, angry and surprised faces; whereas the early HD groups were significantly impaired across all emotions including neutral expressions. In early HD, neuroleptic use was associated with worse facial emotion recognition, whereas SSRI use was associated with better facial emotion recognition. The findings suggest that emotion recognition impairments exist across the HD spectrum, but are relatively more widespread in manifest HD than in the premanifest period. Commonly prescribed medications to treat HD-related symptoms also appear to affect emotion recognition. These findings have important implications for interpersonal communication and medication usage in HD. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Face Recognition across Varying Poses in 7- and 9-Month-Old Infants: The Role of Facial Expression

ERIC Educational Resources Information Center

Gross, Cornelia; Schwarzer, Gudrun

2010-01-01

Three studies were conducted to determine whether 7- and 9-month-old infants generalize face identity to a novel pose of the same face when only internal face sections with and without an emotional expression were presented. In Study 1, 7- and 9-month-old infants were habituated to a full frontal or three-quarter pose of a face with neutral facial…
Recognition of blurred images by the method of moments.

PubMed

Flusser, J; Suk, T; Saic, S

1996-01-01

The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.
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
Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.
Emotion processing in chimeric faces: hemispheric asymmetries in expression and recognition of emotions.

PubMed

Indersmitten, Tim; Gur, Ruben C

2003-05-01

Since the discovery of facial asymmetries in emotional expressions of humans and other primates, hypotheses have related the greater left-hemiface intensity to right-hemispheric dominance in emotion processing. However, the difficulty of creating true frontal views of facial expressions in two-dimensional photographs has confounded efforts to better understand the phenomenon. We have recently described a method for obtaining three-dimensional photographs of posed and evoked emotional expressions and used these stimuli to investigate both intensity of expression and accuracy of recognizing emotion in chimeric faces constructed from only left- or right-side composites. The participant population included 38 (19 male, 19 female) African-American, Caucasian, and Asian adults. They were presented with chimeric composites generated from faces of eight actors and eight actresses showing four emotions: happiness, sadness, anger, and fear, each in posed and evoked conditions. We replicated the finding that emotions are expressed more intensely in the left hemiface for all emotions and conditions, with the exception of evoked anger, which was expressed more intensely in the right hemiface. In contrast, the results indicated that emotional expressions are recognized more efficiently in the right hemiface, indicating that the right hemiface expresses emotions more accurately. The double dissociation between the laterality of expression intensity and that of recognition efficiency supports the notion that the two kinds of processes may have distinct neural substrates. Evoked anger is uniquely expressed more intensely and accurately on the side of the face that projects to the viewer's right hemisphere, dominant in emotion recognition.
Fractionation of memory in medial temporal lobe amnesia.

PubMed

Bird, Chris M; Shallice, Tim; Cipolotti, Lisa

2007-03-25

We report a comprehensive investigation of the anterograde memory functions of two patients with memory impairments (RH and JC). RH had neuroradiological evidence of apparently selective right-sided hippocampal damage and an intact cognitive profile apart from selective memory impairments. JC, had neuroradiological evidence of bilateral hippocampal damage following anoxia due to cardiac arrest. He had anomic and "executive" difficulties in addition to a global amnesia, suggesting atrophy extending beyond hippocampal regions. Their performance is compared with that of a previously reported hippocampal amnesic patient who showed preserved recollection and familiarity for faces in the context of severe verbal and topographical memory impairment [VC; Cipolotti, L., Bird, C., Good, T., Macmanus, D., Rudge, P., & Shallice, T. (2006). Recollection and familiarity in dense hippocampal amnesia: A case study. Neuropsychologia, 44, 489-506.] The patients were administered experimental tests using verbal (words) and two types of non-verbal materials (faces and buildings). Receiver operating characteristic analyses were used to estimate the contribution of recollection and familiarity to recognition performance on the experimental tests. RH had preserved verbal recognition memory. Interestingly, her face recognition memory was also spared, whilst topographical recognition memory was impaired. JC was impaired for all types of verbal and non-verbal materials. In both patients, deficits in recollection were invariably associated with deficits in familiarity. JC's data demonstrate the need for a comprehensive cognitive investigation in patients with apparently selective hippocampal damage following anoxia. The data from RH suggest that the right hippocampus is necessary for recollection and familiarity for topographical materials, whilst the left hippocampus is sufficient to underpin these processes for at least some types of verbal materials. Face recognition memory may be adequately subserved by areas outside of the hippocampus.

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.
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.
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.
Perception of face and body expressions using electromyography, pupillometry and gaze measures.

PubMed

Kret, Mariska E; Stekelenburg, Jeroen J; Roelofs, Karin; de Gelder, Beatrice

2013-01-01

Traditional emotion theories stress the importance of the face in the expression of emotions but bodily expressions are becoming increasingly important as well. In these experiments we tested the hypothesis that similar physiological responses can be evoked by observing emotional face and body signals and that the reaction to angry signals is amplified in anxious individuals. We designed three experiments in which participants categorized emotional expressions from isolated facial and bodily expressions and emotionally congruent and incongruent face-body compounds. Participants' fixations were measured and their pupil size recorded with eye-tracking equipment and their facial reactions measured with electromyography. The results support our prediction that the recognition of a facial expression is improved in the context of a matching posture and importantly, vice versa as well. From their facial expressions, it appeared that observers acted with signs of negative emotionality (increased corrugator activity) to angry and fearful facial expressions and with positive emotionality (increased zygomaticus) to happy facial expressions. What we predicted and found, was that angry and fearful cues from the face or the body, attracted more attention than happy cues. We further observed that responses evoked by angry cues were amplified in individuals with high anxiety scores. In sum, we show that people process bodily expressions of emotion in a similar fashion as facial expressions and that the congruency between the emotional signals from the face and body facilitates the recognition of the emotion.
Perception of Face and Body Expressions Using Electromyography, Pupillometry and Gaze Measures

PubMed Central

Kret, Mariska E.; Stekelenburg, Jeroen J.; Roelofs, Karin; de Gelder, Beatrice

2013-01-01

Traditional emotion theories stress the importance of the face in the expression of emotions but bodily expressions are becoming increasingly important as well. In these experiments we tested the hypothesis that similar physiological responses can be evoked by observing emotional face and body signals and that the reaction to angry signals is amplified in anxious individuals. We designed three experiments in which participants categorized emotional expressions from isolated facial and bodily expressions and emotionally congruent and incongruent face-body compounds. Participants’ fixations were measured and their pupil size recorded with eye-tracking equipment and their facial reactions measured with electromyography. The results support our prediction that the recognition of a facial expression is improved in the context of a matching posture and importantly, vice versa as well. From their facial expressions, it appeared that observers acted with signs of negative emotionality (increased corrugator activity) to angry and fearful facial expressions and with positive emotionality (increased zygomaticus) to happy facial expressions. What we predicted and found, was that angry and fearful cues from the face or the body, attracted more attention than happy cues. We further observed that responses evoked by angry cues were amplified in individuals with high anxiety scores. In sum, we show that people process bodily expressions of emotion in a similar fashion as facial expressions and that the congruency between the emotional signals from the face and body facilitates the recognition of the emotion. PMID:23403886
Rotation, scale, and translation invariant pattern recognition using feature extraction

NASA Astrophysics Data System (ADS)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.
Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523
Face photo-sketch synthesis and recognition.

PubMed

Wang, Xiaogang; Tang, Xiaoou

2009-11-01

In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications for both digital entertainment and law enforcement. We assume that faces to be studied are in a frontal pose, with normal lighting and neutral expression, and have no occlusions. To synthesize sketch/photo images, the face region is divided into overlapping patches for learning. The size of the patches decides the scale of local face structures to be learned. From a training set which contains photo-sketch pairs, the joint photo-sketch model is learned at multiple scales using a multiscale MRF model. By transforming a face photo to a sketch (or transforming a sketch to a photo), the difference between photos and sketches is significantly reduced, thus allowing effective matching between the two in face sketch recognition. After the photo-sketch transformation, in principle, most of the proposed face photo recognition approaches can be applied to face sketch recognition in a straightforward way. Extensive experiments are conducted on a face sketch database including 606 faces, which can be downloaded from our Web site (http://mmlab.ie.cuhk.edu.hk/facesketch.html).
Facial first impressions from another angle: How social judgements are influenced by changeable and invariant facial properties.

PubMed

Sutherland, Clare A M; Young, Andrew W; Rhodes, Gillian

2017-05-01

First impressions made to photographs of faces can depend as much on momentary characteristics of the photographed image (within-person variability) as on consistent properties of the face of the person depicted (between-person variability). Here, we examine two important sources of within-person variability: emotional expression and viewpoint. We find more within-person variability than between-person variability for social impressions of key traits of trustworthiness, dominance, and attractiveness, which index the main dimensions in theoretical models of facial impressions. The most important source of this variability is the emotional expression of the face, but the viewpoint of the photograph also affects impressions and modulates the effects of expression. For example, faces look most trustworthy with a happy expression when they are facing the perceiver, compared to when they are facing elsewhere, whereas the opposite is true for anger and disgust. Our findings highlight the integration of these different sources of variability in social impression formation. © 2016 The British Psychological Society.
Biased recognition of facial affect in patients with major depressive disorder reflects clinical state.

PubMed

Münkler, Paula; Rothkirch, Marcus; Dalati, Yasmin; Schmack, Katharina; Sterzer, Philipp

2015-01-01

Cognitive theories of depression posit that perception is negatively biased in depressive disorder. Previous studies have provided empirical evidence for this notion, but left open the question whether the negative perceptual bias reflects a stable trait or the current depressive state. Here we investigated the stability of negatively biased perception over time. Emotion perception was examined in patients with major depressive disorder (MDD) and healthy control participants in two experiments. In the first experiment subjective biases in the recognition of facial emotional expressions were assessed. Participants were presented with faces that were morphed between sad and neutral and happy expressions and had to decide whether the face was sad or happy. The second experiment assessed automatic emotion processing by measuring the potency of emotional faces to gain access to awareness using interocular suppression. A follow-up investigation using the same tests was performed three months later. In the emotion recognition task, patients with major depression showed a shift in the criterion for the differentiation between sad and happy faces: In comparison to healthy controls, patients with MDD required a greater intensity of the happy expression to recognize a face as happy. After three months, this negative perceptual bias was reduced in comparison to the control group. The reduction in negative perceptual bias correlated with the reduction of depressive symptoms. In contrast to previous work, we found no evidence for preferential access to awareness of sad vs. happy faces. Taken together, our results indicate that MDD-related perceptual biases in emotion recognition reflect the current clinical state rather than a stable depressive trait.
Reconstructing 3D Face Model with Associated Expression Deformation from a Single Face Image via Constructing a Low-Dimensional Expression Deformation Manifold.

PubMed

Wang, Shu-Fan; Lai, Shang-Hong

2011-10-01

Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.
Cultural differences in gaze and emotion recognition: Americans contrast more than Chinese.

PubMed

Stanley, Jennifer Tehan; Zhang, Xin; Fung, Helene H; Isaacowitz, Derek M

2013-02-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye-tracking data suggest that, for some emotions, Americans attended more to the target faces, and they made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Cultural Differences in Gaze and Emotion Recognition: Americans Contrast More than Chinese

PubMed Central

Tehan Stanley, Jennifer; Zhang, Xin; Fung, Helene H.; Isaacowitz, Derek M.

2014-01-01

We investigated the influence of contextual expressions on emotion recognition accuracy and gaze patterns among American and Chinese participants. We expected Chinese participants would be more influenced by, and attend more to, contextual information than Americans. Consistent with our hypothesis, Americans were more accurate than Chinese participants at recognizing emotions embedded in the context of other emotional expressions. Eye tracking data suggest that, for some emotions, Americans attended more to the target faces and made more gaze transitions to the target face than Chinese. For all emotions except anger and disgust, Americans appeared to use more of a contrasting strategy where each face was individually contrasted with the target face, compared with Chinese who used less of a contrasting strategy. Both cultures were influenced by contextual information, although the benefit of contextual information depended upon the perceptual dissimilarity of the contextual emotions to the target emotion and the gaze pattern employed during the recognition task. PMID:22889414
Human and animal sounds influence recognition of body language.

PubMed

Van den Stock, Jan; Grèzes, Julie; de Gelder, Beatrice

2008-11-25

In naturalistic settings emotional events have multiple correlates and are simultaneously perceived by several sensory systems. Recent studies have shown that recognition of facial expressions is biased towards the emotion expressed by a simultaneously presented emotional expression in the voice even if attention is directed to the face only. So far, no study examined whether this phenomenon also applies to whole body expressions, although there is no obvious reason why this crossmodal influence would be specific for faces. Here we investigated whether perception of emotions expressed in whole body movements is influenced by affective information provided by human and by animal vocalizations. Participants were instructed to attend to the action displayed by the body and to categorize the expressed emotion. The results indicate that recognition of body language is biased towards the emotion expressed by the simultaneously presented auditory information, whether it consist of human or of animal sounds. Our results show that a crossmodal influence from auditory to visual emotional information obtains for whole body video images with the facial expression blanked and includes human as well as animal sounds.
Pose invariant face recognition: 3D model from single photo

NASA Astrophysics Data System (ADS)

Napoléon, Thibault; Alfalou, Ayman

2017-02-01

Face recognition is widely studied in the literature for its possibilities in surveillance and security. In this paper, we report a novel algorithm for the identification task. This technique is based on an optimized 3D modeling allowing to reconstruct faces in different poses from a limited number of references (i.e. one image by class/person). Particularly, we propose to use an active shape model to detect a set of keypoints on the face necessary to deform our synthetic model with our optimized finite element method. Indeed, in order to improve our deformation, we propose a regularization by distances on graph. To perform the identification we use the VanderLugt correlator well know to effectively address this task. On the other hand we add a difference of Gaussian filtering step to highlight the edges and a description step based on the local binary patterns. The experiments are performed on the PHPID database enhanced with our 3D reconstructed faces of each person with an azimuth and an elevation ranging from -30° to +30°. The obtained results prove the robustness of our new method with 88.76% of good identification when the classic 2D approach (based on the VLC) obtains just 44.97%.
Identity modulates short-term memory for facial emotion.

PubMed

Galster, Murray; Kahana, Michael J; Wilson, Hugh R; Sekuler, Robert

2009-12-01

For some time, the relationship between processing of facial expression and facial identity has been in dispute. Using realistic synthetic faces, we reexamined this relationship for both perception and short-term memory. In Experiment 1, subjects tried to identify whether the emotional expression on a probe stimulus face matched the emotional expression on either of two remembered faces that they had just seen. The results showed that identity strongly influenced recognition short-term memory for emotional expression. In Experiment 2, subjects' similarity/dissimilarity judgments were transformed by multidimensional scaling (MDS) into a 2-D description of the faces' perceptual representations. Distances among stimuli in the MDS representation, which showed a strong linkage of emotional expression and facial identity, were good predictors of correct and false recognitions obtained previously in Experiment 1. The convergence of the results from Experiments 1 and 2 suggests that the overall structure and configuration of faces' perceptual representations may parallel their representation in short-term memory and that facial identity modulates the representation of facial emotion, both in perception and in memory. The stimuli from this study may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental.
The Ability of Visually Impaired Children to Read Expressions and Recognize Faces.

ERIC Educational Resources Information Center

Ellis, H. D.; And Others

1987-01-01

Seventeen visually impaired children, aged 7-11 years, were compared with sighted children on a test of facial recognition and a test of expression identification. The visually impaired children were less able to recognize faces successfully but showed no disadvantage in discerning facial expressions such as happiness, anger, surprise, or fear.…
View-Based Models of 3D Object Recognition and Class-Specific Invariance

DTIC Science & Technology

1994-04-01

underlie recognition of geon-like com- ponents (see Edelman, 1991 and Biederman , 1987 ). I(X -_ ta)II1y = (X - ta)TWTW(x -_ ta) (3) View-invariant features...Institute of Technology, 1993. neocortex. Biological Cybernetics, 1992. 14] I. Biederman . Recognition by components: a theory [20] B. Olshausen, C...Anderson, and D. Van Essen. A of human image understanding. Psychol. Review, neural model of visual attention and invariant pat- 94:115-147, 1987 . tern
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.
Putting the face in context: Body expressions impact facial emotion processing in human infants.

PubMed

Rajhans, Purva; Jessen, Sarah; Missana, Manuela; Grossmann, Tobias

2016-06-01

Body expressions exert strong contextual effects on facial emotion perception in adults. Specifically, conflicting body cues hamper the recognition of emotion from faces, as evident on both the behavioral and neural level. We examined the developmental origins of the neural processes involved in emotion perception across body and face in 8-month-old infants by measuring event-related brain potentials (ERPs). We primed infants with body postures (fearful, happy) that were followed by either congruent or incongruent facial expressions. Our results revealed that body expressions impact facial emotion processing and that incongruent body cues impair the neural discrimination of emotional facial expressions. Priming effects were associated with attentional and recognition memory processes, as reflected in a modulation of the Nc and Pc evoked at anterior electrodes. These findings demonstrate that 8-month-old infants possess neural mechanisms that allow for the integration of emotion across body and face, providing evidence for the early developmental emergence of context-sensitive facial emotion perception. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.
Fuzzy based finger vein recognition with rotation invariant feature matching

NASA Astrophysics Data System (ADS)

Ezhilmaran, D.; Joseph, Rose Bindu

2017-11-01

Finger vein recognition is a promising biometric with commercial applications which is explored widely in the recent years. In this paper, a finger vein recognition system is proposed using rotation invariant feature descriptors for matching after enhancing the finger vein images with an interval type-2 fuzzy method. SIFT features are extracted and matched using a matching score based on Euclidian distance. Rotation invariance of the proposed method is verified in the experiment and the results are compared with SURF matching and minutiae matching. It is seen that rotation invariance is verified and the poor quality issues are solved efficiently with the designed system of finger vein recognition during the analysis. The experiments underlines the robustness and reliability of the interval type-2 fuzzy enhancement and SIFT feature matching.
Recognition of facial, auditory, and bodily emotions in older adults.

PubMed

Ruffman, Ted; Halberstadt, Jamin; Murray, Janice

2009-11-01

Understanding older adults' social functioning difficulties requires insight into their recognition of emotion processing in voices and bodies, not just faces, the focus of most prior research. We examined 60 young and 61 older adults' recognition of basic emotions in facial, vocal, and bodily expressions, and when matching faces and bodies to voices, using 120 emotion items. Older adults were worse than young adults in 17 of 30 comparisons, with consistent difficulties in recognizing both positive (happy) and negative (angry and sad) vocal and bodily expressions. Nearly three quarters of older adults functioned at a level similar to the lowest one fourth of young adults, suggesting that age-related changes are common. In addition, we found that older adults' difficulty in matching emotions was not explained by difficulty on the component sources (i.e., faces or voices on their own), suggesting an additional problem of integration.
Training facial expression production in children on the autism spectrum.

PubMed

Gordon, Iris; Pierce, Matthew D; Bartlett, Marian S; Tanaka, James W

2014-10-01

Children with autism spectrum disorder (ASD) show deficits in their ability to produce facial expressions. In this study, a group of children with ASD and IQ-matched, typically developing (TD) children were trained to produce "happy" and "angry" expressions with the FaceMaze computer game. FaceMaze uses an automated computer recognition system that analyzes the child's facial expression in real time. Before and after playing the Angry and Happy versions of FaceMaze, children posed "happy" and "angry" expressions. Naïve raters judged the post-FaceMaze "happy" and "angry" expressions of the ASD group as higher in quality than their pre-FaceMaze productions. Moreover, the post-game expressions of the ASD group were rated as equal in quality as the expressions of the TD group.
Development of novel tasks for studying view-invariant object recognition in rodents: Sensitivity to scopolamine.

PubMed

Mitchnick, Krista A; Wideman, Cassidy E; Huff, Andrew E; Palmer, Daniel; McNaughton, Bruce L; Winters, Boyer D

2018-05-15

The capacity to recognize objects from different view-points or angles, referred to as view-invariance, is an essential process that humans engage in daily. Currently, the ability to investigate the neurobiological underpinnings of this phenomenon is limited, as few ethologically valid view-invariant object recognition tasks exist for rodents. Here, we report two complementary, novel view-invariant object recognition tasks in which rodents physically interact with three-dimensional objects. Prior to experimentation, rats and mice were given extensive experience with a set of 'pre-exposure' objects. In a variant of the spontaneous object recognition task, novelty preference for pre-exposed or new objects was assessed at various angles of rotation (45°, 90° or 180°); unlike control rodents, for whom the objects were novel, rats and mice tested with pre-exposed objects did not discriminate between rotated and un-rotated objects in the choice phase, indicating substantial view-invariant object recognition. Secondly, using automated operant touchscreen chambers, rats were tested on pre-exposed or novel objects in a pairwise discrimination task, where the rewarded stimulus (S+) was rotated (180°) once rats had reached acquisition criterion; rats tested with pre-exposed objects re-acquired the pairwise discrimination following S+ rotation more effectively than those tested with new objects. Systemic scopolamine impaired performance on both tasks, suggesting involvement of acetylcholine at muscarinic receptors in view-invariant object processing. These tasks present novel means of studying the behavioral and neural bases of view-invariant object recognition in rodents. Copyright © 2018 Elsevier B.V. All rights reserved.
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.
Using computerized games to teach face recognition skills to children with autism spectrum disorder: the Let's Face It! program.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin; Kaiser, Martha D; Schultz, Robert T

2010-08-01

An emerging body of evidence indicates that relative to typically developing children, children with autism are selectively impaired in their ability to recognize facial identity. A critical question is whether face recognition skills can be enhanced through a direct training intervention. In a randomized clinical trial, children diagnosed with autism spectrum disorder were pre-screened with a battery of subtests (the Let's Face It! Skills battery) examining face and object processing abilities. Participants who were significantly impaired in their face processing abilities were assigned to either a treatment or a waitlist group. Children in the treatment group (N = 42) received 20 hours of face training with the Let's Face It! (LFI!) computer-based intervention. The LFI! program is comprised of seven interactive computer games that target the specific face impairments associated with autism, including the recognition of identity across image changes in expression, viewpoint and features, analytic and holistic face processing strategies and attention to information in the eye region. Time 1 and Time 2 performance for the treatment and waitlist groups was assessed with the Let's Face It! Skills battery. The main finding was that relative to the control group (N = 37), children in the face training group demonstrated reliable improvements in their analytic recognition of mouth features and holistic recognition of a face based on its eyes features. These results indicate that a relatively short-term intervention program can produce measurable improvements in the face recognition skills of children with autism. As a treatment for face processing deficits, the Let's Face It! program has advantages of being cost-free, adaptable to the specific learning needs of the individual child and suitable for home and school applications.
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.
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.
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
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
View-invariant object recognition ability develops after discrimination, not mere exposure, at several viewing angles.

PubMed

Yamashita, Wakayo; Wang, Gang; Tanaka, Keiji

2010-01-01

One usually fails to recognize an unfamiliar object across changes in viewing angle when it has to be discriminated from similar distractor objects. Previous work has demonstrated that after long-term experience in discriminating among a set of objects seen from the same viewing angle, immediate recognition of the objects across 30-60 degrees changes in viewing angle becomes possible. The capability for view-invariant object recognition should develop during the within-viewing-angle discrimination, which includes two kinds of experience: seeing individual views and discriminating among the objects. The aim of the present study was to determine the relative contribution of each factor to the development of view-invariant object recognition capability. Monkeys were first extensively trained in a task that required view-invariant object recognition (Object task) with several sets of objects. The animals were then exposed to a new set of objects over 26 days in one of two preparatory tasks: one in which each object view was seen individually, and a second that required discrimination among the objects at each of four viewing angles. After the preparatory period, we measured the monkeys' ability to recognize the objects across changes in viewing angle, by introducing the object set to the Object task. Results indicated significant view-invariant recognition after the second but not first preparatory task. These results suggest that discrimination of objects from distractors at each of several viewing angles is required for the development of view-invariant recognition of the objects when the distractors are similar to the objects.
Emotion recognition in borderline personality disorder: effects of emotional information on negative bias.

PubMed

Fenske, Sabrina; Lis, Stefanie; Liebke, Lisa; Niedtfeld, Inga; Kirsch, Peter; Mier, Daniela

2015-01-01

Borderline Personality Disorder (BPD) is characterized by severe deficits in social interactions, which might be linked to deficits in emotion recognition. Research on emotion recognition abilities in BPD revealed heterogeneous results, ranging from deficits to heightened sensitivity. The most stable findings point to an impairment in the evaluation of neutral facial expressions as neutral, as well as to a negative bias in emotion recognition; that is the tendency to attribute negative emotions to neutral expressions, or in a broader sense to report a more negative emotion category than depicted. However, it remains unclear which contextual factors influence the occurrence of this negative bias. Previous studies suggest that priming by preceding emotional information and also constrained processing time might augment the emotion recognition deficit in BPD. To test these assumptions, 32 female BPD patients and 31 healthy females, matched for age and education, participated in an emotion recognition study, in which every facial expression was preceded by either a positive, neutral or negative scene. Furthermore, time constraints for processing were varied by presenting the facial expressions with short (100 ms) or long duration (up to 3000 ms) in two separate blocks. BPD patients showed a significant deficit in emotion recognition for neutral and positive facial expression, associated with a significant negative bias. In BPD patients, this emotion recognition deficit was differentially affected by preceding emotional information and time constraints, with a greater influence of emotional information during long face presentations and a greater influence of neutral information during short face presentations. Our results are in line with previous findings supporting the existence of a negative bias in emotion recognition in BPD patients, and provide further insights into biased social perceptions in BPD patients.
Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1994-01-01

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.
Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition.

PubMed

Tang, Xin; Feng, Guo-Can; Li, Xiao-Xin; Cai, Jia-Xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases.
Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition

PubMed Central

Tang, Xin; Feng, Guo-can; Li, Xiao-xin; Cai, Jia-xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases. PMID:26571112
Does cortisol modulate emotion recognition and empathy?

PubMed

Duesenberg, Moritz; Weber, Juliane; Schulze, Lars; Schaeuffele, Carmen; Roepke, Stefan; Hellmann-Regen, Julian; Otte, Christian; Wingenfeld, Katja

2016-04-01

Emotion recognition and empathy are important aspects in the interaction and understanding of other people's behaviors and feelings. The Human environment comprises of stressful situations that impact social interactions on a daily basis. Aim of the study was to examine the effects of the stress hormone cortisol on emotion recognition and empathy. In this placebo-controlled study, 40 healthy men and 40 healthy women (mean age 24.5 years) received either 10mg of hydrocortisone or placebo. We used the Multifaceted Empathy Test to measure emotional and cognitive empathy. Furthermore, we examined emotion recognition from facial expressions, which contained two emotions (anger and sadness) and two emotion intensities (40% and 80%). We did not find a main effect for treatment or sex on either empathy or emotion recognition but a sex × emotion interaction on emotion recognition. The main result was a four-way-interaction on emotion recognition including treatment, sex, emotion and task difficulty. At 40% task difficulty, women recognized angry faces better than men in the placebo condition. Furthermore, in the placebo condition, men recognized sadness better than anger. At 80% task difficulty, men and women performed equally well in recognizing sad faces but men performed worse compared to women with regard to angry faces. Apparently, our results did not support the hypothesis that increases in cortisol concentration alone influence empathy and emotion recognition in healthy young individuals. However, sex and task difficulty appear to be important variables in emotion recognition from facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.
The Perception of Facial Expressions and Stimulus Motion by Two- and Five-Month-Old Infants Using Holographic Stimuli.

ERIC Educational Resources Information Center

Nelson, Charles A.; Horowitz, Frances Degen

1983-01-01

Holograms of faces were used to study two- and five-month-old infants' discriminations of changes in facial expression and pose when the stimulus was seen to move or to remain stationary. While no evidence was found suggesting that infants preferred the moving face, evidence indicated that motion contrasts facilitate face recognition. (Author/RH)
Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

PubMed

Moghadam, Saeed Montazeri; Seyyedsalehi, Seyyed Ali

2018-05-31

Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthesize and interpolate new and imaginary data. This synthesis is possibly a simple model of imaginations in human brain where the components are expressed in a nonlinear low dimensional manifold. The current paper introduces a novel Dynamic Deep Bottleneck Neural Network to analyze and extract three main features of videos regarding the expression of emotions on the face. These main features are identity, emotion and expression intensity that are laid in three different sub-manifolds of one nonlinear general manifold. The proposed model enjoying the advantages of recurrent networks was used to analyze the sequence and dynamics of information in videos. It is noteworthy to mention that this model also has also the potential to synthesize new videos showing variations of one specific emotion on the face of unknown subjects. Experiments on discrimination and recognition ability of extracted components showed that the proposed model has an average of 97.77% accuracy in recognition of six prominent emotions (Fear, Surprise, Sadness, Anger, Disgust, and Happiness), and 78.17% accuracy in the recognition of intensity. The produced videos revealed variations from neutral to the apex of an emotion on the face of the unfamiliar test subject which is on average 0.8 similar to reference videos in the scale of the SSIM method. Copyright © 2018 Elsevier 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.

Facial affect recognition in early and late-stage schizophrenia patients.

PubMed

Romero-Ferreiro, María Verónica; Aguado, Luis; Rodriguez-Torresano, Javier; Palomo, Tomás; Rodriguez-Jimenez, Roberto; Pedreira-Massa, José Luis

2016-04-01

Prior studies have shown deficits in social cognition and emotion perception in first-episode psychosis (FEP) and multi-episode schizophrenia (MES) patients. These studies compared patients at different stages of the illness with only a single control group which differed in age from at least one clinical group. The present study provides new evidence of a differential pattern of deficit in facial affect recognition in FEP and MES patients using a double age-matched control design. Compared to their controls, FEP patients only showed impaired recognition of fearful faces (p=.007). In contrast to this, the MES patients showed a more generalized deficit compared to their age-matched controls, with impaired recognition of angry, sad and fearful faces (ps<.01) and an increased misattribution of emotional meaning to neutral faces. PANSS scores of FEP patients on Depressed factor correlated positively with the accuracy to recognize fearful expressions (r=.473). For the MES group fear recognition correlated positively with negative PANSS factor (r=.498) and recognition of sad and neutral expressions was inversely correlated with disorganized PANSS factor (r=-.461 and r=-.541, respectively). These results provide evidence that a generalized impairment of affect recognition is observed in advanced-stage patients and is not characteristic of the early stages of schizophrenia. Moreover, the finding that anomalous attribution of emotional meaning to neutral faces is observed only in MES patients suggests that an increased attribution of salience to social stimuli is a characteristic of social cognition in advanced stages of the disorder. Copyright © 2016 Elsevier B.V. All rights reserved.
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.
Body Emotion Recognition Disproportionately Depends on Vertical Orientations during Childhood

ERIC Educational Resources Information Center

Balas, Benjamin; Auen, Amanda; Saville, Alyson; Schmidt, Jamie

2018-01-01

Children's ability to recognize emotional expressions from faces and bodies develops during childhood. However, the low-level features that support accurate body emotion recognition during development have not been well characterized. This is in marked contrast to facial emotion recognition, which is known to depend upon specific spatial frequency…
Face recognition algorithm based on Gabor wavelet and locality preserving projections

NASA Astrophysics Data System (ADS)

Liu, Xiaojie; Shen, Lin; Fan, Honghui

2017-07-01

In order to solve the effects of illumination changes and differences of personal features on the face recognition rate, this paper presents a new face recognition algorithm based on Gabor wavelet and Locality Preserving Projections (LPP). The problem of the Gabor filter banks with high dimensions was solved effectively, and also the shortcoming of the LPP on the light illumination changes was overcome. Firstly, the features of global image information were achieved, which used the good spatial locality and orientation selectivity of Gabor wavelet filters. Then the dimensions were reduced by utilizing the LPP, which well-preserved the local information of the image. The experimental results shown that this algorithm can effectively extract the features relating to facial expressions, attitude and other information. Besides, it can reduce influence of the illumination changes and the differences in personal features effectively, which improves the face recognition rate to 99.2%.
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.
Facial emotion expression recognition by children at familial risk for depression: High risk boys are oversensitive to sadness

PubMed Central

Lopez-Duran, Nestor L.; Kuhlman, Kate R.; George, Charles; Kovacs, Maria

2012-01-01

In the present study we examined perceptual sensitivity to facial expressions of sadness among children at familial-risk for depression (N = 64) and low-risk peers (N = 40) between the ages 7 and 13(Mage = 9.51; SD = 2.27). Participants were presented with pictures of facial expressions that varied in emotional intensity from neutral to full-intensity sadness or anger (i.e., emotion recognition), or pictures of faces morphing from anger to sadness (emotion discrimination). After each picture was presented, children indicated whether the face showed a specific emotion (i.e., sadness, anger) or no emotion at all (neutral). In the emotion recognition task, boys (but not girls) at familial-risk for depression identified sadness at significantly lower levels of emotional intensity than did their low-risk peers. The high and low-risk groups did not differ with regard to identification of anger. In the emotion discrimination task, both groups displayed over-identification of sadness in ambiguous mixed faces but high-risk youth were less likely to show this labeling bias than their peers. Our findings are consistent with the hypothesis that enhanced perceptual sensitivity to subtle traces of sadness in facial expressions may be a potential mechanism of risk among boys at familial-risk for depression. This enhanced perceptual sensitivity does not appear to be due to biases in the labeling of ambiguous faces. PMID:23106941
Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.
Facial Expression Recognition with Fusion Features Extracted from Salient Facial Areas.

PubMed

Liu, Yanpeng; Li, Yibin; Ma, Xin; Song, Rui

2017-03-29

In the pattern recognition domain, deep architectures are currently widely used and they have achieved fine results. However, these deep architectures make particular demands, especially in terms of their requirement for big datasets and GPU. Aiming to gain better results without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size; therefore, it can extracts more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features' dimensions are reduced by Principal Component Analysis (PCA) and we apply several classifiers to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames compared with neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. As a result, the salient areas found from different subjects are the same size. In addition, the gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.
Testing Measurement Invariance across Groups of Children with and without Attention-Deficit/ Hyperactivity Disorder: Applications for Word Recognition and Spelling Tasks

PubMed Central

Lúcio, Patrícia S.; Salum, Giovanni; Swardfager, Walter; Mari, Jair de Jesus; Pan, Pedro M.; Bressan, Rodrigo A.; Gadelha, Ary; Rohde, Luis A.; Cogo-Moreira, Hugo

2017-01-01

Although studies have consistently demonstrated that children with attention-deficit/hyperactivity disorder (ADHD) perform significantly lower than controls on word recognition and spelling tests, such studies rely on the assumption that those groups are comparable in these measures. This study investigates comparability of word recognition and spelling tests based on diagnostic status for ADHD through measurement invariance methods. The participants (n = 1,935; 47% female; 11% ADHD) were children aged 6–15 with normal IQ (≥70). Measurement invariance was investigated through Confirmatory Factor Analysis and Multiple Indicators Multiple Causes models. Measurement invariance was attested in both methods, demonstrating the direct comparability of the groups. Children with ADHD were 0.51 SD lower in word recognition and 0.33 SD lower in spelling tests than controls. Results suggest that differences in performance on word recognition and spelling tests are related to true mean differences based on ADHD diagnostic status. Implications for clinical practice and research are discussed. PMID:29118733
Testing Measurement Invariance across Groups of Children with and without Attention-Deficit/ Hyperactivity Disorder: Applications for Word Recognition and Spelling Tasks.

PubMed

Lúcio, Patrícia S; Salum, Giovanni; Swardfager, Walter; Mari, Jair de Jesus; Pan, Pedro M; Bressan, Rodrigo A; Gadelha, Ary; Rohde, Luis A; Cogo-Moreira, Hugo

2017-01-01

Although studies have consistently demonstrated that children with attention-deficit/hyperactivity disorder (ADHD) perform significantly lower than controls on word recognition and spelling tests, such studies rely on the assumption that those groups are comparable in these measures. This study investigates comparability of word recognition and spelling tests based on diagnostic status for ADHD through measurement invariance methods. The participants ( n = 1,935; 47% female; 11% ADHD) were children aged 6-15 with normal IQ (≥70). Measurement invariance was investigated through Confirmatory Factor Analysis and Multiple Indicators Multiple Causes models. Measurement invariance was attested in both methods, demonstrating the direct comparability of the groups. Children with ADHD were 0.51 SD lower in word recognition and 0.33 SD lower in spelling tests than controls. Results suggest that differences in performance on word recognition and spelling tests are related to true mean differences based on ADHD diagnostic status. Implications for clinical practice and research are discussed.
Recognition memory for emotional and neutral faces: an event-related potential study.

PubMed

Johansson, Mikael; Mecklinger, Axel; Treese, Anne-Cécile

2004-12-01

This study examined emotional influences on the hypothesized event-related potential (ERP) correlates of familiarity and recollection (Experiment 1) and the states of awareness (Experiment 2) accompanying recognition memory for faces differing in facial affect. Participants made gender judgments to positive, negative, and neutral faces at study and were in the test phase instructed to discriminate between studied and nonstudied faces. Whereas old-new discrimination was unaffected by facial expression, negative faces were recollected to a greater extent than both positive and neutral faces as reflected in the parietal ERP old-new effect and in the proportion of remember judgments. Moreover, emotion-specific modulations were observed in frontally recorded ERPs elicited by correctly rejected new faces that concurred with a more liberal response criterion for emotional as compared to neutral faces. Taken together, the results are consistent with the view that processes promoting recollection are facilitated for negative events and that emotion may affect recognition performance by influencing criterion setting mediated by the prefrontal cortex.
Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.
Can We Distinguish Emotions from Faces? Investigation of Implicit and Explicit Processes of Peak Facial Expressions.

PubMed

Xiao, Ruiqi; Li, Xianchun; Li, Lin; Wang, Yanmei

2016-01-01

Most previous studies on facial expression recognition have focused on the moderate emotions; to date, few studies have been conducted to investigate the explicit and implicit processes of peak emotions. In the current study, we used transiently peak intense expression images of athletes at the winning or losing point in competition as materials, and investigated the diagnosability of peak facial expressions at both implicit and explicit levels. In Experiment 1, participants were instructed to evaluate isolated faces, isolated bodies, and the face-body compounds, and eye-tracking movement was recorded. The results revealed that the isolated body and face-body congruent images were better recognized than isolated face and face-body incongruent images, indicating that the emotional information conveyed by facial cues was ambiguous, and the body cues influenced facial emotion recognition. Furthermore, eye movement records showed that the participants displayed distinct gaze patterns for the congruent and incongruent compounds. In Experiment 2A, the subliminal affective priming task was used, with faces as primes and bodies as targets, to investigate the unconscious emotion perception of peak facial expressions. The results showed that winning face prime facilitated reaction to winning body target, whereas losing face prime inhibited reaction to winning body target, suggesting that peak facial expressions could be perceived at the implicit level. In general, the results indicate that peak facial expressions cannot be consciously recognized but can be perceived at the unconscious level. In Experiment 2B, revised subliminal affective priming task and a strict awareness test were used to examine the validity of unconscious perception of peak facial expressions found in Experiment 2A. Results of Experiment 2B showed that reaction time to both winning body targets and losing body targets was influenced by the invisibly peak facial expression primes, which indicated the unconscious perception of peak facial expressions.
Can We Distinguish Emotions from Faces? Investigation of Implicit and Explicit Processes of Peak Facial Expressions

PubMed Central

Xiao, Ruiqi; Li, Xianchun; Li, Lin; Wang, Yanmei

2016-01-01

Most previous studies on facial expression recognition have focused on the moderate emotions; to date, few studies have been conducted to investigate the explicit and implicit processes of peak emotions. In the current study, we used transiently peak intense expression images of athletes at the winning or losing point in competition as materials, and investigated the diagnosability of peak facial expressions at both implicit and explicit levels. In Experiment 1, participants were instructed to evaluate isolated faces, isolated bodies, and the face-body compounds, and eye-tracking movement was recorded. The results revealed that the isolated body and face-body congruent images were better recognized than isolated face and face-body incongruent images, indicating that the emotional information conveyed by facial cues was ambiguous, and the body cues influenced facial emotion recognition. Furthermore, eye movement records showed that the participants displayed distinct gaze patterns for the congruent and incongruent compounds. In Experiment 2A, the subliminal affective priming task was used, with faces as primes and bodies as targets, to investigate the unconscious emotion perception of peak facial expressions. The results showed that winning face prime facilitated reaction to winning body target, whereas losing face prime inhibited reaction to winning body target, suggesting that peak facial expressions could be perceived at the implicit level. In general, the results indicate that peak facial expressions cannot be consciously recognized but can be perceived at the unconscious level. In Experiment 2B, revised subliminal affective priming task and a strict awareness test were used to examine the validity of unconscious perception of peak facial expressions found in Experiment 2A. Results of Experiment 2B showed that reaction time to both winning body targets and losing body targets was influenced by the invisibly peak facial expression primes, which indicated the unconscious perception of peak facial expressions. PMID:27630604
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.
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.
Visual body recognition in a prosopagnosic patient.

PubMed

Moro, V; Pernigo, S; Avesani, R; Bulgarelli, C; Urgesi, C; Candidi, M; Aglioti, S M

2012-01-01

Conspicuous deficits in face recognition characterize prosopagnosia. Information on whether agnosic deficits may extend to non-facial body parts is lacking. Here we report the neuropsychological description of FM, a patient affected by a complete deficit in face recognition in the presence of mild clinical signs of visual object agnosia. His deficit involves both overt and covert recognition of faces (i.e. recognition of familiar faces, but also categorization of faces for gender or age) as well as the visual mental imagery of faces. By means of a series of matching-to-sample tasks we investigated: (i) a possible association between prosopagnosia and disorders in visual body perception; (ii) the effect of the emotional content of stimuli on the visual discrimination of faces, bodies and objects; (iii) the existence of a dissociation between identity recognition and the emotional discrimination of faces and bodies. Our results document, for the first time, the co-occurrence of body agnosia, i.e. the visual inability to discriminate body forms and body actions, and prosopagnosia. Moreover, the results show better performance in the discrimination of emotional face and body expressions with respect to body identity and neutral actions. Since FM's lesions involve bilateral fusiform areas, it is unlikely that the amygdala-temporal projections explain the relative sparing of emotion discrimination performance. Indeed, the emotional content of the stimuli did not improve the discrimination of their identity. The results hint at the existence of two segregated brain networks involved in identity and emotional discrimination that are at least partially shared by face and body processing. Copyright © 2011 Elsevier Ltd. All rights reserved.
Recent progress in invariant pattern recognition

NASA Astrophysics Data System (ADS)

Arsenault, Henri H.; Chang, S.; Gagne, Philippe; Gualdron Gonzalez, Oscar

1996-12-01

We present some recent results in invariant pattern recognition, including methods that are invariant under two or more distortions of position, orientation and scale. There are now a few methods that yield good results under changes of both rotation and scale. Some new methods are introduced. These include locally adaptive nonlinear matched filters, scale-adapted wavelet transforms and invariant filters for disjoint noise. Methods using neural networks will also be discussed, including an optical method that allows simultaneous classification of multiple targets.
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.

The Tromso Infant Faces Database (TIF): Development, Validation and Application to Assess Parenting Experience on Clarity and Intensity Ratings.

PubMed

Maack, Jana K; Bohne, Agnes; Nordahl, Dag; Livsdatter, Lina; Lindahl, Åsne A W; Øvervoll, Morten; Wang, Catharina E A; Pfuhl, Gerit

2017-01-01

Newborns and infants are highly depending on successfully communicating their needs; e.g., through crying and facial expressions. Although there is a growing interest in the mechanisms of and possible influences on the recognition of facial expressions in infants, heretofore there exists no validated database of emotional infant faces. In the present article we introduce a standardized and freely available face database containing Caucasian infant face images from 18 infants 4 to 12 months old. The development and validation of the Tromsø Infant Faces (TIF) database is presented in Study 1. Over 700 adults categorized the photographs by seven emotion categories (happy, sad, disgusted, angry, afraid, surprised, neutral) and rated intensity, clarity and their valance. In order to examine the relevance of TIF, we then present its first application in Study 2, investigating differences in emotion recognition across different stages of parenthood. We found a small gender effect in terms of women giving higher intensity and clarity ratings than men. Moreover, parents of young children rated the images as clearer than all the other groups, and parents rated "neutral" expressions as more clearly and more intense. Our results suggest that caretaking experience provides an implicit advantage in the processing of emotional expressions in infant faces, especially for the more difficult, ambiguous expressions.
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.
Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.
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.
On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.

PubMed

Shao, Zhanpeng; Li, Youfu

2016-02-01

Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.
Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

NASA Astrophysics Data System (ADS)

Chen, Cunjian; Ross, Arun

2013-05-01

Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.
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.
Emotion Recognition in Animated Compared to Human Stimuli in Adolescents with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Brosnan, Mark; Johnson, Hilary; Grawmeyer, Beate; Chapman, Emma; Benton, Laura

2015-01-01

There is equivocal evidence as to whether there is a deficit in recognising emotional expressions in Autism spectrum disorder (ASD). This study compared emotion recognition in ASD in three types of emotion expression media (still image, dynamic image, auditory) across human stimuli (e.g. photo of a human face) and animated stimuli (e.g. cartoon…
Generating virtual training samples for sparse representation of face images and face recognition

NASA Astrophysics Data System (ADS)

Du, Yong; Wang, Yu

2016-03-01

There are many challenges in face recognition. In real-world scenes, images of the same face vary with changing illuminations, different expressions and poses, multiform ornaments, or even altered mental status. Limited available training samples cannot convey these possible changes in the training phase sufficiently, and this has become one of the restrictions to improve the face recognition accuracy. In this article, we view the multiplication of two images of the face as a virtual face image to expand the training set and devise a representation-based method to perform face recognition. The generated virtual samples really reflect some possible appearance and pose variations of the face. By multiplying a training sample with another sample from the same subject, we can strengthen the facial contour feature and greatly suppress the noise. Thus, more human essential information is retained. Also, uncertainty of the training data is simultaneously reduced with the increase of the training samples, which is beneficial for the training phase. The devised representation-based classifier uses both the original and new generated samples to perform the classification. In the classification phase, we first determine K nearest training samples for the current test sample by calculating the Euclidean distances between the test sample and training samples. Then, a linear combination of these selected training samples is used to represent the test sample, and the representation result is used to classify the test sample. The experimental results show that the proposed method outperforms some state-of-the-art face recognition methods.
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.
Selective attention to emotional cues and emotion recognition in healthy subjects: the role of mineralocorticoid receptor stimulation.

PubMed

Schultebraucks, Katharina; Deuter, Christian E; Duesenberg, Moritz; Schulze, Lars; Hellmann-Regen, Julian; Domke, Antonia; Lockenvitz, Lisa; Kuehl, Linn K; Otte, Christian; Wingenfeld, Katja

2016-09-01

Selective attention toward emotional cues and emotion recognition of facial expressions are important aspects of social cognition. Stress modulates social cognition through cortisol, which acts on glucocorticoid (GR) and mineralocorticoid receptors (MR) in the brain. We examined the role of MR activation on attentional bias toward emotional cues and on emotion recognition. We included 40 healthy young women and 40 healthy young men (mean age 23.9 ± 3.3), who either received 0.4 mg of the MR agonist fludrocortisone or placebo. A dot-probe paradigm was used to test for attentional biases toward emotional cues (happy and sad faces). Moreover, we used a facial emotion recognition task to investigate the ability to recognize emotional valence (anger and sadness) from facial expression in four graded categories of emotional intensity (20, 30, 40, and 80 %). In the emotional dot-probe task, we found a main effect of treatment and a treatment × valence interaction. Post hoc analyses revealed an attentional bias away from sad faces after placebo intake and a shift in selective attention toward sad faces compared to placebo. We found no attentional bias toward happy faces after fludrocortisone or placebo intake. In the facial emotion recognition task, there was no main effect of treatment. MR stimulation seems to be important in modulating quick, automatic emotional processing, i.e., a shift in selective attention toward negative emotional cues. Our results confirm and extend previous findings of MR function. However, we did not find an effect of MR stimulation on emotion recognition.
2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.
Calculus of nonrigid surfaces for geometry and texture manipulation.

PubMed

Bronstein, Alexander; Bronstein, Michael; Kimmel, Ron

2007-01-01

We present a geometric framework for automatically finding intrinsic correspondence between three-dimensional nonrigid objects. We model object deformation as near isometries and find the correspondence as the minimum-distortion mapping. A generalization of multidimensional scaling is used as the numerical core of our approach. As a result, we obtain the possibility to manipulate the extrinsic geometry and the texture of the objects as vectors in a linear space. We demonstrate our method on the problems of expression-invariant texture mapping onto an animated three-dimensional face, expression exaggeration, morphing between faces, and virtual body painting.
Facing mixed emotions: Analytic and holistic perception of facial emotion expressions engages separate brain networks.

PubMed

Meaux, Emilie; Vuilleumier, Patrik

2016-11-01

The ability to decode facial emotions is of primary importance for human social interactions; yet, it is still debated how we analyze faces to determine their expression. Here we compared the processing of emotional face expressions through holistic integration and/or local analysis of visual features, and determined which brain systems mediate these distinct processes. Behavioral, physiological, and brain responses to happy and angry faces were assessed by presenting congruent global configurations of expressions (e.g., happy top+happy bottom), incongruent composite configurations (e.g., angry top+happy bottom), and isolated features (e.g. happy top only). Top and bottom parts were always from the same individual. Twenty-six healthy volunteers were scanned using fMRI while they classified the expression in either the top or the bottom face part but ignored information in the other non-target part. Results indicate that the recognition of happy and anger expressions is neither strictly holistic nor analytic Both routes were involved, but with a different role for analytic and holistic information depending on the emotion type, and different weights of local features between happy and anger expressions. Dissociable neural pathways were engaged depending on emotional face configurations. In particular, regions within the face processing network differed in their sensitivity to holistic expression information, which predominantly activated fusiform, inferior occipital areas and amygdala when internal features were congruent (i.e. template matching), whereas more local analysis of independent features preferentially engaged STS and prefrontal areas (IFG/OFC) in the context of full face configurations, but early visual areas and pulvinar when seen in isolated parts. Collectively, these findings suggest that facial emotion recognition recruits separate, but interactive dorsal and ventral routes within the face processing networks, whose engagement may be shaped by reciprocal interactions and modulated by task demands. Copyright © 2016 Elsevier Inc. All rights reserved.
Degraded Impairment of Emotion Recognition in Parkinson's Disease Extends from Negative to Positive Emotions.

PubMed

Lin, Chia-Yao; Tien, Yi-Min; Huang, Jong-Tsun; Tsai, Chon-Haw; Hsu, Li-Chuan

2016-01-01

Because of dopaminergic neurodegeneration, patients with Parkinson's disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment 1 and identify gender in Experiment 2. In Experiment 1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment 2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment 2 as alternative explanations for the results of Experiment 1. We concluded that patients' ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions.
Degraded Impairment of Emotion Recognition in Parkinson's Disease Extends from Negative to Positive Emotions

PubMed Central

Tien, Yi-Min; Huang, Jong-Tsun

2016-01-01

Because of dopaminergic neurodegeneration, patients with Parkinson's disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment 1 and identify gender in Experiment 2. In Experiment 1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment 2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment 2 as alternative explanations for the results of Experiment 1. We concluded that patients' ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions. PMID:27555668
Foveation: an alternative method to simultaneously preserve privacy and information in face images

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

PubMed

Wickline, Virginia B; Bailey, Wendy; Nowicki, Stephen

2009-03-01

The authors explored whether there were in-group advantages in emotion recognition of faces and voices by culture or geographic region. Participants were 72 African American students (33 men, 39 women), 102 European American students (30 men, 72 women), 30 African international students (16 men, 14 women), and 30 European international students (15 men, 15 women). The participants determined emotions in African American and European American faces and voices. Results showed an in-group advantage-sometimes by culture, less often by race-in recognizing facial and vocal emotional expressions. African international students were generally less accurate at interpreting American nonverbal stimuli than were European American, African American, and European international peers. Results suggest that, although partly universal, emotional expressions have subtle differences across cultures that persons must learn.
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
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.

Feedforward object-vision models only tolerate small image variations compared to human

PubMed Central

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

2014-01-01

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986
How do typically developing deaf children and deaf children with autism spectrum disorder use the face when comprehending emotional facial expressions in British sign language?

PubMed

Denmark, Tanya; Atkinson, Joanna; Campbell, Ruth; Swettenham, John

2014-10-01

Facial expressions in sign language carry a variety of communicative features. While emotion can modulate a spoken utterance through changes in intonation, duration and intensity, in sign language specific facial expressions presented concurrently with a manual sign perform this function. When deaf adult signers cannot see facial features, their ability to judge emotion in a signed utterance is impaired (Reilly et al. in Sign Lang Stud 75:113-118, 1992). We examined the role of the face in the comprehension of emotion in sign language in a group of typically developing (TD) deaf children and in a group of deaf children with autism spectrum disorder (ASD). We replicated Reilly et al.'s (Sign Lang Stud 75:113-118, 1992) adult results in the TD deaf signing children, confirming the importance of the face in understanding emotion in sign language. The ASD group performed more poorly on the emotion recognition task than the TD children. The deaf children with ASD showed a deficit in emotion recognition during sign language processing analogous to the deficit in vocal emotion recognition that has been observed in hearing children with ASD.
Characterization and recognition of mixed emotional expressions in thermal face image

NASA Astrophysics Data System (ADS)

Saha, Priya; Bhattacharjee, Debotosh; De, Barin K.; Nasipuri, Mita

2016-05-01

Facial expressions in infrared imaging have been introduced to solve the problem of illumination, which is an integral constituent of visual imagery. The paper investigates facial skin temperature distribution on mixed thermal facial expressions of our created face database where six are basic expressions and rest 12 are a mixture of those basic expressions. Temperature analysis has been performed on three facial regions of interest (ROIs); periorbital, supraorbital and mouth. Temperature variability of the ROIs in different expressions has been measured using statistical parameters. The temperature variation measurement in ROIs of a particular expression corresponds to a vector, which is later used in recognition of mixed facial expressions. Investigations show that facial features in mixed facial expressions can be characterized by positive emotion induced facial features and negative emotion induced facial features. Supraorbital is a useful facial region that can differentiate basic expressions from mixed expressions. Analysis and interpretation of mixed expressions have been conducted with the help of box and whisker plot. Facial region containing mixture of two expressions is generally less temperature inducing than corresponding facial region containing basic expressions.
Rapid communication: Global-local processing affects recognition of distractor emotional faces.

PubMed

Srinivasan, Narayanan; Gupta, Rashmi

2011-03-01

Recent studies have shown links between happy faces and global, distributed attention as well as sad faces to local, focused attention. Emotions have been shown to affect global-local processing. Given that studies on emotion-cognition interactions have not explored the effect of perceptual processing at different spatial scales on processing stimuli with emotional content, the present study investigated the link between perceptual focus and emotional processing. The study investigated the effects of global-local processing on the recognition of distractor faces with emotional expressions. Participants performed a digit discrimination task with digits at either the global level or the local level presented against a distractor face (happy or sad) as background. The results showed that global processing associated with broad scope of attention facilitates recognition of happy faces, and local processing associated with narrow scope of attention facilitates recognition of sad faces. The novel results of the study provide conclusive evidence for emotion-cognition interactions by demonstrating the effect of perceptual processing on emotional faces. The results along with earlier complementary results on the effect of emotion on global-local processing support a reciprocal relationship between emotional processing and global-local processing. Distractor processing with emotional information also has implications for theories of selective attention.
Recognition of facial expressions is moderated by Islamic cues.

PubMed

Kret, Mariska E; Fischer, Agneta H

2018-05-01

Recognising emotions from faces that are partly covered is more difficult than from fully visible faces. The focus of the present study is on the role of an Islamic versus non-Islamic context, i.e. Islamic versus non-Islamic headdress in perceiving emotions. We report an experiment that investigates whether briefly presented (40 ms) facial expressions of anger, fear, happiness and sadness are perceived differently when covered by a niqāb or turban, compared to a cap and shawl. In addition, we examined whether oxytocin, a neuropeptide regulating affection, bonding and cooperation between ingroup members and fostering outgroup vigilance and derogation, would differentially impact on emotion recognition from wearers of Islamic versus non-Islamic headdresses. The results first of all show that the recognition of happiness was more accurate when the face was covered by a Western compared to Islamic headdress. Second, participants more often incorrectly assigned sadness to a face covered by an Islamic headdress compared to a cap and shawl. Third, when correctly recognising sadness, they did so faster when the face was covered by an Islamic compared to Western headdress. Fourth, oxytocin did not modulate any of these effects. Implications for theorising about the role of group membership on emotion perception are discussed.
Hierarchical Encoding of Social Cues in Primate Inferior Temporal Cortex

PubMed Central

Morin, Elyse L.; Hadj-Bouziane, Fadila; Stokes, Mark; Ungerleider, Leslie G.; Bell, Andrew H.

2015-01-01

Faces convey information about identity and emotional state, both of which are important for our social interactions. Models of face processing propose that changeable versus invariant aspects of a face, specifically facial expression/gaze direction versus facial identity, are coded by distinct neural pathways and yet neurophysiological data supporting this separation are incomplete. We recorded activity from neurons along the inferior bank of the superior temporal sulcus (STS), while monkeys viewed images of conspecific faces and non-face control stimuli. Eight monkey identities were used, each presented with 3 different facial expressions (neutral, fear grin, and threat). All facial expressions were displayed with both a direct and averted gaze. In the posterior STS, we found that about one-quarter of face-responsive neurons are sensitive to social cues, the majority of which being sensitive to only one of these cues. In contrast, in anterior STS, not only did the proportion of neurons sensitive to social cues increase, but so too did the proportion of neurons sensitive to conjunctions of identity with either gaze direction or expression. These data support a convergence of signals related to faces as one moves anteriorly along the inferior bank of the STS, which forms a fundamental part of the face-processing network. PMID:24836688
Identity-expression interaction in face perception: sex, visual field, and psychophysical factors.

PubMed

Godard, Ornella; Baudouin, Jean-Yves; Bonnet, Philippe; Fiori, Nicole

2013-01-01

We investigated the psychophysical factors underlying the identity-emotion interaction in face perception. Visual field and sex were also taken into account. Participants had to judge whether a probe face, presented in either the left or the right visual field, and a central target face belonging to same person while emotional expression varied (Experiment 1) or to judge whether probe and target faces expressed the same emotion while identity was manipulated (Experiment 2). For accuracy we replicated the mutual facilitation effect between identity and emotion; no sex or hemispheric differences were found. Processing speed measurements, however, showed a lesser degree of interference in women than in men, especially for matching identity when faces expressed different emotions after a left visual presentation probe face. Psychophysical indices can be used to determine whether these effects are perceptual (A') or instead arise at a post-perceptual decision-making stage (B"). The influence of identity on the processing of facial emotion seems to be due to perceptual factors, whereas the influence of emotion changes on identity processing seems to be related to decisional factors. In addition, men seem to be more "conservative" after a LVF/RH probe-face presentation when processing identity. Women seem to benefit from better abilities to extract facial invariant aspects relative to identity.
Impact of severity of drug use on discrete emotions recognition in polysubstance abusers.

PubMed

Fernández-Serrano, María José; Lozano, Oscar; Pérez-García, Miguel; Verdejo-García, Antonio

2010-06-01

Neuropsychological studies support the association between severity of drug intake and alterations in specific cognitive domains and neural systems, but there is disproportionately less research on the neuropsychology of emotional alterations associated with addiction. One of the key aspects of adaptive emotional functioning potentially relevant to addiction progression and treatment is the ability to recognize basic emotions in the faces of others. Therefore, the aims of this study were: (i) to examine facial emotion recognition in abstinent polysubstance abusers, and (ii) to explore the association between patterns of quantity and duration of use of several drugs co-abused (including alcohol, cannabis, cocaine, heroin and MDMA) and the ability to identify discrete facial emotional expressions portraying basic emotions. We compared accuracy of emotion recognition of facial expressions portraying six basic emotions (measured with the Ekman Faces Test) between polysubstance abusers (PSA, n=65) and non-drug using comparison individuals (NDCI, n=30), and used regression models to explore the association between quantity and duration of use of the different drugs co-abused and indices of recognition of each of the six emotions, while controlling for relevant socio-demographic and affect-related confounders. Results showed: (i) that PSA had significantly poorer recognition than NDCI for facial expressions of anger, disgust, fear and sadness; (ii) that measures of quantity and duration of drugs used significantly predicted poorer discrete emotions recognition: quantity of cocaine use predicted poorer anger recognition, and duration of cocaine use predicted both poorer anger and fear recognition. Severity of cocaine use also significantly predicted overall recognition accuracy. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.
Identifying and detecting facial expressions of emotion in peripheral vision.

PubMed

Smith, Fraser W; Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus.
Identifying and detecting facial expressions of emotion in peripheral vision

PubMed Central

Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus. PMID:29847562
Identifying differences in biased affective information processing in major depression.

PubMed

Gollan, Jackie K; Pane, Heather T; McCloskey, Michael S; Coccaro, Emil F

2008-05-30

This study investigates the extent to which participants with major depression differ from healthy comparison participants in the irregularities in affective information processing, characterized by deficits in facial expression recognition, intensity categorization, and reaction time to identifying emotionally salient and neutral information. Data on diagnoses, symptom severity, and affective information processing using a facial recognition task were collected from 66 participants, male and female between ages 18 and 54 years, grouped by major depressive disorder (N=37) or healthy non-psychiatric (N=29) status. Findings from MANCOVAs revealed that major depression was associated with a significantly longer reaction time to sad facial expressions compared with healthy status. Also, depressed participants demonstrated a negative bias towards interpreting neutral facial expressions as sad significantly more often than healthy participants. In turn, healthy participants interpreted neutral faces as happy significantly more often than depressed participants. No group differences were observed for facial expression recognition and intensity categorization. The observed effects suggest that depression has significant effects on the perception of the intensity of negative affective stimuli, delayed speed of processing sad affective information, and biases towards interpreting neutral faces as sad.
Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.
Repeated short presentations of morphed facial expressions change recognition and evaluation of facial expressions.

PubMed

Moriya, Jun; Tanno, Yoshihiko; Sugiura, Yoshinori

2013-11-01

This study investigated whether sensitivity to and evaluation of facial expressions varied with repeated exposure to non-prototypical facial expressions for a short presentation time. A morphed facial expression was presented for 500 ms repeatedly, and participants were required to indicate whether each facial expression was happy or angry. We manipulated the distribution of presentations of the morphed facial expressions for each facial stimulus. Some of the individuals depicted in the facial stimuli expressed anger frequently (i.e., anger-prone individuals), while the others expressed happiness frequently (i.e., happiness-prone individuals). After being exposed to the faces of anger-prone individuals, the participants became less sensitive to those individuals' angry faces. Further, after being exposed to the faces of happiness-prone individuals, the participants became less sensitive to those individuals' happy faces. We also found a relative increase in the social desirability of happiness-prone individuals after exposure to the facial stimuli.
Facial race and sex cues have a comparable influence on emotion recognition in Chinese and Australian participants.

PubMed

Craig, Belinda M; Zhang, Jing; Lipp, Ottmar V

2017-10-01

The magnitude of the happy categorisation advantage, the faster recognition of happiness than negative expressions, is influenced by facial race and sex cues. Previous studies have investigated these relationships using racial outgroups stereotypically associated with physical threat in predominantly Caucasian samples. To determine whether these influences generalise to stimuli representing other ethnic groups and to participants of different ethnicities, Caucasian Australian (Experiments 1 and 2) and Chinese participants (Experiment 2) categorised happy and angry expressions displayed on own-race male faces presented with emotional other-race male, own-race female, and other-race female faces in separate tasks. The influence of social category cues on the happy categorisation advantage was similar in the Australian and Chinese samples. In both samples, the happy categorisation advantage was present for own-race male faces when they were encountered with other-race male faces but reduced when own-race male faces were categorised along with female faces. The happy categorisation advantage was present for own-race and other-race female faces when they were encountered with own-race male faces in both samples. Results suggest similarity in the influence of social category cues on emotion categorisation.
Image object recognition based on the Zernike moment and neural networks

NASA Astrophysics Data System (ADS)

Wan, Jianwei; Wang, Ling; Huang, Fukan; Zhou, Liangzhu

1998-03-01

This paper first give a comprehensive discussion about the concept of artificial neural network its research methods and the relations with information processing. On the basis of such a discussion, we expound the mathematical similarity of artificial neural network and information processing. Then, the paper presents a new method of image recognition based on invariant features and neural network by using image Zernike transform. The method not only has the invariant properties for rotation, shift and scale of image object, but also has good fault tolerance and robustness. Meanwhile, it is also compared with statistical classifier and invariant moments recognition method.
Wavelet filtered shifted phase-encoded joint transform correlation for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.
Face-space: A unifying concept in face recognition research.

PubMed

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

2016-10-01

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

NASA Astrophysics Data System (ADS)

Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

2015-11-01

We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.
Interference among the Processing of Facial Emotion, Face Race, and Face Gender.

PubMed

Li, Yongna; Tse, Chi-Shing

2016-01-01

People can process multiple dimensions of facial properties simultaneously. Facial processing models are based on the processing of facial properties. The current study examined the processing of facial emotion, face race, and face gender using categorization tasks. The same set of Chinese, White and Black faces, each posing a neutral, happy or angry expression, was used in three experiments. Facial emotion interacted with face race in all the tasks. The interaction of face race and face gender was found in the race and gender categorization tasks, whereas the interaction of facial emotion and face gender was significant in the emotion and gender categorization tasks. These results provided evidence for a symmetric interaction between variant facial properties (emotion) and invariant facial properties (race and gender).
Interference among the Processing of Facial Emotion, Face Race, and Face Gender

PubMed Central

Li, Yongna; Tse, Chi-Shing

2016-01-01

People can process multiple dimensions of facial properties simultaneously. Facial processing models are based on the processing of facial properties. The current study examined the processing of facial emotion, face race, and face gender using categorization tasks. The same set of Chinese, White and Black faces, each posing a neutral, happy or angry expression, was used in three experiments. Facial emotion interacted with face race in all the tasks. The interaction of face race and face gender was found in the race and gender categorization tasks, whereas the interaction of facial emotion and face gender was significant in the emotion and gender categorization tasks. These results provided evidence for a symmetric interaction between variant facial properties (emotion) and invariant facial properties (race and gender). PMID:27840621

Evaluating the independence of sex and expression in judgments of faces.

PubMed

Le Gal, Patricia M; Bruce, Vicki

2002-02-01

Face recognition models suggest independent processing for functionally different types of information, such as identity, expression, sex, and facial speech. Interference between sex and expression information was tested using both a rating study and Garner's selective attention paradigm using speeded sex and expression decisions. When participants were asked to assess the masculinity of male and female angry and surprised faces, they found surprised faces to be more feminine than angry ones (Experiment 1). However, in a speeded-classification situation in the laboratory in which the sex decision was either "easy" relative to the expression decision (Experiment 2) or of more equivalent difficulty (Experiment 3), it was possible for participants to attend selectively to either dimension without interference from the other. Qualified support is offered for independent processing routes.
Invariant object recognition based on the generalized discrete radon transform

NASA Astrophysics Data System (ADS)

Easley, Glenn R.; Colonna, Flavia

2004-04-01

We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.
Face recognition using an enhanced independent component analysis approach.

PubMed

Kwak, Keun-Chang; Pedrycz, Witold

2007-03-01

This paper is concerned with an enhanced independent component analysis (ICA) and its application to face recognition. Typically, face representations obtained by ICA involve unsupervised learning and high-order statistics. In this paper, we develop an enhancement of the generic ICA by augmenting this method by the Fisher linear discriminant analysis (LDA); hence, its abbreviation, FICA. The FICA is systematically developed and presented along with its underlying architecture. A comparative analysis explores four distance metrics, as well as classification with support vector machines (SVMs). We demonstrate that the FICA approach leads to the formation of well-separated classes in low-dimension subspace and is endowed with a great deal of insensitivity to large variation in illumination and facial expression. The comprehensive experiments are completed for the facial-recognition technology (FERET) face database; a comparative analysis demonstrates that FICA comes with improved classification rates when compared with some other conventional approaches such as eigenface, fisherface, and the ICA itself.
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.
Subliminal access to abstract face representations does not rely on attention.

PubMed

Harry, Bronson; Davis, Chris; Kim, Jeesun

2012-03-01

The present study used masked repetition priming to examine whether face representations can be accessed without attention. Two experiments using a face recognition task (fame judgement) presented masked repetition and control primes in spatially unattended locations prior to target onset. Experiment 1 (n=20) used the same images as primes and as targets and Experiment 2 (n=17) used different images of the same individual as primes and targets. Repetition priming was observed across both experiments regardless of whether spatial attention was cued to the location of the prime. Priming occurred for both famous and non-famous targets in Experiment 1 but was only reliable for famous targets in Experiment 2, suggesting that priming in Experiment 1 indexed access to view-specific representations whereas priming in Experiment 2 indexed access to view-invariant, abstract representations. Overall, the results indicate that subliminal access to abstract face representations does not rely on attention. Copyright © 2011 Elsevier Inc. All rights reserved.
Lip reading using neural networks

NASA Astrophysics Data System (ADS)

Kalbande, Dhananjay; Mishra, Akassh A.; Patil, Sanjivani; Nirgudkar, Sneha; Patel, Prashant

2011-10-01

Computerized lip reading, or speech reading, is concerned with the difficult task of converting a video signal of a speaking person to written text. It has several applications like teaching deaf and dumb to speak and communicate effectively with the other people, its crime fighting potential and invariance to acoustic environment. We convert the video of the subject speaking vowels into images and then images are further selected manually for processing. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. Contour tracking methods and Template matching are used for the extraction of lips from the face. K Nearest Neighbor algorithm is then used to classify the 'speaking' images and the 'silent' images. The sequence of images is then transformed into segments of utterances. Feature vector is calculated on each frame for all the segments and is stored in the database with properly labeled class. Character recognition is performed using modified KNN algorithm which assigns more weight to nearer neighbors. This paper reports the recognition of vowels using KNN algorithms
Robust Real-Time and Rotation-Invariant American Sign Language Alphabet Recognition Using Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2012-07-01

The automatic interpretation of human gestures can be used for a natural interaction with computers without the use of mechanical devices such as keyboards and mice. The recognition of hand postures have been studied for many years. However, most of the literature in this area has considered 2D images which cannot provide a full description of the hand gestures. In addition, a rotation-invariant identification remains an unsolved problem even with the use of 2D images. The objective of the current study is to design a rotation-invariant recognition process while using a 3D signature for classifying hand postures. An heuristic and voxelbased signature has been designed and implemented. The tracking of the hand motion is achieved with the Kalman filter. A unique training image per posture is used in the supervised classification. The designed recognition process and the tracking procedure have been successfully evaluated. This study has demonstrated the efficiency of the proposed rotation invariant 3D hand posture signature which leads to 98.24% recognition rate after testing 12723 samples of 12 gestures taken from the alphabet of the American Sign Language.
Discrimination and categorization of emotional facial expressions and faces in Parkinson's disease.

PubMed

Alonso-Recio, Laura; Martín, Pilar; Rubio, Sandra; Serrano, Juan M

2014-09-01

Our objective was to compare the ability to discriminate and categorize emotional facial expressions (EFEs) and facial identity characteristics (age and/or gender) in a group of 53 individuals with Parkinson's disease (PD) and another group of 53 healthy subjects. On the one hand, by means of discrimination and identification tasks, we compared two stages in the visual recognition process that could be selectively affected in individuals with PD. On the other hand, facial expression versus gender and age comparison permits us to contrast whether the emotional or non-emotional content influences the configural perception of faces. In Experiment I, we did not find differences between groups, either with facial expression or age, in discrimination tasks. Conversely, in Experiment II, we found differences between the groups, but only in the EFE identification task. Taken together, our results indicate that configural perception of faces does not seem to be globally impaired in PD. However, this ability is selectively altered when the categorization of emotional faces is required. A deeper assessment of the PD group indicated that decline in facial expression categorization is more evident in a subgroup of patients with higher global impairment (motor and cognitive). Taken together, these results suggest that the problems found in facial expression recognition may be associated with the progressive neuronal loss in frontostriatal and mesolimbic circuits, which characterizes PD. © 2013 The British Psychological Society.
Emotion recognition abilities across stimulus modalities in schizophrenia and the role of visual attention.

PubMed

Simpson, Claire; Pinkham, Amy E; Kelsven, Skylar; Sasson, Noah J

2013-12-01

Emotion can be expressed by both the voice and face, and previous work suggests that presentation modality may impact emotion recognition performance in individuals with schizophrenia. We investigated the effect of stimulus modality on emotion recognition accuracy and the potential role of visual attention to faces in emotion recognition abilities. Thirty-one patients who met DSM-IV criteria for schizophrenia (n=8) or schizoaffective disorder (n=23) and 30 non-clinical control individuals participated. Both groups identified emotional expressions in three different conditions: audio only, visual only, combined audiovisual. In the visual only and combined conditions, time spent visually fixating salient features of the face were recorded. Patients were significantly less accurate than controls in emotion recognition during both the audio and visual only conditions but did not differ from controls on the combined condition. Analysis of visual scanning behaviors demonstrated that patients attended less than healthy individuals to the mouth in the visual condition but did not differ in visual attention to salient facial features in the combined condition, which may in part explain the absence of a deficit for patients in this condition. Collectively, these findings demonstrate that patients benefit from multimodal stimulus presentations of emotion and support hypotheses that visual attention to salient facial features may serve as a mechanism for accurate emotion identification. © 2013.
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.
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.
Understanding amygdala responsiveness to fearful expressions through the lens of psychopathy and altruism.

PubMed

Marsh, Abigail A

2016-06-01

Because the face is the central focus of human social interactions, emotional facial expressions provide a unique window into the emotional lives of others. They play a particularly important role in fostering empathy, which entails understanding and responding to others' emotions, especially distress-related emotions such as fear. This Review considers how fearful facial as well as vocal and postural expressions are interpreted, with an emphasis on the role of the amygdala. The amygdala may be best known for its role in the acquisition and expression of conditioned fear, but it also supports the perception and recognition of others' fear. Various explanations have been supplied for the amygdala's role in interpreting and responding to fearful expressions. They include theories that amygdala responses to fearful expressions 1) reflect heightened vigilance in response to uncertain danger, 2) promote heightened attention to the eye region of faces, 3) represent a response to an unconditioned aversive stimulus, or 4) reflect the generation of an empathic fear response. Among these, only empathic fear explains why amygdala lesions would impair fear recognition across modalities. Supporting the possibility of a link between fundamental empathic processes and amygdala responses to fear is evidence that impaired fear recognition in psychopathic individuals results from amygdala dysfunction, whereas enhanced fear recognition in altruistic individuals results from enhanced amygdala function. Empathic concern and caring behaviors may be fostered by sensitivity to signs of acute distress in others, which relies on intact functioning of the amygdala. © 2015 Wiley Periodicals, Inc.
Facial Affect Recognition in Violent and Nonviolent Antisocial Behavior Subtypes.

PubMed

Schönenberg, Michael; Mayer, Sarah Verena; Christian, Sandra; Louis, Katharina; Jusyte, Aiste

2016-10-01

Prior studies provide evidence for impaired recognition of distress cues in individuals exhibiting antisocial behavior. However, it remains unclear whether this deficit is generally associated with antisociality or may be specific to violent behavior only. To examine whether there are meaningful differences between the two behavioral dimensions rule-breaking and aggression, violent and nonviolent incarcerated offenders as well as control participants were presented with an animated face recognition task in which a video sequence of a neutral face changed into an expression of one of the six basic emotions. The participants were instructed to press a button as soon as they were able to identify the emotional expression, allowing for an assessment of the perceived emotion onset. Both aggressive and nonaggressive offenders demonstrated a delayed perception of primarily fearful facial cues as compared to controls. These results suggest the importance of targeting impaired emotional processing in both types of antisocial behavior.
Head pose estimation in computer vision: a survey.

PubMed

Murphy-Chutorian, Erik; Trivedi, Mohan Manubhai

2009-04-01

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.
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
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.
Identity modulates short-term memory for facial emotion

PubMed Central

Galster, Murray; Kahana, Michael J.; Wilson, Hugh R.; Sekuler, Robert

2010-01-01

For some time, the relationship between processing of facial expression and facial identity has been in dispute. Using realistic synthetic faces, we reexamined this relationship for both perception and short-term memory. In Experiment 1, subjects tried to identify whether the emotional expression on a probe stimulus face matched the emotional expression on either of two remembered faces that they had just seen. The results showed that identity strongly influenced recognition short-term memory for emotional expression. In Experiment 2, subjects’ similarity/dissimilarity judgments were transformed by multidimensional scaling (MDS) into a 2-D description of the faces’ perceptual representations. Distances among stimuli in the MDS representation, which showed a strong linkage of emotional expression and facial identity, were good predictors of correct and false recognitions obtained previously in Experiment 1. The convergence of the results from Experiments 1 and 2 suggests that the overall structure and configuration of faces’ perceptual representations may parallel their representation in short-term memory and that facial identity modulates the representation of facial emotion, both in perception and in memory. The stimuli from this study may be downloaded from http://cabn.psychonomic-journals.org/content/supplemental. PMID:19897794
General recognition theory with individual differences: a new method for examining perceptual and decisional interactions with an application to face perception.

PubMed

Soto, Fabian A; Vucovich, Lauren; Musgrave, Robert; Ashby, F Gregory

2015-02-01

A common question in perceptual science is to what extent different stimulus dimensions are processed independently. General recognition theory (GRT) offers a formal framework via which different notions of independence can be defined and tested rigorously, while also dissociating perceptual from decisional factors. This article presents a new GRT model that overcomes several shortcomings with previous approaches, including a clearer separation between perceptual and decisional processes and a more complete description of such processes. The model assumes that different individuals share similar perceptual representations, but vary in their attention to dimensions and in the decisional strategies they use. We apply the model to the analysis of interactions between identity and emotional expression during face recognition. The results of previous research aimed at this problem have been disparate. Participants identified four faces, which resulted from the combination of two identities and two expressions. An analysis using the new GRT model showed a complex pattern of dimensional interactions. The perception of emotional expression was not affected by changes in identity, but the perception of identity was affected by changes in emotional expression. There were violations of decisional separability of expression from identity and of identity from expression, with the former being more consistent across participants than the latter. One explanation for the disparate results in the literature is that decisional strategies may have varied across studies and influenced the results of tests of perceptual interactions, as previous studies lacked the ability to dissociate between perceptual and decisional interactions.
[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.
View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Freiwald, Winrich A.; Anselmi, Fabio; Poggio, Tomaso

2017-01-01

SUMMARY The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations [1, 2]. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3, 4, 5, 6]. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. PMID:27916522

Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification.

PubMed

Li, Haoxiang; Hua, Gang

2018-04-01

Pose variation remains to be a major challenge for real-world face recognition. We approach this problem through a probabilistic elastic part model. We extract local descriptors (e.g., LBP or SIFT) from densely sampled multi-scale image patches. By augmenting each descriptor with its location, a Gaussian mixture model (GMM) is trained to capture the spatial-appearance distribution of the face parts of all face images in the training corpus, namely the probabilistic elastic part (PEP) model. Each mixture component of the GMM is confined to be a spherical Gaussian to balance the influence of the appearance and the location terms, which naturally defines a part. Given one or multiple face images of the same subject, the PEP-model builds its PEP representation by sequentially concatenating descriptors identified by each Gaussian component in a maximum likelihood sense. We further propose a joint Bayesian adaptation algorithm to adapt the universally trained GMM to better model the pose variations between the target pair of faces/face tracks, which consistently improves face verification accuracy. Our experiments show that we achieve state-of-the-art face verification accuracy with the proposed representations on the Labeled Face in the Wild (LFW) dataset, the YouTube video face database, and the CMU MultiPIE dataset.
QWT: Retrospective and New Applications

NASA Astrophysics Data System (ADS)

Xu, Yi; Yang, Xiaokang; Song, Li; Traversoni, Leonardo; Lu, Wei

Quaternion wavelet transform (QWT) achieves much attention in recent years as a new image analysis tool. In most cases, it is an extension of the real wavelet transform and complex wavelet transform (CWT) by using the quaternion algebra and the 2D Hilbert transform of filter theory, where analytic signal representation is desirable to retrieve phase-magnitude description of intrinsically 2D geometric structures in a grayscale image. In the context of color image processing, however, it is adapted to analyze the image pattern and color information as a whole unit by mapping sequential color pixels to a quaternion-valued vector signal. This paper provides a retrospective of QWT and investigates its potential use in the domain of image registration, image fusion, and color image recognition. It is indicated that it is important for QWT to induce the mechanism of adaptive scale representation of geometric features, which is further clarified through two application instances of uncalibrated stereo matching and optical flow estimation. Moreover, quaternionic phase congruency model is defined based on analytic signal representation so as to operate as an invariant feature detector for image registration. To achieve better localization of edges and textures in image fusion task, we incorporate directional filter bank (DFB) into the quaternion wavelet decomposition scheme to greatly enhance the direction selectivity and anisotropy of QWT. Finally, the strong potential use of QWT in color image recognition is materialized in a chromatic face recognition system by establishing invariant color features. Extensive experimental results are presented to highlight the exciting properties of QWT.
Updating schematic emotional facial expressions in working memory: Response bias and sensitivity.

PubMed

Tamm, Gerly; Kreegipuu, Kairi; Harro, Jaanus; Cowan, Nelson

2017-01-01

It is unclear if positive, negative, or neutral emotional expressions have an advantage in short-term recognition. Moreover, it is unclear from previous studies of working memory for emotional faces whether effects of emotions comprise response bias or sensitivity. The aim of this study was to compare how schematic emotional expressions (sad, angry, scheming, happy, and neutral) are discriminated and recognized in an updating task (2-back recognition) in a representative sample of birth cohort of young adults. Schematic facial expressions allow control of identity processing, which is separate from expression processing, and have been used extensively in attention research but not much, until now, in working memory research. We found that expressions with a U-curved mouth (i.e., upwardly curved), namely happy and scheming expressions, favoured a bias towards recognition (i.e., towards indicating that the probe and the stimulus in working memory are the same). Other effects of emotional expression were considerably smaller (1-2% of the variance explained)) compared to a large proportion of variance that was explained by the physical similarity of items being compared. We suggest that the nature of the stimuli plays a role in this. The present application of signal detection methodology with emotional, schematic faces in a working memory procedure requiring fast comparisons helps to resolve important contradictions that have emerged in the emotional perception literature. Copyright © 2016 Elsevier B.V. All rights reserved.
Orientation-Invariant Object Recognition: Evidence from Repetition Blindness

ERIC Educational Resources Information Center

Harris, Irina M.; Dux, Paul E.

2005-01-01

The question of whether object recognition is orientation-invariant or orientation-dependent was investigated using a repetition blindness (RB) paradigm. In RB, the second occurrence of a repeated stimulus is less likely to be reported, compared to the occurrence of a different stimulus, if it occurs within a short time of the first presentation.…
Face-n-Food: Gender Differences in Tuning to Faces.

PubMed

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

2015-01-01

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

PubMed Central

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Hussein, Wafaa R.; Sellahewa, Harin; Jassim, Sabah A.

2012-06-01

Face recognition in uncontrolled environments is greatly affected by fuzziness of face feature vectors as a result of extreme variation in recording conditions (e.g. illumination, poses or expressions) in different sessions. Many techniques have been developed to deal with these variations, resulting in improved performances. This paper aims to model template fuzziness as errors and investigate the use of error detection/correction techniques for face recognition in uncontrolled environments. Error correction codes (ECC) have recently been used for biometric key generation but not on biometric templates. We have investigated error patterns in binary face feature vectors extracted from different image windows of differing sizes and for different recording conditions. By estimating statistical parameters for the intra-class and inter-class distributions of Hamming distances in each window, we encode with appropriate ECC's. The proposed approached is tested for binarised wavelet templates using two face databases: Extended Yale-B and Yale. We shall demonstrate that using different combinations of BCH-based ECC's for different blocks and different recording conditions leads to in different accuracy rates, and that using ECC's results in significantly improved recognition results.
Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

NASA Astrophysics Data System (ADS)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.
Learning the spherical harmonic features for 3-D face recognition.

PubMed

Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

2013-03-01

In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method.
The role of movement in the recognition of famous faces.

PubMed

Lander, K; Christie, F; Bruce, V

1999-11-01

The effects of movement on the recognition of famous faces shown in difficult conditions were investigated. Images were presented as negatives, upside down (inverted), and thresholded. Results indicate that, under all these conditions, moving faces were recognized significantly better than static ones. One possible explanation of this effect could be that a moving sequence contains more static information about the different views and expressions of the face than does a single static image. However, even when the amount of static information was equated (Experiments 3 and 4), there was still an advantage for moving sequences that contained their original dynamic properties. The results suggest that the dynamics of the motion provide additional information, helping to access an established familiar face representation. Both the theoretical and the practical implications for these findings are discussed.
Robust 3D face landmark localization based on local coordinate coding.

PubMed

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J

2014-12-01

In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.
The effects of angry and happy expressions on recognition memory for unfamiliar faces in delusion-prone individuals.

PubMed

Larøi, Frank; D'Argembeau, Arnaud; Van der Linden, Martial

2006-12-01

Numerous studies suggest a cognitive bias for threat-related material in delusional ideation. However, few studies have examined this bias using a memory task. We investigated the influence of delusion-proneness on identity and expression memory for angry and happy faces. Participants high and low in delusion-proneness were presented with happy and angry faces and were later asked to recognise the same faces displaying a neutral expression. They also had to remember what the initial expressions of the faces had been. Remember/know/guess judgments were asked for both identity and expression memory. Results showed that delusion-prone participants better recognised the identity of angry faces compared to non-delusional participants. Also, this difference between the two groups was mainly due to a greater number of remember responses in delusion-prone participants. These findings extend previous studies by showing that delusions are associated with a memory bias for threat-related stimuli.
Visual Search for Basic Emotional Expressions in Autism; Impaired Processing of Anger, Fear and Sadness, but a Typical Happy Face Advantage

ERIC Educational Resources Information Center

Farran, Emily K.; Branson, Amanda; King, Ben J.

2011-01-01

Facial expression recognition was investigated in 20 males with high functioning autism (HFA) or Asperger syndrome (AS), compared to typically developing individuals matched for chronological age (TD CA group) and verbal and non-verbal ability (TD V/NV group). This was the first study to employ a visual search, "face in the crowd" paradigm with a…
Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala.

PubMed

Inagaki, Mikio; Fujita, Ichiro

2011-07-13

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.
Hierarchical Encoding of Social Cues in Primate Inferior Temporal Cortex.

PubMed

Morin, Elyse L; Hadj-Bouziane, Fadila; Stokes, Mark; Ungerleider, Leslie G; Bell, Andrew H

2015-09-01

Faces convey information about identity and emotional state, both of which are important for our social interactions. Models of face processing propose that changeable versus invariant aspects of a face, specifically facial expression/gaze direction versus facial identity, are coded by distinct neural pathways and yet neurophysiological data supporting this separation are incomplete. We recorded activity from neurons along the inferior bank of the superior temporal sulcus (STS), while monkeys viewed images of conspecific faces and non-face control stimuli. Eight monkey identities were used, each presented with 3 different facial expressions (neutral, fear grin, and threat). All facial expressions were displayed with both a direct and averted gaze. In the posterior STS, we found that about one-quarter of face-responsive neurons are sensitive to social cues, the majority of which being sensitive to only one of these cues. In contrast, in anterior STS, not only did the proportion of neurons sensitive to social cues increase, but so too did the proportion of neurons sensitive to conjunctions of identity with either gaze direction or expression. These data support a convergence of signals related to faces as one moves anteriorly along the inferior bank of the STS, which forms a fundamental part of the face-processing network. Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.
Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions

PubMed Central

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject’s face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject’s face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network. PMID:26859884
Project PAVE (Personality And Vision Experimentation): role of personal and interpersonal resilience in the perception of emotional facial expression

PubMed Central

Tanzer, Michal; Shahar, Golan; Avidan, Galia

2014-01-01

The aim of the proposed theoretical model is to illuminate personal and interpersonal resilience by drawing from the field of emotional face perception. We suggest that perception/recognition of emotional facial expressions serves as a central link between subjective, self-related processes and the social context. Emotional face perception constitutes a salient social cue underlying interpersonal communication and behavior. Because problems in communication and interpersonal behavior underlie most, if not all, forms of psychopathology, it follows that perception/recognition of emotional facial expressions impacts psychopathology. The ability to accurately interpret one’s facial expression is crucial in subsequently deciding on an appropriate course of action. However, perception in general, and of emotional facial expressions in particular, is highly influenced by individuals’ personality and the self-concept. Herein we briefly outline well-established theories of personal and interpersonal resilience and link them to the neuro-cognitive basis of face perception. We then describe the findings of our ongoing program of research linking two well-established resilience factors, general self-efficacy (GSE) and perceived social support (PSS), with face perception. We conclude by pointing out avenues for future research focusing on possible genetic markers and patterns of brain connectivity associated with the proposed model. Implications of our integrative model to psychotherapy are discussed. PMID:25165439
Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

PubMed

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.
Diminutives facilitate word segmentation in natural speech: cross-linguistic evidence.

PubMed

Kempe, Vera; Brooks, Patricia J; Gillis, Steven; Samson, Graham

2007-06-01

Final-syllable invariance is characteristic of diminutives (e.g., doggie), which are a pervasive feature of the child-directed speech registers of many languages. Invariance in word endings has been shown to facilitate word segmentation (Kempe, Brooks, & Gillis, 2005) in an incidental-learning paradigm in which synthesized Dutch pseudonouns were used. To broaden the cross-linguistic evidence for this invariance effect and to increase its ecological validity, adult English speakers (n=276) were exposed to naturally spoken Dutch or Russian pseudonouns presented in sentence contexts. A forced choice test was given to assess target recognition, with foils comprising unfamiliar syllable combinations in Experiments 1 and 2 and syllable combinations straddling word boundaries in Experiment 3. A control group (n=210) received the recognition test with no prior exposure to targets. Recognition performance improved with increasing final-syllable rhyme invariance, with larger increases for the experimental group. This confirms that word ending invariance is a valid segmentation cue in artificial, as well as naturalistic, speech and that diminutives may aid segmentation in a number of languages.

Does Facial Resemblance Enhance Cooperation?

PubMed Central

Giang, Trang; Bell, Raoul; Buchner, Axel

2012-01-01

Facial self-resemblance has been proposed to serve as a kinship cue that facilitates cooperation between kin. In the present study, facial resemblance was manipulated by morphing stimulus faces with the participants' own faces or control faces (resulting in self-resemblant or other-resemblant composite faces). A norming study showed that the perceived degree of kinship was higher for the participants and the self-resemblant composite faces than for actual first-degree relatives. Effects of facial self-resemblance on trust and cooperation were tested in a paradigm that has proven to be sensitive to facial trustworthiness, facial likability, and facial expression. First, participants played a cooperation game in which the composite faces were shown. Then, likability ratings were assessed. In a source memory test, participants were required to identify old and new faces, and were asked to remember whether the faces belonged to cooperators or cheaters in the cooperation game. Old-new recognition was enhanced for self-resemblant faces in comparison to other-resemblant faces. However, facial self-resemblance had no effects on the degree of cooperation in the cooperation game, on the emotional evaluation of the faces as reflected in the likability judgments, and on the expectation that a face belonged to a cooperator rather than to a cheater. Therefore, the present results are clearly inconsistent with the assumption of an evolved kin recognition module built into the human face recognition system. PMID:23094095
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.
Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition

PubMed Central

Kheradpisheh, Saeed Reza; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

2016-01-01

Deep convolutional neural networks (DCNNs) have attracted much attention recently, and have shown to be able to recognize thousands of object categories in natural image databases. Their architecture is somewhat similar to that of the human visual system: both use restricted receptive fields, and a hierarchy of layers which progressively extract more and more abstracted features. Yet it is unknown whether DCNNs match human performance at the task of view-invariant object recognition, whether they make similar errors and use similar representations for this task, and whether the answers depend on the magnitude of the viewpoint variations. To investigate these issues, we benchmarked eight state-of-the-art DCNNs, the HMAX model, and a baseline shallow model and compared their results to those of humans with backward masking. Unlike in all previous DCNN studies, we carefully controlled the magnitude of the viewpoint variations to demonstrate that shallow nets can outperform deep nets and humans when variations are weak. When facing larger variations, however, more layers were needed to match human performance and error distributions, and to have representations that are consistent with human behavior. A very deep net with 18 layers even outperformed humans at the highest variation level, using the most human-like representations. PMID:27601096
An audiovisual emotion recognition system

NASA Astrophysics Data System (ADS)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.
Memory for faces and voices varies as a function of sex and expressed emotion.

PubMed

S Cortes, Diana; Laukka, Petri; Lindahl, Christina; Fischer, Håkan

2017-01-01

We investigated how memory for faces and voices (presented separately and in combination) varies as a function of sex and emotional expression (anger, disgust, fear, happiness, sadness, and neutral). At encoding, participants judged the expressed emotion of items in forced-choice tasks, followed by incidental Remember/Know recognition tasks. Results from 600 participants showed that accuracy (hits minus false alarms) was consistently higher for neutral compared to emotional items, whereas accuracy for specific emotions varied across the presentation modalities (i.e., faces, voices, and face-voice combinations). For the subjective sense of recollection ("remember" hits), neutral items received the highest hit rates only for faces, whereas for voices and face-voice combinations anger and fear expressions instead received the highest recollection rates. We also observed better accuracy for items by female expressers, and own-sex bias where female participants displayed memory advantage for female faces and face-voice combinations. Results further suggest that own-sex bias can be explained by recollection, rather than familiarity, rates. Overall, results show that memory for faces and voices may be influenced by the expressions that they carry, as well as by the sex of both items and participants. Emotion expressions may also enhance the subjective sense of recollection without enhancing memory accuracy.
Memory for faces and voices varies as a function of sex and expressed emotion

PubMed Central

Laukka, Petri; Lindahl, Christina; Fischer, Håkan

2017-01-01

We investigated how memory for faces and voices (presented separately and in combination) varies as a function of sex and emotional expression (anger, disgust, fear, happiness, sadness, and neutral). At encoding, participants judged the expressed emotion of items in forced-choice tasks, followed by incidental Remember/Know recognition tasks. Results from 600 participants showed that accuracy (hits minus false alarms) was consistently higher for neutral compared to emotional items, whereas accuracy for specific emotions varied across the presentation modalities (i.e., faces, voices, and face-voice combinations). For the subjective sense of recollection (“remember” hits), neutral items received the highest hit rates only for faces, whereas for voices and face-voice combinations anger and fear expressions instead received the highest recollection rates. We also observed better accuracy for items by female expressers, and own-sex bias where female participants displayed memory advantage for female faces and face-voice combinations. Results further suggest that own-sex bias can be explained by recollection, rather than familiarity, rates. Overall, results show that memory for faces and voices may be influenced by the expressions that they carry, as well as by the sex of both items and participants. Emotion expressions may also enhance the subjective sense of recollection without enhancing memory accuracy. PMID:28570691
A task-invariant cognitive reserve network.

PubMed

Stern, Yaakov; Gazes, Yunglin; Razlighi, Qolomreza; Steffener, Jason; Habeck, Christian

2018-05-14

The concept of cognitive reserve (CR) can explain individual differences in susceptibility to cognitive or functional impairment in the presence of age or disease-related brain changes. Epidemiologic evidence indicates that CR helps maintain performance in the face of pathology across multiple cognitive domains. We therefore tried to identify a single, "task-invariant" CR network that is active during the performance of many disparate tasks. In imaging data acquired from 255 individuals age 20-80 while performing 12 different cognitive tasks, we used an iterative approach to derive a multivariate network that was expressed during the performance of all tasks, and whose degree of expression correlated with IQ, a proxy for CR. When applied to held out data or forward applied to fMRI data from an entirely different activation task, network expression correlated with IQ. Expression of the CR pattern accounted for additional variance in fluid reasoning performance over and above the influence of cortical thickness, and also moderated between cortical thickness and reasoning performance, consistent with the behavior of a CR network. The identification of a task-invariant CR network supports the idea that life experiences may result in brain processing differences that might provide reserve against age- or disease-related changes across multiple tasks. Copyright © 2018. Published by Elsevier Inc.
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.
Measuring Individual Differences in Sensitivities to Basic Emotions in Faces

ERIC Educational Resources Information Center

Suzuki, Atsunobu; Hoshino, Takahiro; Shigemasu, Kazuo

2006-01-01

The assessment of individual differences in facial expression recognition is normally required to address two major issues: (1) high agreement level (ceiling effect) and (2) differential difficulty levels across emotions. We propose a new assessment method designed to quantify individual differences in the recognition of the six basic emotions,…
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.
Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.
Applying the attractor field model to social cognition: Perceptual discrimination is facilitated, but memory is impaired for faces displaying evaluatively congruent expressions.

PubMed

Corneille, Olivier; Hugenberg, Kurt; Potter, Timothy

2007-09-01

A new model of mental representation is applied to social cognition: the attractor field model. Using the model, the authors predicted and found a perceptual advantage but a memory disadvantage for faces displaying evaluatively congruent expressions. In Experiment 1, participants completed a same/different perceptual discrimination task involving morphed pairs of angry-to-happy Black and White faces. Pairs of faces displaying evaluatively incongruent expressions (i.e., happy Black, angry White) were more likely to be labeled as similar and were less likely to be accurately discriminated from one another than faces displaying evaluatively congruent expressions (i.e., angry Black, happy White). Experiment 2 replicated this finding and showed that objective discriminability of stimuli moderated the impact of attractor field effects on perceptual discrimination accuracy. In Experiment 3, participants completed a recognition task for angry and happy Black and White faces. Consistent with the attractor field model, memory accuracy was better for faces displaying evaluatively incongruent expressions. Theoretical and practical implications of these findings are discussed. (c) 2007 APA, all rights reserved
Fusiform gyrus face selectivity relates to individual differences in facial recognition ability.

PubMed

Furl, Nicholas; Garrido, Lúcia; Dolan, Raymond J; Driver, Jon; Duchaine, Bradley

2011-07-01

Regions of the occipital and temporal lobes, including a region in the fusiform gyrus (FG), have been proposed to constitute a "core" visual representation system for faces, in part because they show face selectivity and face repetition suppression. But recent fMRI studies of developmental prosopagnosics (DPs) raise questions about whether these measures relate to face processing skills. Although DPs manifest deficient face processing, most studies to date have not shown unequivocal reductions of functional responses in the proposed core regions. We scanned 15 DPs and 15 non-DP control participants with fMRI while employing factor analysis to derive behavioral components related to face identification or other processes. Repetition suppression specific to facial identities in FG or to expression in FG and STS did not show compelling relationships with face identification ability. However, we identified robust relationships between face selectivity and face identification ability in FG across our sample for several convergent measures, including voxel-wise statistical parametric mapping, peak face selectivity in individually defined "fusiform face areas" (FFAs), and anatomical extents (cluster sizes) of those FFAs. None of these measures showed associations with behavioral expression or object recognition ability. As a group, DPs had reduced face-selective responses in bilateral FFA when compared with non-DPs. Individual DPs were also more likely than non-DPs to lack expected face-selective activity in core regions. These findings associate individual differences in face processing ability with selectivity in core face processing regions. This confirms that face selectivity can provide a valid marker for neural mechanisms that contribute to face identification ability.
Recognition of emotional facial expressions and broad autism phenotype in parents of children diagnosed with autistic spectrum disorder.

PubMed

Kadak, Muhammed Tayyib; Demirel, Omer Faruk; Yavuz, Mesut; Demir, Türkay

2014-07-01

Research findings debate about features of broad autism phenotype. In this study, we tested whether parents of children with autism have problems recognizing emotional facial expression and the contribution of such an impairment to the broad phenotype of autism. Seventy-two parents of children with autistic spectrum disorder and 38 parents of control group participated in the study. Broad autism features was measured with Autism Quotient (AQ). Recognition of Emotional Face Expression Test was assessed with the Emotion Recognition Test, consisting a set of photographs from Ekman & Friesen's. In a two-tailed analysis of variance of AQ, there was a significant difference for social skills (F(1, 106)=6.095; p<.05). Analyses of variance revealed significant difference in the recognition of happy, surprised and neutral expressions (F(1, 106)=4.068, p=.046; F(1, 106)=4.068, p=.046; F(1, 106)=6.064, p=.016). According to our findings, social impairment could be considered a characteristic feature of BAP. ASD parents had difficulty recognizing neutral expressions, suggesting that ASD parents may have impaired recognition of ambiguous expressions as do autistic children. Copyright © 2014 Elsevier Inc. All rights reserved.
Newborn chickens generate invariant object representations at the onset of visual object experience

PubMed Central

Wood, Justin N.

2013-01-01

To recognize objects quickly and accurately, mature visual systems build invariant object representations that generalize across a range of novel viewing conditions (e.g., changes in viewpoint). To date, however, the origins of this core cognitive ability have not yet been established. To examine how invariant object recognition develops in a newborn visual system, I raised chickens from birth for 2 weeks within controlled-rearing chambers. These chambers provided complete control over all visual object experiences. In the first week of life, subjects’ visual object experience was limited to a single virtual object rotating through a 60° viewpoint range. In the second week of life, I examined whether subjects could recognize that virtual object from novel viewpoints. Newborn chickens were able to generate viewpoint-invariant representations that supported object recognition across large, novel, and complex changes in the object’s appearance. Thus, newborn visual systems can begin building invariant object representations at the onset of visual object experience. These abstract representations can be generated from sparse data, in this case from a visual world containing a single virtual object seen from a limited range of viewpoints. This study shows that powerful, robust, and invariant object recognition machinery is an inherent feature of the newborn brain. PMID:23918372
Can gaze avoidance explain why individuals with Asperger's syndrome can't recognise emotions from facial expressions?

PubMed

Sawyer, Alyssa C P; Williamson, Paul; Young, Robyn L

2012-04-01

Research has shown that individuals with Autism Spectrum Disorders (ASD) have difficulties recognising emotions from facial expressions. Since eye contact is important for accurate emotion recognition, and individuals with ASD tend to avoid eye contact, this tendency for gaze aversion has been proposed as an explanation for the emotion recognition deficit. This explanation was investigated using a newly developed emotion and mental state recognition task. Individuals with Asperger's Syndrome were less accurate at recognising emotions and mental states, but did not show evidence of gaze avoidance compared to individuals without Asperger's Syndrome. This suggests that the way individuals with Asperger's Syndrome look at faces cannot account for the difficulty they have recognising expressions.
Preschooler's Faces in Spontaneous Emotional Contexts--How Well Do They Match Adult Facial Expression Prototypes?

ERIC Educational Resources Information Center

Gaspar, Augusta; Esteves, Francisco G.

2012-01-01

Prototypical facial expressions of emotion, also known as universal facial expressions, are the underpinnings of most research concerning recognition of emotions in both adults and children. Data on natural occurrences of these prototypes in natural emotional contexts are rare and difficult to obtain in adults. By recording naturalistic…
Accurate landmarking of three-dimensional facial data in the presence of facial expressions and occlusions using a three-dimensional statistical facial feature model.

PubMed

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

2011-10-01

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

PubMed

Caudek, Corrado; Monni, Alessandra

2013-01-01

We studied the effects of negative cognitive style, sad mood, and facial affect on the self-face advantage in a sample of 66 healthy individuals (mean age 26.5 years, range 19-47 years). The sample was subdivided into four groups according to inferential style and responsivity to sad mood induction. Following a sad mood induction, we examined the effect on working memory of an incidental association between facial affect, facial identity, and head-pose orientation. Overall, head-pose recognition was more accurate for the self-face than for nonself face (self-face advantage, SFA). However, participants high in negative cognitive style who experienced higher levels of sadness displayed a stronger SFA for sad expressions than happy expressions. The remaining participants displayed an opposite bias (a stronger SFA for happy expressions than sad expressions), or no bias. These findings highlight the importance of trait-vulnerability status in the working memory biases related to emotional facial expressions.
The time course of individual face recognition: A pattern analysis of ERP signals.

PubMed

Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

2016-05-15

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatially invariant coding of numerical information in functionally defined subregions of human parietal cortex.

PubMed

Eger, E; Pinel, P; Dehaene, S; Kleinschmidt, A

2015-05-01

Macaque electrophysiology has revealed neurons responsive to number in lateral (LIP) and ventral (VIP) intraparietal areas. Recently, fMRI pattern recognition revealed information discriminative of individual numbers in human parietal cortex but without precisely localizing the relevant sites or testing for subregions with different response profiles. Here, we defined the human functional equivalents of LIP (feLIP) and VIP (feVIP) using neurophysiologically motivated localizers. We applied multivariate pattern recognition to investigate whether both regions represent numerical information and whether number codes are position specific or invariant. In a delayed number comparison paradigm with laterally presented numerosities, parietal cortex discriminated between numerosities better than early visual cortex, and discrimination generalized across hemifields in parietal, but not early visual cortex. Activation patterns in the 2 parietal regions of interest did not differ in the coding of position-specific or position-independent number information, but in the expression of a numerical distance effect which was more pronounced in feLIP. Thus, the representation of number in parietal cortex is at least partially position invariant. Both feLIP and feVIP contain information about individual numerosities in humans, but feLIP hosts a coarser representation of numerosity than feVIP, compatible with either broader tuning or a summation code. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
In the face of emotions: event-related potentials in supraliminal and subliminal facial expression recognition.

PubMed

Balconi, Michela; Lucchiari, Claudio

2005-02-01

Is facial expression recognition marked by specific event-related potentials (ERPs) effects? Are conscious and unconscious elaborations of emotional facial stimuli qualitatively different processes? In Experiment 1, ERPs elicited by supraliminal stimuli were recorded when 21 participants viewed emotional facial expressions of four emotions and a neutral stimulus. Two ERP components (N2 and P3) were analyzed for their peak amplitude and latency measures. First, emotional face-specificity was observed for the negative deflection N2, whereas P3 was not affected by the content of the stimulus (emotional or neutral). A more posterior distribution of ERPs was found for N2. Moreover, a lateralization effect was revealed for negative (right lateralization) and positive (left lateralization) facial expressions. In Experiment 2 (20 participants), 1-ms subliminal stimulation was carried out. Unaware information processing was revealed to be quite similar to aware information processing for peak amplitude but not for latency. In fact, unconscious stimulation produced a more delayed peak variation than conscious stimulation.
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.
Still-to-video face recognition in unconstrained environments

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Liu, Changsong; Ding, Xiaoqing

2015-02-01

Face images from video sequences captured in unconstrained environments usually contain several kinds of variations, e.g. pose, facial expression, illumination, image resolution and occlusion. Motion blur and compression artifacts also deteriorate recognition performance. Besides, in various practical systems such as law enforcement, video surveillance and e-passport identification, only a single still image per person is enrolled as the gallery set. Many existing methods may fail to work due to variations in face appearances and the limit of available gallery samples. In this paper, we propose a novel approach for still-to-video face recognition in unconstrained environments. By assuming that faces from still images and video frames share the same identity space, a regularized least squares regression method is utilized to tackle the multi-modality problem. Regularization terms based on heuristic assumptions are enrolled to avoid overfitting. In order to deal with the single image per person problem, we exploit face variations learned from training sets to synthesize virtual samples for gallery samples. We adopt a learning algorithm combining both affine/convex hull-based approach and regularizations to match image sets. Experimental results on a real-world dataset consisting of unconstrained video sequences demonstrate that our method outperforms the state-of-the-art methods impressively.
Biometrics Foundation Documents

DTIC Science & Technology

2009-01-01

a digital form. The quality of the sensor used has a significant impact on the recognition results. Example “sensors” could be digital cameras...Difficult to control sensor and channel variances that significantly impact capabilities Not sufficiently distinctive for identification over large...expressions, hairstyle, glasses, hats, makeup, etc. have on face recognition systems? Minor variances , such as those mentioned, will have a moderate
Emotion Recognition in Children with Autism Spectrum Disorders: Relations to Eye Gaze and Autonomic State

ERIC Educational Resources Information Center

Bal, Elgiz; Harden, Emily; Lamb, Damon; Van Hecke, Amy Vaughan; Denver, John W.; Porges, Stephen W.

2010-01-01

Respiratory Sinus Arrhythmia (RSA), heart rate, and accuracy and latency of emotion recognition were evaluated in children with autism spectrum disorders (ASD) and typically developing children while viewing videos of faces slowly transitioning from a neutral expression to one of six basic emotions (e.g., anger, disgust, fear, happiness, sadness,…
Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors.

PubMed

Yurtman, Aras; Barshan, Billur

2017-08-09

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage.
Age- and gender-related variations of emotion recognition in pseudowords and faces.

PubMed

Demenescu, Liliana R; Mathiak, Krystyna A; Mathiak, Klaus

2014-01-01

BACKGROUND/STUDY CONTEXT: The ability to interpret emotionally salient stimuli is an important skill for successful social functioning at any age. The objective of the present study was to disentangle age and gender effects on emotion recognition ability in voices and faces. Three age groups of participants (young, age range: 18-35 years; middle-aged, age range: 36-55 years; and older, age range: 56-75 years) identified basic emotions presented in voices and faces in a forced-choice paradigm. Five emotions (angry, fearful, sad, disgusted, and happy) and a nonemotional category (neutral) were shown as encoded in color photographs of facial expressions and pseudowords spoken in affective prosody. Overall, older participants had a lower accuracy rate in categorizing emotions than young and middle-aged participants. Females performed better than males in recognizing emotions from voices, and this gender difference emerged in middle-aged and older participants. The performance of emotion recognition in faces was significantly correlated with the performance in voices. The current study provides further evidence for a general age and gender effect on emotion recognition; the advantage of females seems to be age- and stimulus modality-dependent.
Influence of emotional expression on memory recognition bias in schizophrenia as revealed by fMRI.

PubMed

Sergerie, Karine; Armony, Jorge L; Menear, Matthew; Sutton, Hazel; Lepage, Martin

2010-07-01

We recently showed that, in healthy individuals, emotional expression influences memory for faces both in terms of accuracy and, critically, in memory response bias (tendency to classify stimuli as previously seen or not, regardless of whether this was the case). Although schizophrenia has been shown to be associated with deficit in episodic memory and emotional processing, the relation between these processes in this population remains unclear. Here, we used our previously validated paradigm to directly investigate the modulation of emotion on memory recognition. Twenty patients with schizophrenia and matched healthy controls completed functional magnetic resonance imaging (fMRI) study of recognition memory of happy, sad, and neutral faces. Brain activity associated with the response bias was obtained by correlating this measure with the contrast subjective old (ie, hits and false alarms) minus subjective new (misses and correct rejections) for sad and happy expressions. Although patients exhibited an overall lower memory performance than controls, they showed the same effects of emotion on memory, both in terms of accuracy and bias. For sad faces, the similar behavioral pattern between groups was mirrored by a largely overlapping neural network, mostly involved in familiarity-based judgments (eg, parahippocampal gyrus). In contrast, controls activated a much larger set of regions for happy faces, including areas thought to underlie recollection-based memory retrieval (eg, superior frontal gyrus and hippocampus) and in novelty detection (eg, amygdala). This study demonstrates that, despite an overall lower memory accuracy, emotional memory is intact in schizophrenia, although emotion-specific differences in brain activation exist, possibly reflecting different strategies.
Basic and complex emotion recognition in children with autism: cross-cultural findings.

PubMed

Fridenson-Hayo, Shimrit; Berggren, Steve; Lassalle, Amandine; Tal, Shahar; Pigat, Delia; Bölte, Sven; Baron-Cohen, Simon; Golan, Ofer

2016-01-01

Children with autism spectrum conditions (ASC) have emotion recognition deficits when tested in different expression modalities (face, voice, body). However, these findings usually focus on basic emotions, using one or two expression modalities. In addition, cultural similarities and differences in emotion recognition patterns in children with ASC have not been explored before. The current study examined the similarities and differences in the recognition of basic and complex emotions by children with ASC and typically developing (TD) controls across three cultures: Israel, Britain, and Sweden. Fifty-five children with high-functioning ASC, aged 5-9, were compared to 58 TD children. On each site, groups were matched on age, sex, and IQ. Children were tested using four tasks, examining recognition of basic and complex emotions from voice recordings, videos of facial and bodily expressions, and emotional video scenarios including all modalities in context. Compared to their TD peers, children with ASC showed emotion recognition deficits in both basic and complex emotions on all three modalities and their integration in context. Complex emotions were harder to recognize, compared to basic emotions for the entire sample. Cross-cultural agreement was found for all major findings, with minor deviations on the face and body tasks. Our findings highlight the multimodal nature of ER deficits in ASC, which exist for basic as well as complex emotions and are relatively stable cross-culturally. Cross-cultural research has the potential to reveal both autism-specific universal deficits and the role that specific cultures play in the way empathy operates in different countries.
Neural Representations that Support Invariant Object Recognition

PubMed Central

Goris, Robbe L. T.; Op de Beeck, Hans P.

2008-01-01

Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) ‘average’ neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously. PMID:19242556
An investigation of the effect of race-based social categorization on adults' recognition of emotion.

PubMed

Reyes, B Nicole; Segal, Shira C; Moulson, Margaret C

2018-01-01

Emotion recognition is important for social interaction and communication, yet previous research has identified a cross-cultural emotion recognition deficit: Recognition is less accurate for emotions expressed by individuals from a cultural group different than one's own. The current study examined whether social categorization based on race, in the absence of cultural differences, influences emotion recognition in a diverse context. South Asian and White Canadians in the Greater Toronto Area completed an emotion recognition task that required them to identify the seven basic emotional expressions when posed by members of the same two groups, allowing us to tease apart the contributions of culture and social group membership. Contrary to our hypothesis, there was no mutual in-group advantage in emotion recognition: Participants were not more accurate at recognizing emotions posed by their respective racial in-groups. Both groups were more accurate at recognizing expressions when posed by South Asian faces, and White participants were more accurate overall compared to South Asian participants. These results suggest that in a diverse environment, categorization based on race alone does not lead to the creation of social out-groups in a way that negatively impacts emotion recognition.
An investigation of the effect of race-based social categorization on adults’ recognition of emotion

PubMed Central

Reyes, B. Nicole; Segal, Shira C.

2018-01-01

Emotion recognition is important for social interaction and communication, yet previous research has identified a cross-cultural emotion recognition deficit: Recognition is less accurate for emotions expressed by individuals from a cultural group different than one’s own. The current study examined whether social categorization based on race, in the absence of cultural differences, influences emotion recognition in a diverse context. South Asian and White Canadians in the Greater Toronto Area completed an emotion recognition task that required them to identify the seven basic emotional expressions when posed by members of the same two groups, allowing us to tease apart the contributions of culture and social group membership. Contrary to our hypothesis, there was no mutual in-group advantage in emotion recognition: Participants were not more accurate at recognizing emotions posed by their respective racial in-groups. Both groups were more accurate at recognizing expressions when posed by South Asian faces, and White participants were more accurate overall compared to South Asian participants. These results suggest that in a diverse environment, categorization based on race alone does not lead to the creation of social out-groups in a way that negatively impacts emotion recognition. PMID:29474367
Food-Induced Emotional Resonance Improves Emotion Recognition.

PubMed

Pandolfi, Elisa; Sacripante, Riccardo; Cardini, Flavia

2016-01-01

The effect of food substances on emotional states has been widely investigated, showing, for example, that eating chocolate is able to reduce negative mood. Here, for the first time, we have shown that the consumption of specific food substances is not only able to induce particular emotional states, but more importantly, to facilitate recognition of corresponding emotional facial expressions in others. Participants were asked to perform an emotion recognition task before and after eating either a piece of chocolate or a small amount of fish sauce-which we expected to induce happiness or disgust, respectively. Our results showed that being in a specific emotional state improves recognition of the corresponding emotional facial expression. Indeed, eating chocolate improved recognition of happy faces, while disgusted expressions were more readily recognized after eating fish sauce. In line with the embodied account of emotion understanding, we suggest that people are better at inferring the emotional state of others when their own emotional state resonates with the observed one.
Food-Induced Emotional Resonance Improves Emotion Recognition

PubMed Central

Pandolfi, Elisa; Sacripante, Riccardo; Cardini, Flavia

2016-01-01

The effect of food substances on emotional states has been widely investigated, showing, for example, that eating chocolate is able to reduce negative mood. Here, for the first time, we have shown that the consumption of specific food substances is not only able to induce particular emotional states, but more importantly, to facilitate recognition of corresponding emotional facial expressions in others. Participants were asked to perform an emotion recognition task before and after eating either a piece of chocolate or a small amount of fish sauce—which we expected to induce happiness or disgust, respectively. Our results showed that being in a specific emotional state improves recognition of the corresponding emotional facial expression. Indeed, eating chocolate improved recognition of happy faces, while disgusted expressions were more readily recognized after eating fish sauce. In line with the embodied account of emotion understanding, we suggest that people are better at inferring the emotional state of others when their own emotional state resonates with the observed one. PMID:27973559
Fixation Patterns of Chinese Participants while Identifying Facial Expressions on Chinese Faces

PubMed Central

Xia, Mu; Li, Xueliu; Zhong, Haiqing; Li, Hong

2017-01-01

Two experiments in this study were designed to explore a model of Chinese fixation with four types of native facial expressions—happy, peaceful, sad, and angry. In both experiments, participants performed an emotion recognition task while their behaviors and eye movements were recorded. Experiment 1 (24 participants, 12 men) demonstrated that both eye fixations and durations were lower for the upper part of the face than for the lower part of the face for all four types of facial expression. Experiment 2 (20 participants, 6 men) repeated this finding and excluded the disturbance of fixation point. These results indicate that Chinese participants demonstrated a superiority effect for the lower part of face while interpreting facial expressions, possibly due to the influence of eastern etiquette culture. PMID:28446896
A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation.

PubMed

Sountsov, Pavel; Santucci, David M; Lisman, John E

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated.
A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation

PubMed Central

Sountsov, Pavel; Santucci, David M.; Lisman, John E.

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated. PMID:22125522
Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

NASA Technical Reports Server (NTRS)

Amador, Jose J (Inventor)

2007-01-01

A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.
The telltale face: possible mechanisms behind defector and cooperator recognition revealed by emotional facial expression metrics.

PubMed

Kovács-Bálint, Zsófia; Bereczkei, Tamás; Hernádi, István

2013-11-01

In this study, we investigated the role of facial cues in cooperator and defector recognition. First, a face image database was constructed from pairs of full face portraits of target subjects taken at the moment of decision-making in a prisoner's dilemma game (PDG) and in a preceding neutral task. Image pairs with no deficiencies (n = 67) were standardized for orientation and luminance. Then, confidence in defector and cooperator recognition was tested with image rating in a different group of lay judges (n = 62). Results indicate that (1) defectors were better recognized (58% vs. 47%), (2) they looked different from cooperators (p < .01), (3) males but not females evaluated the images with a relative bias towards the cooperator category (p < .01), and (4) females were more confident in detecting defectors (p < .05). According to facial microexpression analysis, defection was strongly linked with depressed lower lips and less opened eyes. Significant correlation was found between the intensity of micromimics and the rating of images in the cooperator-defector dimension. In summary, facial expressions can be considered as reliable indicators of momentary social dispositions in the PDG. Females may exhibit an evolutionary-based overestimation bias to detecting social visual cues of the defector face. © 2012 The British Psychological Society.

Recognizing Emotion in Faces: Developmental Effects of Child Abuse and Neglect.

ERIC Educational Resources Information Center

Pollak, Seth D.; Cicchetti, Dante; Hornung, Katherine; Reed, Alex

2000-01-01

Two experiments assessed recognition of emotion among physically abused and neglected preschoolers. Results showed that neglected children had more difficulty discriminating emotional expressions that control or abused children. Abused children displayed response bias for angry facial expressions. Control children viewed discrete emotions as…
Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.
View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation.

PubMed

Leibo, Joel Z; Liao, Qianli; Anselmi, Fabio; Freiwald, Winrich A; Poggio, Tomaso

2017-01-09

The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations, like depth rotations [1, 2]. Current computational models of object recognition, including recent deep-learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3-6]. Here, we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here, we demonstrate that one specific biologically plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli, like faces, at intermediate levels of the architecture and show why it does so. Thus, the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. Copyright © 2017 Elsevier Ltd. All rights reserved.
A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.
Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.
Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.
Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217
A Face Attention Technique for a Robot Able to Interpret Facial Expressions

NASA Astrophysics Data System (ADS)

Simplício, Carlos; Prado, José; Dias, Jorge

Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.
Famous face recognition, face matching, and extraversion.

PubMed

Lander, Karen; Poyarekar, Siddhi

2015-01-01

It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.
Learning to Be (In)Variant: Combining Prior Knowledge and Experience to Infer Orientation Invariance in Object Recognition

ERIC Educational Resources Information Center

Austerweil, Joseph L.; Griffiths, Thomas L.; Palmer, Stephen E.

2017-01-01

How does the visual system recognize images of a novel object after a single observation despite possible variations in the viewpoint of that object relative to the observer? One possibility is comparing the image with a prototype for invariance over a relevant transformation set (e.g., translations and dilations). However, invariance over…
Alterations in neural processing of emotional faces in adolescent anorexia nervosa patients - an event-related potential study.

PubMed

Sfärlea, Anca; Greimel, Ellen; Platt, Belinda; Bartling, Jürgen; Schulte-Körne, Gerd; Dieler, Alica C

2016-09-01

The present study explored the neurophysiological correlates of perception and recognition of emotional facial expressions in adolescent anorexia nervosa (AN) patients using event-related potentials (ERPs). We included 20 adolescent girls with AN and 24 healthy girls and recorded ERPs during a passive viewing task and three active tasks requiring processing of emotional faces in varying processing depths; one of the tasks also assessed emotion recognition abilities behaviourally. Despite the absence of behavioural differences, we found that across all tasks AN patients exhibited a less pronounced early posterior negativity (EPN) in response to all facial expressions compared to controls. The EPN is an ERP component reflecting an automatic, perceptual processing stage which is modulated by the intrinsic salience of a stimulus. Hence, the less pronounced EPN in anorexic girls suggests that they might perceive other people's faces as less intrinsically relevant, i.e. as less "important" than do healthy girls. Copyright © 2016 Elsevier B.V. All rights reserved.
Functional MRI study of diencephalic amnesia in Wernicke-Korsakoff syndrome.

PubMed

Caulo, M; Van Hecke, J; Toma, L; Ferretti, A; Tartaro, A; Colosimo, C; Romani, G L; Uncini, A

2005-07-01

Anterograde amnesia in Wernicke-Korsakoff syndrome is associated with diencephalic lesions, mainly in the anterior thalamic nuclei. Whether diencephalic and temporal lobe amnesias are distinct entities is still not clear. We investigated episodic memory for faces using functional MRI (fMRI) in eight controls and in a 34-year-old man with Wernicke-Korsakoff syndrome and diencephalic lesions but without medial temporal lobe (MTL) involvement at MRI. fMRI was performed with a 1.5 tesla unit. Three dual-choice tasks were employed: (i) face encoding (18 faces were randomly presented three times and subjects were asked to memorize the faces); (ii) face perception (subjects indicated which of two faces matched a third face); and (iii) face recognition (subjects indicated which of two faces belonged to the group they had been asked to memorize during encoding). All activation was greater in the right hemisphere. In controls both the encoding and recognition tasks activated two hippocampal regions (anterior and posterior). The anterior hippocampal region was more activated during recognition. Activation in the prefrontal cortex was greater during recognition. In the subject with Wernicke-Korsakoff syndrome, fMRI did not show hippocampal activation during either encoding or recognition. During recognition, although behavioural data showed defective retrieval, the prefrontal regions were activated as in controls, except for the ventrolateral prefrontal cortex. fMRI activation of the visual cortices and the behavioural score on the perception task indicated that the subject with Wernicke-Korsakoff syndrome perceived the faces, paid attention to the task and demonstrated accurate judgement. In the subject with Wernicke-Korsakoff syndrome, although the anatomical damage does not involve the MTL, the hippocampal memory encoding has been lost, possibly as a consequence of the hippocampal-anterior thalamic axis involvement. Anterograde amnesia could therefore be the expression of damage to an extended hippocampal system, and the distinction between temporal lobe and diencephalic amnesia has limited value. In the subject with Wernicke-Korsakoff syndrome, the preserved dorsolateral prefrontal cortex activation during incorrect recognition suggests that this region is more involved in either the orientation or attention at retrieval than in retrieval. The lack of activation of the prefrontal ventrolateral cortex confirms the role of this area in episodic memory formation.
Reading the mind in the infant eyes: paradoxical effects of oxytocin on neural activity and emotion recognition in watching pictures of infant faces.

PubMed

Voorthuis, Alexandra; Riem, Madelon M E; Van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J

2014-09-11

The neuropeptide oxytocin facilitates parental caregiving and is involved in the processing of infant vocal cues. In this randomized-controlled trial with functional magnetic resonance imaging we examined the influence of intranasally administered oxytocin on neural activity during emotion recognition in infant faces. Blood oxygenation level dependent (BOLD) responses during emotion recognition were measured in 50 women who were administered 16 IU of oxytocin or a placebo. Participants performed an adapted version of the Infant Facial Expressions of Emotions from Looking at Pictures (IFEEL pictures), a task that has been developed to assess the perception and interpretation of infants' facial expressions. Experimentally induced oxytocin levels increased activation in the inferior frontal gyrus (IFG), the middle temporal gyrus (MTG) and the superior temporal gyrus (STG). However, oxytocin decreased performance on the IFEEL picture task. Our findings suggest that oxytocin enhances processing of facial cues of the emotional state of infants on a neural level, but at the same time it may decrease the correct interpretation of infants' facial expressions on a behavior level. This article is part of a Special Issue entitled Oxytocin and Social Behav. © 2013 Published by Elsevier B.V.
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.
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.
Metric invariance in object recognition: a review and further evidence.

PubMed

Cooper, E E; Biederman, I; Hummel, J E

1992-06-01

Phenomenologically, human shape recognition appears to be invariant with changes of orientation in depth (up to parts occlusion), position in the visual field, and size. Recent versions of template theories (e.g., Ullman, 1989; Lowe, 1987) assume that these invariances are achieved through the application of transformations such as rotation, translation, and scaling of the image so that it can be matched metrically to a stored template. Presumably, such transformations would require time for their execution. We describe recent priming experiments in which the effects of a prior brief presentation of an image on its subsequent recognition are assessed. The results of these experiments indicate that the invariance is complete: The magnitude of visual priming (as distinct from name or basic level concept priming) is not affected by a change in position, size, orientation in depth, or the particular lines and vertices present in the image, as long as representations of the same components can be activated. An implemented seven layer neural network model (Hummel & Biederman, 1992) that captures these fundamental properties of human object recognition is described. Given a line drawing of an object, the model activates a viewpoint-invariant structural description of the object, specifying its parts and their interrelations. Visual priming is interpreted as a change in the connection weights for the activation of: a) cells, termed geon feature assemblies (GFAs), that conjoin the output of units that represent invariant, independent properties of a single geon and its relations (such as its type, aspect ratio, relations to other geons), or b) a change in the connection weights by which several GFAs activate a cell representing an object.
Specificity of Facial Expression Labeling Deficits in Childhood Psychopathology

ERIC Educational Resources Information Center

Guyer, Amanda E.; McClure, Erin B.; Adler, Abby D.; Brotman, Melissa A.; Rich, Brendan A.; Kimes, Alane S.; Pine, Daniel S.; Ernst, Monique; Leibenluft, Ellen

2007-01-01

Background: We examined whether face-emotion labeling deficits are illness-specific or an epiphenomenon of generalized impairment in pediatric psychiatric disorders involving mood and behavioral dysregulation. Method: Two hundred fifty-two youths (7-18 years old) completed child and adult facial expression recognition subtests from the Diagnostic…
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…
View-Invariant Gait Recognition Through Genetic Template Segmentation

NASA Astrophysics Data System (ADS)

Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

2017-08-01

Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.
Empathy costs: Negative emotional bias in high empathisers.

PubMed

Chikovani, George; Babuadze, Lasha; Iashvili, Nino; Gvalia, Tamar; Surguladze, Simon

2015-09-30

Excessive empathy has been associated with compassion fatigue in health professionals and caregivers. We investigated an effect of empathy on emotion processing in 137 healthy individuals of both sexes. We tested a hypothesis that high empathy may underlie increased sensitivity to negative emotion recognition which may interact with gender. Facial emotion stimuli comprised happy, angry, fearful, and sad faces presented at different intensities (mild and prototypical) and different durations (500ms and 2000ms). The parameters of emotion processing were represented by discrimination accuracy, response bias and reaction time. We found that higher empathy was associated with better recognition of all emotions. We also demonstrated that higher empathy was associated with response bias towards sad and fearful faces. The reaction time analysis revealed that higher empathy in females was associated with faster (compared with males) recognition of mildly sad faces of brief duration. We conclude that although empathic abilities were providing for advantages in recognition of all facial emotional expressions, the bias towards emotional negativity may potentially carry a risk for empathic distress. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Factorial Invariance of an Integrated Measure of Classroom Sense of Community in Face-to-Face and Online Courses

ERIC Educational Resources Information Center

Cho, YoonJung; Hathcoat, John D.; Bridges, Stacey L.; Mathew, Susan; Bang, Hyeyoung

2014-01-01

The aim of the present study was to develop a more integrated measure of classroom sense of community (SOC) while testing factorial invariance of the measurement structure across face-to-face and online courses. We incorporated two existing SOC measures to capture both context-specific and context-general characteristics of SOC and developed an…
Brief report: Representational momentum for dynamic facial expressions in pervasive developmental disorder.

PubMed

Uono, Shota; Sato, Wataru; Toichi, Motomi

2010-03-01

Individuals with pervasive developmental disorder (PDD) have difficulty with social communication via emotional facial expressions, but behavioral studies involving static images have reported inconsistent findings about emotion recognition. We investigated whether dynamic presentation of facial expression would enhance subjective perception of expressed emotion in 13 individuals with PDD and 13 typically developing controls. We presented dynamic and static emotional (fearful and happy) expressions. Participants were asked to match a changeable emotional face display with the last presented image. The results showed that both groups perceived the last image of dynamic facial expression to be more emotionally exaggerated than the static facial expression. This finding suggests that individuals with PDD have an intact perceptual mechanism for processing dynamic information in another individual's face.
Tryptophan depletion decreases the recognition of fear in female volunteers.

PubMed

Harmer, C J; Rogers, R D; Tunbridge, E; Cowen, P J; Goodwin, G M

2003-06-01

Serotonergic processes have been implicated in the modulation of fear conditioning in humans, postulated to occur at the level of the amygdala. The processing of other fear-relevant cues, such as facial expressions, has also been associated with amygdala function, but an effect of serotonin depletion on these processes has not been assessed. The present study investigated the effects of reducing serotonin function, using acute tryptophan depletion, on the recognition of basic facial expressions of emotions in healthy male and female volunteers. A double-blind between-groups design was used, with volunteers being randomly allocated to receive an amino acid drink specifically lacking tryptophan or a control mixture containing a balanced mixture of these amino acids. Participants were given a facial expression recognition task 5 h after drink administration. This task featured examples of six basic emotions (fear, anger, disgust, surprise, sadness and happiness) that had been morphed between each full emotion and neutral in 10% steps. As a control, volunteers were given a famous face classification task matched in terms of response selection and difficulty level. Tryptophan depletion significantly impaired the recognition of fearful facial expressions in female, but not male, volunteers. This was specific since recognition of other basic emotions was comparable in the two groups. There was also no effect of tryptophan depletion on the classification of famous faces or on subjective state ratings of mood or anxiety. These results confirm a role for serotonin in the processing of fear related cues, and in line with previous findings also suggest greater effects of tryptophan depletion in female volunteers. Although acute tryptophan depletion does not typically affect mood in healthy subjects, the present results suggest that subtle changes in the processing of emotional material may occur with this manipulation of serotonin function.
Blurred image recognition by legendre moment invariants

PubMed Central

Zhang, Hui; Shu, Huazhong; Han, Guo-Niu; Coatrieux, Gouenou; Luo, Limin; Coatrieux, Jean-Louis

2010-01-01

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments. PMID:19933003
The perception and identification of facial emotions in individuals with autism spectrum disorders using the Let's Face It! Emotion Skills Battery.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin S; South, Mikle; McPartland, James C; Kaiser, Martha D; Schultz, Robert T

2012-12-01

Although impaired social-emotional ability is a hallmark of autism spectrum disorder (ASD), the perceptual skills and mediating strategies contributing to the social deficits of autism are not well understood. A perceptual skill that is fundamental to effective social communication is the ability to accurately perceive and interpret facial emotions. To evaluate the expression processing of participants with ASD, we designed the Let's Face It! Emotion Skills Battery (LFI! Battery), a computer-based assessment composed of three subscales measuring verbal and perceptual skills implicated in the recognition of facial emotions. We administered the LFI! Battery to groups of participants with ASD and typically developing control (TDC) participants that were matched for age and IQ. On the Name Game labeling task, participants with ASD (N = 68) performed on par with TDC individuals (N = 66) in their ability to name the facial emotions of happy, sad, disgust and surprise and were only impaired in their ability to identify the angry expression. On the Matchmaker Expression task that measures the recognition of facial emotions across different facial identities, the ASD participants (N = 66) performed reliably worse than TDC participants (N = 67) on the emotions of happy, sad, disgust, frighten and angry. In the Parts-Wholes test of perceptual strategies of expression, the TDC participants (N = 67) displayed more holistic encoding for the eyes than the mouths in expressive faces whereas ASD participants (N = 66) exhibited the reverse pattern of holistic recognition for the mouth and analytic recognition of the eyes. In summary, findings from the LFI! Battery show that participants with ASD were able to label the basic facial emotions (with the exception of angry expression) on par with age- and IQ-matched TDC participants. However, participants with ASD were impaired in their ability to generalize facial emotions across different identities and showed a tendency to recognize the mouth feature holistically and the eyes as isolated parts. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.
Local visual perception bias in children with high-functioning autism spectrum disorders; do we have the whole picture?

PubMed

Falkmer, Marita; Black, Melissa; Tang, Julia; Fitzgerald, Patrick; Girdler, Sonya; Leung, Denise; Ordqvist, Anna; Tan, Tele; Jahan, Ishrat; Falkmer, Torbjorn

2016-01-01

While local bias in visual processing in children with autism spectrum disorders (ASD) has been reported to result in difficulties in recognizing faces and facially expressed emotions, but superior ability in disembedding figures, associations between these abilities within a group of children with and without ASD have not been explored. Possible associations in performance on the Visual Perception Skills Figure-Ground test, a face recognition test and an emotion recognition test were investigated within 25 8-12-years-old children with high-functioning autism/Asperger syndrome, and in comparison to 33 typically developing children. Analyses indicated a weak positive correlation between accuracy in Figure-Ground recognition and emotion recognition. No other correlation estimates were significant. These findings challenge both the enhanced perceptual function hypothesis and the weak central coherence hypothesis, and accentuate the importance of further scrutinizing the existance and nature of local visual bias in ASD.
Functional architecture of visual emotion recognition ability: A latent variable approach.

PubMed

Lewis, Gary J; Lefevre, Carmen E; Young, Andrew W

2016-05-01

Emotion recognition has been a focus of considerable attention for several decades. However, despite this interest, the underlying structure of individual differences in emotion recognition ability has been largely overlooked and thus is poorly understood. For example, limited knowledge exists concerning whether recognition ability for one emotion (e.g., disgust) generalizes to other emotions (e.g., anger, fear). Furthermore, it is unclear whether emotion recognition ability generalizes across modalities, such that those who are good at recognizing emotions from the face, for example, are also good at identifying emotions from nonfacial cues (such as cues conveyed via the body). The primary goal of the current set of studies was to address these questions through establishing the structure of individual differences in visual emotion recognition ability. In three independent samples (Study 1: n = 640; Study 2: n = 389; Study 3: n = 303), we observed that the ability to recognize visually presented emotions is based on different sources of variation: a supramodal emotion-general factor, supramodal emotion-specific factors, and face- and within-modality emotion-specific factors. In addition, we found evidence that general intelligence and alexithymia were associated with supramodal emotion recognition ability. Autism-like traits, empathic concern, and alexithymia were independently associated with face-specific emotion recognition ability. These results (a) provide a platform for further individual differences research on emotion recognition ability, (b) indicate that differentiating levels within the architecture of emotion recognition ability is of high importance, and (c) show that the capacity to understand expressions of emotion in others is linked to broader affective and cognitive processes. (c) 2016 APA, all rights reserved).
Facilitation of face recognition through the retino-tectal pathway.

PubMed

Nakano, Tamami; Higashida, Noriko; Kitazawa, Shigeru

2013-08-01

Humans can shift their gazes faster to human faces than to non-face targets during a task in which they are required to choose between face and non-face targets. However, it remains unclear whether a direct projection from the retina to the superior colliculus is specifically involved in this facilitated recognition of faces. To address this question, we presented a pair of face and non-face pictures to participants modulated in greyscale (luminance-defined stimuli) in one condition and modulated in a blue-yellow scale (S-cone-isolating stimuli) in another. The information of the S-cone-isolating stimuli is conveyed through the retino-geniculate pathway rather than the retino-tectal pathway. For the luminance stimuli, the reaction time was shorter towards a face than towards a non-face target. The facilitatory effect while choosing a face disappeared with the S-cone stimuli. Moreover, fearful faces elicited a significantly larger facilitatory effect relative to neutral faces, when the face (with or without emotion) and non-face stimuli were presented in greyscale. The effect of emotional expressions disappeared with the S-cone stimuli. In contrast to the S-cone stimuli, the face facilitatory effect was still observed with negated stimuli that were prepared by reversing the polarity of the original colour pictures and looked as unusual as the S-cone stimuli but still contained luminance information. These results demonstrate that the face facilitatory effect requires the facial and emotional information defined by luminance, suggesting that the luminance information conveyed through the retino-tectal pathway is responsible for the faster recognition of human faces. Copyright © 2013 Elsevier Ltd. All rights reserved.
Non-accidental properties, metric invariance, and encoding by neurons in a model of ventral stream visual object recognition, VisNet.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2018-05-01

When objects transform into different views, some properties are maintained, such as whether the edges are convex or concave, and these non-accidental properties are likely to be important in view-invariant object recognition. The metric properties, such as the degree of curvature, may change with different views, and are less likely to be useful in object recognition. It is shown that in a model of invariant visual object recognition in the ventral visual stream, VisNet, non-accidental properties are encoded much more than metric properties by neurons. Moreover, it is shown how with the temporal trace rule training in VisNet, non-accidental properties of objects become encoded by neurons, and how metric properties are treated invariantly. We also show how VisNet can generalize between different objects if they have the same non-accidental property, because the metric properties are likely to overlap. VisNet is a 4-layer unsupervised model of visual object recognition trained by competitive learning that utilizes a temporal trace learning rule to implement the learning of invariance using views that occur close together in time. A second crucial property of this model of object recognition is, when neurons in the level corresponding to the inferior temporal visual cortex respond selectively to objects, whether neurons in the intermediate layers can respond to combinations of features that may be parts of two or more objects. In an investigation using the four sides of a square presented in every possible combination, it was shown that even though different layer 4 neurons are tuned to encode each feature or feature combination orthogonally, neurons in the intermediate layers can respond to features or feature combinations present is several objects. This property is an important part of the way in which high capacity can be achieved in the four-layer ventral visual cortical pathway. These findings concerning non-accidental properties and the use of neurons in intermediate layers of the hierarchy help to emphasise fundamental underlying principles of the computations that may be implemented in the ventral cortical visual stream used in object recognition. Copyright © 2018 Elsevier Inc. All rights reserved.
Memory deficits for facial identity in patients with amnestic mild cognitive impairment (MCI).

PubMed

Savaskan, Egemen; Summermatter, Daniel; Schroeder, Clemens; Schächinger, Hartmut

2018-01-01

Faces are among the most relevant social stimuli revealing an encounter's identity and actual emotional state. Deficits in facial recognition may be an early sign of cognitive decline leading to social deficits. The main objective of the present study is to investigate if individuals with amnestic mild cognitive impairment show recognition deficits in facial identity. Thirty-seven individuals with amnestic mild cognitive impairment, multiple-domain (15 female; age: 75±8 yrs.) and forty-one healthy volunteers (24 female; age 71±6 yrs.) participated. All participants completed a human portrait memory test presenting unfamiliar faces with happy and angry emotional expressions. Five and thirty minutes later, old and new neutral faces were presented, and discrimination sensitivity (d') and response bias (C) were assessed as signal detection parameters of cued facial identity recognition. Memory performance was lower in amnestic mild cognitive impairment as compared to control subjects, mainly because of an altered response bias towards an increased false alarm rate (favoring false OLD ascription of NEW items). In both groups, memory performance declined between the early and later testing session, and was always better for acquired happy than angry faces. Facial identity memory is impaired in patients with amnestic mild cognitive impairment. Liberalization of the response bias may reflect a socially motivated compensatory mechanism maintaining an almost identical recognition hit rate of OLD faces in individuals with amnestic mild cognitive impairment.
Working Memory Impairment in People with Williams Syndrome: Effects of Delay, Task and Stimuli

PubMed Central

O'Hearn, Kirsten; Courtney, Susan; Street, Whitney; Landau, Barbara

2009-01-01

Williams syndrome (WS) is a neurodevelopmental disorder associated with impaired visuospatial representations subserved by the dorsal stream and relatively strong object recognition abilities subserved by the ventral stream. There is conflicting evidence on whether this uneven pattern extends to working memory (WM) in WS. The present studies provide a new perspective, testing WM for a single stimulus using a delayed recognition paradigm in individuals with WS and typically developing children matched for mental age (MA matches). In three experiments, participants judged whether a second stimulus ‘matched’ an initial sample, either in location or identity. We first examined memory for faces, houses and locations using a 5 s delay (Experiment 1) and a 2 s delay (Experiment 2). We then tested memory for human faces, houses, cat faces, and shoes with a 2 s delay using a new set of stimuli that were better controlled for expression, hairline and orientation (Experiment 3). With the 5 s delay (Experiment 1), the WS group was impaired overall compared to MA matches. While participants with WS tended to perform more poorly than MA matches with the 2 s delay, they also exhibited an uneven profile compared to MA matches. Face recognition was relatively preserved in WS with friendly faces (Experiment 2) but not when the faces had a neutral expression and were less natural looking (Experiment 3). Experiment 3 indicated that memory for object identity was relatively stronger than memory for location in WS. These findings reveal an overall WM impairment in WS that can be overcome under some conditions. Abnormalities in the parietal lobe/dorsal stream in WS may damage not only the representation of spatial location but also may impact WM for visual stimuli more generally. PMID:19084315
Working memory impairment in people with Williams syndrome: effects of delay, task and stimuli.

PubMed

O'Hearn, Kirsten; Courtney, Susan; Street, Whitney; Landau, Barbara

2009-04-01

Williams syndrome (WS) is a neurodevelopmental disorder associated with impaired visuospatial representations subserved by the dorsal stream and relatively strong object recognition abilities subserved by the ventral stream. There is conflicting evidence on whether this uneven pattern in WS extends to working memory (WM). The present studies provide a new perspective, testing WM for a single stimulus using a delayed recognition paradigm in individuals with WS and typically developing children matched for mental age (MA matches). In three experiments, participants judged whether a second stimulus 'matched' an initial sample, either in location or identity. We first examined memory for faces, houses and locations using a 5s delay (Experiment 1) and a 2s delay (Experiment 2). We then tested memory for human faces, houses, cat faces, and shoes with a 2s delay using a new set of stimuli that were better controlled for expression, hairline and orientation (Experiment 3). With the 5s delay (Experiment 1), the WS group was impaired overall compared to MA matches. While participants with WS tended to perform more poorly than MA matches with the 2s delay, they also exhibited an uneven profile compared to MA matches. Face recognition was relatively preserved in WS with friendly faces (Experiment 2) but not when the faces had a neutral expression and were less natural looking (Experiment 3). Experiment 3 indicated that memory for object identity was relatively stronger than memory for location in WS. These findings reveal an overall WM impairment in WS that can be overcome under some conditions. Abnormalities in the parietal lobe/dorsal stream in WS may damage not only the representation of spatial location but may also impact WM for visual stimuli more generally.
Emotion Recognition - the need for a complete analysis of the phenomenon of expression formation

NASA Astrophysics Data System (ADS)

Bobkowska, Katarzyna; Przyborski, Marek; Skorupka, Dariusz

2018-01-01

This article shows how complex emotions are. This has been proven by the analysis of the changes that occur on the face. The authors present the problem of image analysis for the purpose of identifying emotions. In addition, they point out the importance of recording the phenomenon of the development of emotions on the human face with the use of high-speed cameras, which allows the detection of micro expression. The work that was prepared for this article was based on analyzing the parallax pair correlation coefficients for specific faces. In the article authors proposed to divide the facial image into 8 characteristic segments. With this approach, it was confirmed that at different moments of emotion the pace of expression and the maximum change characteristic of a particular emotion, for each part of the face is different.
Adolescents' ability to read different emotional faces relates to their history of maltreatment and type of psychopathology.

PubMed

Leist, Tatyana; Dadds, Mark R

2009-04-01

Emotional processing styles appear to characterize various forms of psychopathology and environmental adversity in children. For example, autistic, anxious, high- and low-emotion conduct problem children, and children who have been maltreated, all appear to show specific deficits and strengths in recognizing the facial expressions of emotions. Until now, the relationships between emotion recognition, antisocial behaviour, emotional problems, callous-unemotional (CU) traits and early maltreatment have never been assessed simultaneously in one study, and the specific associations of emotion recognition to maltreatment and child characteristics are therefore unknown. We examined facial-emotion processing in a sample of 23 adolescents selected for high-risk status on the variables of interest. As expected, maltreatment and child characteristics showed unique associations. CU traits were uniquely related to impairments in fear recognition. Antisocial behaviour was uniquely associated with better fear recognition, but impaired anger recognition. Emotional problems were associated with better recognition of anger and sadness, but lower recognition of neutral faces. Maltreatment was predictive of superior recognition of fear and sadness. The findings are considered in terms of social information-processing theories of psychopathology. Implications for clinical interventions are discussed.
Development of Training/Self-Recognizing Tools for Disability Students Using a Face Expression Recognition Sensor and a Smart-Watch

ERIC Educational Resources Information Center

Kawada, Taku; Ando, Akinobu; Saito, Hirotaka; Uekida, Jun; Nagai, Nobuyuki; Takeshima, Hisashi; Davis, Darold

2016-01-01

In this paper, we developed two kinds of application software run on a mobile/wearable device for autistic spectrum disorder students, intellectual disability students, or physically challenged. One of the applications is expression detector/evaluator using a smartphone and a small expression sensor for social skill training. This sensor can…
Brain systems for assessing the affective value of faces

PubMed Central

Said, Christopher P.; Haxby, James V.; Todorov, Alexander

2011-01-01

Cognitive neuroscience research on facial expression recognition and face evaluation has proliferated over the past 15 years. Nevertheless, large questions remain unanswered. In this overview, we discuss the current understanding in the field, and describe what is known and what remains unknown. In §2, we describe three types of behavioural evidence that the perception of traits in neutral faces is related to the perception of facial expressions, and may rely on the same mechanisms. In §3, we discuss cortical systems for the perception of facial expressions, and argue for a partial segregation of function in the superior temporal sulcus and the fusiform gyrus. In §4, we describe the current understanding of how the brain responds to emotionally neutral faces. To resolve some of the inconsistencies in the literature, we perform a large group analysis across three different studies, and argue that one parsimonious explanation of prior findings is that faces are coded in terms of their typicality. In §5, we discuss how these two lines of research—perception of emotional expressions and face evaluation—could be integrated into a common, cognitive neuroscience framework. PMID:21536552
Perception of biological motion from size-invariant body representations.

PubMed

Lappe, Markus; Wittinghofer, Karin; de Lussanet, Marc H E

2015-01-01

The visual recognition of action is one of the socially most important and computationally demanding capacities of the human visual system. It combines visual shape recognition with complex non-rigid motion perception. Action presented as a point-light animation is a striking visual experience for anyone who sees it for the first time. Information about the shape and posture of the human body is sparse in point-light animations, but it is essential for action recognition. In the posturo-temporal filter model of biological motion perception posture information is picked up by visual neurons tuned to the form of the human body before body motion is calculated. We tested whether point-light stimuli are processed through posture recognition of the human body form by using a typical feature of form recognition, namely size invariance. We constructed a point-light stimulus that can only be perceived through a size-invariant mechanism. This stimulus changes rapidly in size from one image to the next. It thus disrupts continuity of early visuo-spatial properties but maintains continuity of the body posture representation. Despite this massive manipulation at the visuo-spatial level, size-changing point-light figures are spontaneously recognized by naive observers, and support discrimination of human body motion.
Social Experience Does Not Abolish Cultural Diversity in Eye Movements

PubMed Central

Kelly, David J.; Jack, Rachael E.; Miellet, Sébastien; De Luca, Emanuele; Foreman, Kay; Caldara, Roberto

2011-01-01

Adults from Eastern (e.g., China) and Western (e.g., USA) cultural groups display pronounced differences in a range of visual processing tasks. For example, the eye movement strategies used for information extraction during a variety of face processing tasks (e.g., identification and facial expressions of emotion categorization) differs across cultural groups. Currently, many of the differences reported in previous studies have asserted that culture itself is responsible for shaping the way we process visual information, yet this has never been directly investigated. In the current study, we assessed the relative contribution of genetic and cultural factors by testing face processing in a population of British Born Chinese adults using face recognition and expression classification tasks. Contrary to predictions made by the cultural differences framework, the majority of British Born Chinese adults deployed “Eastern” eye movement strategies, while approximately 25% of participants displayed “Western” strategies. Furthermore, the cultural eye movement strategies used by individuals were consistent across recognition and expression tasks. These findings suggest that “culture” alone cannot straightforwardly account for diversity in eye movement patterns. Instead a more complex understanding of how the environment and individual experiences can influence the mechanisms that govern visual processing is required. PMID:21886626
IntraFace

PubMed Central

De la Torre, Fernando; Chu, Wen-Sheng; Xiong, Xuehan; Vicente, Francisco; Ding, Xiaoyu; Cohn, Jeffrey

2016-01-01

Within the last 20 years, there has been an increasing interest in the computer vision community in automated facial image analysis algorithms. This has been driven by applications in animation, market research, autonomous-driving, surveillance, and facial editing among others. To date, there exist several commercial packages for specific facial image analysis tasks such as facial expression recognition, facial attribute analysis or face tracking. However, free and easy-to-use software that incorporates all these functionalities is unavailable. This paper presents IntraFace (IF), a publicly-available software package for automated facial feature tracking, head pose estimation, facial attribute recognition, and facial expression analysis from video. In addition, IFincludes a newly develop technique for unsupervised synchrony detection to discover correlated facial behavior between two or more persons, a relatively unexplored problem in facial image analysis. In tests, IF achieved state-of-the-art results for emotion expression and action unit detection in three databases, FERA, CK+ and RU-FACS; measured audience reaction to a talk given by one of the authors; and discovered synchrony for smiling in videos of parent-infant interaction. IF is free of charge for academic use at http://www.humansensing.cs.cmu.edu/intraface/. PMID:27346987
IntraFace.

PubMed

De la Torre, Fernando; Chu, Wen-Sheng; Xiong, Xuehan; Vicente, Francisco; Ding, Xiaoyu; Cohn, Jeffrey

2015-05-01

Within the last 20 years, there has been an increasing interest in the computer vision community in automated facial image analysis algorithms. This has been driven by applications in animation, market research, autonomous-driving, surveillance, and facial editing among others. To date, there exist several commercial packages for specific facial image analysis tasks such as facial expression recognition, facial attribute analysis or face tracking. However, free and easy-to-use software that incorporates all these functionalities is unavailable. This paper presents IntraFace (IF), a publicly-available software package for automated facial feature tracking, head pose estimation, facial attribute recognition, and facial expression analysis from video. In addition, IFincludes a newly develop technique for unsupervised synchrony detection to discover correlated facial behavior between two or more persons, a relatively unexplored problem in facial image analysis. In tests, IF achieved state-of-the-art results for emotion expression and action unit detection in three databases, FERA, CK+ and RU-FACS; measured audience reaction to a talk given by one of the authors; and discovered synchrony for smiling in videos of parent-infant interaction. IF is free of charge for academic use at http://www.humansensing.cs.cmu.edu/intraface/.

Recognizing Action Units for Facial Expression Analysis

PubMed Central

Tian, Ying-li; Kanade, Takeo; Cohn, Jeffrey F.

2010-01-01

Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more often communicated by changes in one or a few discrete facial features. In this paper, we develop an Automatic Face Analysis (AFA) system to analyze facial expressions based on both permanent facial features (brows, eyes, mouth) and transient facial features (deepening of facial furrows) in a nearly frontal-view face image sequence. The AFA system recognizes fine-grained changes in facial expression into action units (AUs) of the Facial Action Coding System (FACS), instead of a few prototypic expressions. Multistate face and facial component models are proposed for tracking and modeling the various facial features, including lips, eyes, brows, cheeks, and furrows. During tracking, detailed parametric descriptions of the facial features are extracted. With these parameters as the inputs, a group of action units (neutral expression, six upper face AUs and 10 lower face AUs) are recognized whether they occur alone or in combinations. The system has achieved average recognition rates of 96.4 percent (95.4 percent if neutral expressions are excluded) for upper face AUs and 96.7 percent (95.6 percent with neutral expressions excluded) for lower face AUs. The generalizability of the system has been tested by using independent image databases collected and FACS-coded for ground-truth by different research teams. PMID:25210210
Sparse Feature Extraction for Pose-Tolerant Face Recognition.

PubMed

Abiantun, Ramzi; Prabhu, Utsav; Savvides, Marios

2014-10-01

Automatic face recognition performance has been steadily improving over years of research, however it remains significantly affected by a number of factors such as illumination, pose, expression, resolution and other factors that can impact matching scores. The focus of this paper is the pose problem which remains largely overlooked in most real-world applications. Specifically, we focus on one-to-one matching scenarios where a query face image of a random pose is matched against a set of gallery images. We propose a method that relies on two fundamental components: (a) A 3D modeling step to geometrically correct the viewpoint of the face. For this purpose, we extend a recent technique for efficient synthesis of 3D face models called 3D Generic Elastic Model. (b) A sparse feature extraction step using subspace modeling and ℓ1-minimization to induce pose-tolerance in coefficient space. This in return enables the synthesis of an equivalent frontal-looking face, which can be used towards recognition. We show significant performance improvements in verification rates compared to commercial matchers, and also demonstrate the resilience of the proposed method with respect to degrading input quality. We find that the proposed technique is able to match non-frontal images to other non-frontal images of varying angles.
Emotion Recognition Deficits in Schizophrenia-Spectrum Disorders and Psychotic Bipolar Disorder: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Study

PubMed Central

Ruocco, Anthony C.; Reilly, James L.; Rubin, Leah H.; Daros, Alex R.; Gershon, Elliot S.; Tamminga, Carol A.; Pearlson, Godfrey D.; Hill, S. Kristian; Keshavan, Matcheri S.; Gur, Ruben C.; Sweeney, John A.

2014-01-01

Background Difficulty recognizing facial emotions is an important social-cognitive deficit associated with psychotic disorders. It also may reflect a familial risk for psychosis in schizophrenia-spectrum disorders and bipolar disorder. Objective The objectives of this study from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were to: 1) compare emotion recognition deficits in schizophrenia, schizoaffective disorder and bipolar disorder with psychosis, 2) determine the familiality of emotion recognition deficits across these disorders, and 3) evaluate emotion recognition deficits in nonpsychotic relatives with and without elevated Cluster A and Cluster B personality disorder traits. Method Participants included probands with schizophrenia (n=297), schizoaffective disorder (depressed type, n=61; bipolar type, n=69), bipolar disorder with psychosis (n=248), their first-degree relatives (n=332, n=69, n=154, and n=286, respectively) and healthy controls (n=380). All participants completed the Penn Emotion Recognition Test, a standardized measure of facial emotion recognition assessing four basic emotions (happiness, sadness, anger and fear) and neutral expressions (no emotion). Results Compared to controls, emotion recognition deficits among probands increased progressively from bipolar disorder to schizoaffective disorder to schizophrenia. Proband and relative groups showed similar deficits perceiving angry and neutral faces, whereas deficits on fearful, happy and sad faces were primarily isolated to schizophrenia probands. Even non-psychotic relatives without elevated Cluster A or Cluster B personality disorder traits showed deficits on neutral and angry faces. Emotion recognition ability was moderately familial only in schizophrenia families. Conclusions Emotion recognition deficits are prominent but somewhat different across psychotic disorders. These deficits are reflected to a lesser extent in relatives, particularly on angry and neutral faces. Deficits were evident in non-psychotic relatives even without elevated personality disorder traits. Deficits in facial emotion recognition may reflect an important social-cognitive deficit in patients with psychotic disorders. PMID:25052782
Emotion recognition deficits in schizophrenia-spectrum disorders and psychotic bipolar disorder: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study.

PubMed

Ruocco, Anthony C; Reilly, James L; Rubin, Leah H; Daros, Alex R; Gershon, Elliot S; Tamminga, Carol A; Pearlson, Godfrey D; Hill, S Kristian; Keshavan, Matcheri S; Gur, Ruben C; Sweeney, John A

2014-09-01

Difficulty recognizing facial emotions is an important social-cognitive deficit associated with psychotic disorders. It also may reflect a familial risk for psychosis in schizophrenia-spectrum disorders and bipolar disorder. The objectives of this study from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were to: 1) compare emotion recognition deficits in schizophrenia, schizoaffective disorder and bipolar disorder with psychosis, 2) determine the familiality of emotion recognition deficits across these disorders, and 3) evaluate emotion recognition deficits in nonpsychotic relatives with and without elevated Cluster A and Cluster B personality disorder traits. Participants included probands with schizophrenia (n=297), schizoaffective disorder (depressed type, n=61; bipolar type, n=69), bipolar disorder with psychosis (n=248), their first-degree relatives (n=332, n=69, n=154, and n=286, respectively) and healthy controls (n=380). All participants completed the Penn Emotion Recognition Test, a standardized measure of facial emotion recognition assessing four basic emotions (happiness, sadness, anger and fear) and neutral expressions (no emotion). Compared to controls, emotion recognition deficits among probands increased progressively from bipolar disorder to schizoaffective disorder to schizophrenia. Proband and relative groups showed similar deficits perceiving angry and neutral faces, whereas deficits on fearful, happy and sad faces were primarily isolated to schizophrenia probands. Even non-psychotic relatives without elevated Cluster A or Cluster B personality disorder traits showed deficits on neutral and angry faces. Emotion recognition ability was moderately familial only in schizophrenia families. Emotion recognition deficits are prominent but somewhat different across psychotic disorders. These deficits are reflected to a lesser extent in relatives, particularly on angry and neutral faces. Deficits were evident in non-psychotic relatives even without elevated personality disorder traits. Deficits in facial emotion recognition may reflect an important social-cognitive deficit in patients with psychotic disorders. Copyright © 2014 Elsevier B.V. All rights reserved.
Face-selective regions differ in their ability to classify facial expressions

PubMed Central

Zhang, Hui; Japee, Shruti; Nolan, Rachel; Chu, Carlton; Liu, Ning; Ungerleider, Leslie G

2016-01-01

Recognition of facial expressions is crucial for effective social interactions. Yet, the extent to which the various face-selective regions in the human brain classify different facial expressions remains unclear. We used functional magnetic resonance imaging (fMRI) and support vector machine pattern classification analysis to determine how well face-selective brain regions are able to decode different categories of facial expression. Subjects participated in a slow event-related fMRI experiment in which they were shown 32 face pictures, portraying four different expressions: neutral, fearful, angry, and happy and belonging to eight different identities. Our results showed that only the amygdala and the posterior superior temporal sulcus (STS) were able to accurately discriminate between these expressions, albeit in different ways: The amygdala discriminated fearful faces from non-fearful faces, whereas STS discriminated neutral from emotional (fearful, angry and happy) faces. In contrast to these findings on the classification of emotional expression, only the fusiform face area (FFA) and anterior inferior temporal cortex (aIT) could discriminate among the various facial identities. Further, the amygdala and STS were better than FFA and aIT at classifying expression, while FFA and aIT were better than the amygdala and STS at classifying identity. Taken together, our findings indicate that the decoding of facial emotion and facial identity occurs in different neural substrates: the amygdala and STS for the former and FFA and aIT for the latter. PMID:26826513
Face-selective regions differ in their ability to classify facial expressions.

PubMed

Zhang, Hui; Japee, Shruti; Nolan, Rachel; Chu, Carlton; Liu, Ning; Ungerleider, Leslie G

2016-04-15

Recognition of facial expressions is crucial for effective social interactions. Yet, the extent to which the various face-selective regions in the human brain classify different facial expressions remains unclear. We used functional magnetic resonance imaging (fMRI) and support vector machine pattern classification analysis to determine how well face-selective brain regions are able to decode different categories of facial expression. Subjects participated in a slow event-related fMRI experiment in which they were shown 32 face pictures, portraying four different expressions: neutral, fearful, angry, and happy and belonging to eight different identities. Our results showed that only the amygdala and the posterior superior temporal sulcus (STS) were able to accurately discriminate between these expressions, albeit in different ways: the amygdala discriminated fearful faces from non-fearful faces, whereas STS discriminated neutral from emotional (fearful, angry and happy) faces. In contrast to these findings on the classification of emotional expression, only the fusiform face area (FFA) and anterior inferior temporal cortex (aIT) could discriminate among the various facial identities. Further, the amygdala and STS were better than FFA and aIT at classifying expression, while FFA and aIT were better than the amygdala and STS at classifying identity. Taken together, our findings indicate that the decoding of facial emotion and facial identity occurs in different neural substrates: the amygdala and STS for the former and FFA and aIT for the latter. Published by Elsevier Inc.
Integrating conventional and inverse representation for face recognition.

PubMed

Xu, Yong; Li, Xuelong; Yang, Jian; Lai, Zhihui; Zhang, David

2014-10-01

Representation-based classification methods are all constructed on the basis of the conventional representation, which first expresses the test sample as a linear combination of the training samples and then exploits the deviation between the test sample and the expression result of every class to perform classification. However, this deviation does not always well reflect the difference between the test sample and each class. With this paper, we propose a novel representation-based classification method for face recognition. This method integrates conventional and the inverse representation-based classification for better recognizing the face. It first produces conventional representation of the test sample, i.e., uses a linear combination of the training samples to represent the test sample. Then it obtains the inverse representation, i.e., provides an approximation representation of each training sample of a subject by exploiting the test sample and training samples of the other subjects. Finally, the proposed method exploits the conventional and inverse representation to generate two kinds of scores of the test sample with respect to each class and combines them to recognize the face. The paper shows the theoretical foundation and rationale of the proposed method. Moreover, this paper for the first time shows that a basic nature of the human face, i.e., the symmetry of the face can be exploited to generate new training and test samples. As these new samples really reflect some possible appearance of the face, the use of them will enable us to obtain higher accuracy. The experiments show that the proposed conventional and inverse representation-based linear regression classification (CIRLRC), an improvement to linear regression classification (LRC), can obtain very high accuracy and greatly outperforms the naive LRC and other state-of-the-art conventional representation based face recognition methods. The accuracy of CIRLRC can be 10% greater than that of LRC.
A model for size- and rotation-invariant pattern processing in the visual system.

PubMed

Reitboeck, H J; Altmann, J

1984-01-01

The mapping of retinal space onto the striate cortex of some mammals can be approximated by a log-polar function. It has been proposed that this mapping is of functional importance for scale- and rotation-invariant pattern recognition in the visual system. An exact log-polar transform converts centered scaling and rotation into translations. A subsequent translation-invariant transform, such as the absolute value of the Fourier transform, thus generates overall size- and rotation-invariance. In our model, the translation-invariance is realized via the R-transform. This transform can be executed by simple neural networks, and it does not require the complex computations of the Fourier transform, used in Mellin-transform size-invariance models. The logarithmic space distortion and differentiation in the first processing stage of the model is realized via "Mexican hat" filters whose diameter increases linearly with eccentricity, similar to the characteristics of the receptive fields of retinal ganglion cells. Except for some special cases, the model can explain object recognition independent of size, orientation and position. Some general problems of Mellin-type size-invariance models-that also apply to our model-are discussed.
A new selective developmental deficit: Impaired object recognition with normal face recognition.

PubMed

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual recognition. Copyright © 2010 Elsevier Srl. All rights reserved.
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.
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 analysis of philogenetically old behavioral patterns like the facial expressions of emotions. PMID:28690565
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 analysis of philogenetically old behavioral patterns like the facial expressions of emotions.
Prevalence of face recognition deficits in middle childhood.

PubMed

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

2017-02-01

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

PubMed

Palermo, Romina; Willis, Megan L; Rivolta, Davide; McKone, Elinor; Wilson, C Ellie; Calder, Andrew J

2011-04-01

We test 12 individuals with congenital prosopagnosia (CP), who replicate a common pattern of showing severe difficulty in recognising facial identity in conjunction with normal recognition of facial expressions (both basic and 'social'). Strength of holistic processing was examined using standard expression composite and identity composite tasks. Compared to age- and sex-matched controls, group analyses demonstrated that CPs showed weaker holistic processing, for both expression and identity information. Implications are (a) normal expression recognition in CP can derive from compensatory strategies (e.g., over-reliance on non-holistic cues to expression); (b) the split between processing of expression and identity information may take place after a common stage of holistic processing; and (c) contrary to a recent claim, holistic processing of identity is functionally involved in face identification ability. Copyright © 2011 Elsevier Ltd. All rights reserved.
Impaired holistic coding of facial expression and facial identity in congenital prosopagnosia

PubMed Central

Palermo, Romina; Willis, Megan L.; Rivolta, Davide; McKone, Elinor; Wilson, C. Ellie; Calder, Andrew J.

2011-01-01

We test 12 individuals with congenital prosopagnosia (CP), who replicate a common pattern of showing severe difficulty in recognising facial identity in conjunction with normal recognition of facial expressions (both basic and ‘social’). Strength of holistic processing was examined using standard expression composite and identity composite tasks. Compared to age- and sex-matched controls, group analyses demonstrated that CPs showed weaker holistic processing, for both expression and identity information. Implications are (a) normal expression recognition in CP can derive from compensatory strategies (e.g., over-reliance on non-holistic cues to expression); (b) the split between processing of expression and identity information may take place after a common stage of holistic processing; and (c) contrary to a recent claim, holistic processing of identity is functionally involved in face identification ability. PMID:21333662
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
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.
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.
Super-recognition in development: A case study of an adolescent with extraordinary face recognition skills.

PubMed

Bennetts, Rachel J; Mole, Joseph; Bate, Sarah

2017-09-01

Face recognition abilities vary widely. While face recognition deficits have been reported in children, it is unclear whether superior face recognition skills can be encountered during development. This paper presents O.B., a 14-year-old female with extraordinary face recognition skills: a "super-recognizer" (SR). O.B. demonstrated exceptional face-processing skills across multiple tasks, with a level of performance that is comparable to adult SRs. Her superior abilities appear to be specific to face identity: She showed an exaggerated face inversion effect and her superior abilities did not extend to object processing or non-identity aspects of face recognition. Finally, an eye-movement task demonstrated that O.B. spent more time than controls examining the nose - a pattern previously reported in adult SRs. O.B. is therefore particularly skilled at extracting and using identity-specific facial cues, indicating that face and object recognition are dissociable during development, and that super recognition can be detected in adolescence.
Optimal faces for gender and expression: a new technique for measuring dynamic templates used in face perception.

PubMed

Poirier, Frédéric J A M; Faubert, Jocelyn

2012-06-22

Facial expressions are important for human communications. Face perception studies often measure the impact of major degradation (e.g., noise, inversion, short presentations, masking, alterations) on natural expression recognition performance. Here, we introduce a novel face perception technique using rich and undegraded stimuli. Participants modified faces to create optimal representations of given expressions. Using sliders, participants adjusted 53 face components (including 37 dynamic) including head, eye, eyebrows, mouth, and nose shape and position. Data was collected from six participants and 10 conditions (six emotions + pain + gender + neutral). Some expressions had unique features (e.g., frown for anger, upward-curved mouth for happiness), whereas others had shared features (e.g., open eyes and mouth for surprise and fear). Happiness was different from other emotions. Surprise was different from other emotions except fear. Weighted sum morphing provides acceptable stimuli for gender-neutral and dynamic stimuli. Many features were correlated, including (1) head size with internal feature sizes as related to gender, (2) internal feature scaling, and (3) eyebrow height and eye openness as related to surprise and fear. These findings demonstrate the method's validity for measuring the optimal facial expressions, which we argue is a more direct measure of their internal representations.

The Odor Context Facilitates the Perception of Low-Intensity Facial Expressions of Emotion

PubMed Central

Leleu, Arnaud; Demily, Caroline; Franck, Nicolas; Durand, Karine; Schaal, Benoist; Baudouin, Jean-Yves

2015-01-01

It has been established that the recognition of facial expressions integrates contextual information. In this study, we aimed to clarify the influence of contextual odors. The participants were asked to match a target face varying in expression intensity with non-ambiguous expressive faces. Intensity variations in the target faces were designed by morphing expressive faces with neutral faces. In addition, the influence of verbal information was assessed by providing half the participants with the emotion names. Odor cues were manipulated by placing participants in a pleasant (strawberry), aversive (butyric acid), or no-odor control context. The results showed two main effects of the odor context. First, the minimum amount of visual information required to perceive an expression was lowered when the odor context was emotionally congruent: happiness was correctly perceived at lower intensities in the faces displayed in the pleasant odor context, and the same phenomenon occurred for disgust and anger in the aversive odor context. Second, the odor context influenced the false perception of expressions that were not used in target faces, with distinct patterns according to the presence of emotion names. When emotion names were provided, the aversive odor context decreased intrusions for disgust ambiguous faces but increased them for anger. When the emotion names were not provided, this effect did not occur and the pleasant odor context elicited an overall increase in intrusions for negative expressions. We conclude that olfaction plays a role in the way facial expressions are perceived in interaction with other contextual influences such as verbal information. PMID:26390036
A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.
A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862
Transcutaneous vagus nerve stimulation (tVNS) enhances recognition of emotions in faces but not bodies.

PubMed

Sellaro, Roberta; de Gelder, Beatrice; Finisguerra, Alessandra; Colzato, Lorenza S

2018-02-01

The polyvagal theory suggests that the vagus nerve is the key phylogenetic substrate enabling optimal social interactions, a crucial aspect of which is emotion recognition. A previous study showed that the vagus nerve plays a causal role in mediating people's ability to recognize emotions based on images of the eye region. The aim of this study is to verify whether the previously reported causal link between vagal activity and emotion recognition can be generalized to situations in which emotions must be inferred from images of whole faces and bodies. To this end, we employed transcutaneous vagus nerve stimulation (tVNS), a novel non-invasive brain stimulation technique that causes the vagus nerve to fire by the application of a mild electrical stimulation to the auricular branch of the vagus nerve, located in the anterior protuberance of the outer ear. In two separate sessions, participants received active or sham tVNS before and while performing two emotion recognition tasks, aimed at indexing their ability to recognize emotions from facial and bodily expressions. Active tVNS, compared to sham stimulation, enhanced emotion recognition for whole faces but not for bodies. Our results confirm and further extend recent observations supporting a causal relationship between vagus nerve activity and the ability to infer others' emotional state, but restrict this association to situations in which the emotional state is conveyed by the whole face and/or by salient facial cues, such as eyes. Copyright © 2017 Elsevier Ltd. All rights reserved.
The neural code for face orientation in the human fusiform face area.

PubMed

Ramírez, Fernando M; Cichy, Radoslaw M; Allefeld, Carsten; Haynes, John-Dylan

2014-09-03

Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirror-symmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA. Copyright © 2014 the authors 0270-6474/14/3412155-13$15.00/0.
Problems of Face Recognition in Patients with Behavioral Variant Frontotemporal Dementia.

PubMed

Chandra, Sadanandavalli Retnaswami; Patwardhan, Ketaki; Pai, Anupama Ramakanth

2017-01-01

Faces are very special as they are most essential for social cognition in humans. It is partly understood that face processing in its abstractness involves several extra striate areas. One of the most important causes for caregiver suffering in patients with anterior dementia is lack of empathy. This apart from being a behavioral disorder could be also due to failure to categorize the emotions of the people around them. Inlusion criteria: DSM IV for Bv FTD Tested for prosopagnosia - familiar faces, famous face, smiling face, crying face and reflected face using a simple picture card (figure 1). Advanced illness and mixed causes. 46 patients (15 females, 31 males) 24 had defective face recognition. (mean age 51.5),10/15 females (70%) and 14/31males(47. Familiar face recognition defect was found in 6/10 females and 6/14 males. Total- 40%(6/15) females and 19.35%(6/31)males with FTD had familiar face recognition. Famous Face: 9/10 females and 7/14 males. Total- 60% (9/15) females with FTD had famous face recognition defect as against 22.6%(7/31) males with FTD Smiling face defects in 8/10 female and no males. Total- 53.33% (8/15) females. Crying face recognition defect in 3/10 female and 2 /14 males. Total- 20%(3/15) females and 6.5%(2/31) males. Reflected face recognition defect in 4 females. Famous face recognition and positive emotion recognition defect in 80%, only 20% comprehend positive emotions, Face recognition defects are found in only 45% of males and more common in females. Face recognition is more affected in females with FTD There is differential involvement of different aspects of the face recognition could be one of the important factor underlying decline in the emotional and social behavior of these patients. Understanding these pathological processes will give more insight regarding patient behavior.
Colour influences perception of facial emotions but this effect is impaired in healthy ageing and schizophrenia.

PubMed

Silver, Henry; Bilker, Warren B

2015-01-01

Social cognition is commonly assessed by identification of emotions in facial expressions. Presence of colour, a salient feature of stimuli, might influence emotional face perception. We administered 2 tests of facial emotion recognition, the Emotion Recognition Test (ER40) using colour pictures and the Penn Emotional Acuity Test using monochromatic pictures, to 37 young healthy, 39 old healthy and 37 schizophrenic men. Among young healthy individuals recognition of emotions was more accurate and faster in colour than in monochromatic pictures. Compared to the younger group, older healthy individuals revealed impairment in identification of sad expressions in colour but not monochromatic pictures. Schizophrenia patients showed greater impairment in colour than monochromatic pictures of neutral and sad expressions and overall total score compared to both healthy groups. Patients showed significant correlations between cognitive impairment and perception of emotion in colour but not monochromatic pictures. Colour enhances perception of general emotional clues and this contextual effect is impaired in healthy ageing and schizophrenia. The effects of colour need to be considered in interpreting and comparing studies of emotion perception. Coloured face stimuli may be more sensitive to emotion processing impairments but less selective for emotion-specific information than monochromatic stimuli. This may impact on their utility in early detection of impairments and investigations of underlying mechanisms.
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.
Children's understanding of facial expression of emotion: II. Drawing of emotion-faces.

PubMed

Missaghi-Lakshman, M; Whissell, C

1991-06-01

67 children from Grades 2, 4, and 7 drew faces representing the emotional expressions of fear, anger, surprise, disgust, happiness, and sadness. The children themselves and 29 adults later decoded the drawings in an emotion-recognition task. Children were the more accurate decoders, and their accuracy and the accuracy of adults increased significantly for judgments of 7th-grade drawings. The emotions happy and sad were most accurately decoded. There were no significant differences associated with sex. In their drawings, children utilized a symbol system that seems to be based on a highlighting or exaggeration of features of the innately governed facial expression of emotion.
Attention to emotion modulates fMRI activity in human right superior temporal sulcus.

PubMed

Narumoto, J; Okada, T; Sadato, N; Fukui, K; Yonekura, Y

2001-10-01

A parallel neural network has been proposed for processing various types of information conveyed by faces including emotion. Using functional magnetic resonance imaging (fMRI), we tested the effect of the explicit attention to the emotional expression of the faces on the neuronal activity of the face-responsive regions. Delayed match to sample procedure was adopted. Subjects were required to match the visually presented pictures with regard to the contour of the face pictures, facial identity, and emotional expressions by valence (happy and fearful expressions) and arousal (fearful and sad expressions). Contour matching of the non-face scrambled pictures was used as a control condition. The face-responsive regions that responded more to faces than to non-face stimuli were the bilateral lateral fusiform gyrus (LFG), the right superior temporal sulcus (STS), and the bilateral intraparietal sulcus (IPS). In these regions, general attention to the face enhanced the activities of the bilateral LFG, the right STS, and the left IPS compared with attention to the contour of the facial image. Selective attention to facial emotion specifically enhanced the activity of the right STS compared with attention to the face per se. The results suggest that the right STS region plays a special role in facial emotion recognition within distributed face-processing systems. This finding may support the notion that the STS is involved in social perception.
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

PubMed

Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

2016-08-01

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.
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.
Misinterpretation of Facial Expressions of Emotion in Verbal Adults with Autism Spectrum Disorder

PubMed Central

Eack, Shaun M.; MAZEFSKY, CARLA A.; Minshew, Nancy J.

2014-01-01

Facial emotion perception is significantly affected in autism spectrum disorder (ASD), yet little is known about how individuals with ASD misinterpret facial expressions that result in their difficulty in accurately recognizing emotion in faces. This study examined facial emotion perception in 45 verbal adults with ASD and 30 age- and gender-matched volunteers without ASD to identify patterns of emotion misinterpretation during face processing that contribute to emotion recognition impairments in autism. Results revealed that difficulty distinguishing emotional from neutral facial expressions characterized much of the emotion perception impairments exhibited by participants with ASD. In particular, adults with ASD uniquely misinterpreted happy faces as neutral, and were significantly more likely than typical volunteers to attribute negative valence to non-emotional faces. The over-attribution of emotions to neutral faces was significantly related to greater communication and emotional intelligence impairments in individuals with ASD. These findings suggest a potential negative bias toward the interpretation of facial expressions and may have implications for interventions designed to remediate emotion perception in ASD. PMID:24535689
Misinterpretation of facial expressions of emotion in verbal adults with autism spectrum disorder.

PubMed

Eack, Shaun M; Mazefsky, Carla A; Minshew, Nancy J

2015-04-01

Facial emotion perception is significantly affected in autism spectrum disorder, yet little is known about how individuals with autism spectrum disorder misinterpret facial expressions that result in their difficulty in accurately recognizing emotion in faces. This study examined facial emotion perception in 45 verbal adults with autism spectrum disorder and 30 age- and gender-matched volunteers without autism spectrum disorder to identify patterns of emotion misinterpretation during face processing that contribute to emotion recognition impairments in autism. Results revealed that difficulty distinguishing emotional from neutral facial expressions characterized much of the emotion perception impairments exhibited by participants with autism spectrum disorder. In particular, adults with autism spectrum disorder uniquely misinterpreted happy faces as neutral, and were significantly more likely than typical volunteers to attribute negative valence to nonemotional faces. The over-attribution of emotions to neutral faces was significantly related to greater communication and emotional intelligence impairments in individuals with autism spectrum disorder. These findings suggest a potential negative bias toward the interpretation of facial expressions and may have implications for interventions designed to remediate emotion perception in autism spectrum disorder. © The Author(s) 2014.
Postencoding cognitive processes in the cross-race effect: Categorization and individuation during face recognition.

PubMed

Ho, Michael R; Pezdek, Kathy

2016-06-01

The cross-race effect (CRE) describes the finding that same-race faces are recognized more accurately than cross-race faces. According to social-cognitive theories of the CRE, processes of categorization and individuation at encoding account for differential recognition of same- and cross-race faces. Recent face memory research has suggested that similar but distinct categorization and individuation processes also occur postencoding, at recognition. Using a divided-attention paradigm, in Experiments 1A and 1B we tested and confirmed the hypothesis that distinct postencoding categorization and individuation processes occur during the recognition of same- and cross-race faces. Specifically, postencoding configural divided-attention tasks impaired recognition accuracy more for same-race than for cross-race faces; on the other hand, for White (but not Black) participants, postencoding featural divided-attention tasks impaired recognition accuracy more for cross-race than for same-race faces. A social categorization paradigm used in Experiments 2A and 2B tested the hypothesis that the postencoding in-group or out-group social orientation to faces affects categorization and individuation processes during the recognition of same-race and cross-race faces. Postencoding out-group orientation to faces resulted in categorization for White but not for Black participants. This was evidenced by White participants' impaired recognition accuracy for same-race but not for cross-race out-group faces. Postencoding in-group orientation to faces had no effect on recognition accuracy for either same-race or cross-race faces. The results of Experiments 2A and 2B suggest that this social orientation facilitates White but not Black participants' individuation and categorization processes at recognition. Models of recognition memory for same-race and cross-race faces need to account for processing differences that occur at both encoding and recognition.
Recognition of Emotional and Nonemotional Facial Expressions: A Comparison between Williams Syndrome and Autism

ERIC Educational Resources Information Center

Lacroix, Agnes; Guidetti, Michele; Roge, Bernadette; Reilly, Judy

2009-01-01

The aim of our study was to compare two neurodevelopmental disorders (Williams syndrome and autism) in terms of the ability to recognize emotional and nonemotional facial expressions. The comparison of these two disorders is particularly relevant to the investigation of face processing and should contribute to a better understanding of social…
Three-dimensional object recognition using similar triangles and decision trees

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.
The Role of Higher Level Adaptive Coding Mechanisms in the Development of Face Recognition

ERIC Educational Resources Information Center

Pimperton, Hannah; Pellicano, Elizabeth; Jeffery, Linda; Rhodes, Gillian

2009-01-01

DevDevelopmental improvements in face identity recognition ability are widely documented, but the source of children's immaturity in face recognition remains unclear. Differences in the way in which children and adults visually represent faces might underlie immaturities in face recognition. Recent evidence of a face identity aftereffect (FIAE),…
2.5D multi-view gait recognition based on point cloud registration.

PubMed

Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

2014-03-28

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM.
Face and body recognition show similar improvement during childhood.

PubMed

Bank, Samantha; Rhodes, Gillian; Read, Ainsley; Jeffery, Linda

2015-09-01

Adults are proficient in extracting identity cues from faces. This proficiency develops slowly during childhood, with performance not reaching adult levels until adolescence. Bodies are similar to faces in that they convey identity cues and rely on specialized perceptual mechanisms. However, it is currently unclear whether body recognition mirrors the slow development of face recognition during childhood. Recent evidence suggests that body recognition develops faster than face recognition. Here we measured body and face recognition in 6- and 10-year-old children and adults to determine whether these two skills show different amounts of improvement during childhood. We found no evidence that they do. Face and body recognition showed similar improvement with age, and children, like adults, were better at recognizing faces than bodies. These results suggest that the mechanisms of face and body memory mature at a similar rate or that improvement of more general cognitive and perceptual skills underlies improvement of both face and body recognition. Copyright © 2015 Elsevier Inc. All rights reserved.

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.
Super-recognizers: People with extraordinary face recognition ability

PubMed Central

Russell, Richard; Duchaine, Brad; Nakayama, Ken

2014-01-01

We tested four people who claimed to have significantly better than ordinary face recognition ability. Exceptional ability was confirmed in each case. On two very different tests of face recognition, all four experimental subjects performed beyond the range of control subject performance. They also scored significantly better than average on a perceptual discrimination test with faces. This effect was larger with upright than inverted faces, and the four subjects showed a larger ‘inversion effect’ than control subjects, who in turn showed a larger inversion effect than developmental prosopagnosics. This indicates an association between face recognition ability and the magnitude of the inversion effect. Overall, these ‘super-recognizers’ are about as good at face recognition and perception as developmental prosopagnosics are bad. Our findings demonstrate the existence of people with exceptionally good face recognition ability, and show that the range of face recognition and face perception ability is wider than previously acknowledged. PMID:19293090
Super-recognizers: people with extraordinary face recognition ability.

PubMed

Russell, Richard; Duchaine, Brad; Nakayama, Ken

2009-04-01

We tested 4 people who claimed to have significantly better than ordinary face recognition ability. Exceptional ability was confirmed in each case. On two very different tests of face recognition, all 4 experimental subjects performed beyond the range of control subject performance. They also scored significantly better than average on a perceptual discrimination test with faces. This effect was larger with upright than with inverted faces, and the 4 subjects showed a larger "inversion effect" than did control subjects, who in turn showed a larger inversion effect than did developmental prosopagnosics. This result indicates an association between face recognition ability and the magnitude of the inversion effect. Overall, these "super-recognizers" are about as good at face recognition and perception as developmental prosopagnosics are bad. Our findings demonstrate the existence of people with exceptionally good face recognition ability and show that the range of face recognition and face perception ability is wider than has been previously acknowledged.
The effect of inversion on face recognition in adults with autism spectrum disorder.

PubMed

Hedley, Darren; Brewer, Neil; Young, Robyn

2015-05-01

Face identity recognition has widely been shown to be impaired in individuals with autism spectrum disorders (ASD). In this study we examined the influence of inversion on face recognition in 26 adults with ASD and 33 age and IQ matched controls. Participants completed a recognition test comprising upright and inverted faces. Participants with ASD performed worse than controls on the recognition task but did not show an advantage for inverted face recognition. Both groups directed more visual attention to the eye than the mouth region and gaze patterns were not found to be associated with recognition performance. These results provide evidence of a normal effect of inversion on face recognition in adults with ASD.
Neutral face classification using personalized appearance models for fast and robust emotion detection.

PubMed

Chiranjeevi, Pojala; Gopalakrishnan, Viswanath; Moogi, Pratibha

2015-09-01

Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning-based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, and so on, in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as user stays neutral for majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this paper, we propose a light-weight neutral versus emotion classification engine, which acts as a pre-processer to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at key emotion (KE) points using a statistical texture model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a statistical texture model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves emotion recognition (ER) accuracy and simultaneously reduces computational complexity of the ER system, as validated on multiple databases.
The effects of social anxiety on emotional face discrimination and its modulation by mouth salience.

PubMed

du Rocher, Andrew R; Pickering, Alan D

2018-05-21

People high in social anxiety experience fear of social situations due to the likelihood of social evaluation. Whereas happy faces are generally processed very quickly, this effect is impaired by high social anxiety. Mouth regions are implicated during emotional face processing, therefore differences in mouth salience might affect how social anxiety relates to emotional face discrimination. We designed an emotional facial expression recognition task to reveal how varying levels of sub-clinical social anxiety (measured by questionnaire) related to the discrimination of happy and fearful faces, and of happy and angry faces. We also categorised the facial expressions by the salience of the mouth region (i.e. high [open mouth] vs. low [closed mouth]). In a sample of 90 participants higher social anxiety (relative to lower social anxiety) was associated with a reduced happy face reaction time advantage. However, this effect was mainly driven by the faces with less salient closed mouths. Our results are consistent with theories of anxiety that incorporate an oversensitive valence evaluation system.
A multi-view face recognition system based on cascade face detector and improved Dlib

NASA Astrophysics Data System (ADS)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.
Altering sensorimotor feedback disrupts visual discrimination of facial expressions.

PubMed

Wood, Adrienne; Lupyan, Gary; Sherrin, Steven; Niedenthal, Paula

2016-08-01

Looking at another person's facial expression of emotion can trigger the same neural processes involved in producing the expression, and such responses play a functional role in emotion recognition. Disrupting individuals' facial action, for example, interferes with verbal emotion recognition tasks. We tested the hypothesis that facial responses also play a functional role in the perceptual processing of emotional expressions. We altered the facial action of participants with a gel facemask while they performed a task that involved distinguishing target expressions from highly similar distractors. Relative to control participants, participants in the facemask condition demonstrated inferior perceptual discrimination of facial expressions, but not of nonface stimuli. The findings suggest that somatosensory/motor processes involving the face contribute to the visual perceptual-and not just conceptual-processing of facial expressions. More broadly, our study contributes to growing evidence for the fundamentally interactive nature of the perceptual inputs from different sensory modalities.
Facial Expressions and Ability to Recognize Emotions From Eyes or Mouth in Children

PubMed Central

Guarnera, Maria; Hichy, Zira; Cascio, Maura I.; Carrubba, Stefano

2015-01-01

This research aims to contribute to the literature on the ability to recognize anger, happiness, fear, surprise, sadness, disgust and neutral emotions from facial information. By investigating children’s performance in detecting these emotions from a specific face region, we were interested to know whether children would show differences in recognizing these expressions from the upper or lower face, and if any difference between specific facial regions depended on the emotion in question. For this purpose, a group of 6-7 year-old children was selected. Participants were asked to recognize emotions by using a labeling task with three stimulus types (region of the eyes, of the mouth, and full face). The findings seem to indicate that children correctly recognize basic facial expressions when pictures represent the whole face, except for a neutral expression, which was recognized from the mouth, and sadness, which was recognized from the eyes. Children are also able to identify anger from the eyes as well as from the whole face. With respect to gender differences, there is no female advantage in emotional recognition. The results indicate a significant interaction ‘gender x face region’ only for anger and neutral emotions. PMID:27247651
Automatic recognition of ship types from infrared images using superstructure moment invariants

NASA Astrophysics Data System (ADS)

Li, Heng; Wang, Xinyu

2007-11-01

Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.
Motion facilitates face perception across changes in viewpoint and expression in older adults.

PubMed

Maguinness, Corrina; Newell, Fiona N

2014-12-01

Faces are inherently dynamic stimuli. However, face perception in younger adults appears to be mediated by the ability to extract structural cues from static images and a benefit of motion is inconsistent. In contrast, static face processing is poorer and more image-dependent in older adults. We therefore compared the role of facial motion in younger and older adults to assess whether motion can enhance perception when static cues are insufficient. In our studies, older and younger adults learned faces presented in motion or in a sequence of static images, containing rigid (viewpoint) or nonrigid (expression) changes. Immediately following learning, participants matched a static test image to the learned face which varied by viewpoint (Experiment 1) or expression (Experiment 2) and was either learned or novel. First, we found an age effect with better face matching performance in younger than in older adults. However, we observed face matching performance improved in the older adult group, across changes in viewpoint and expression, when faces were learned in motion relative to static presentation. There was no benefit for facial (nonrigid) motion when the task involved matching inverted faces (Experiment 3), suggesting that the ability to use dynamic face information for the purpose of recognition reflects motion encoding which is specific to upright faces. Our results suggest that ageing may offer a unique insight into how dynamic cues support face processing, which may not be readily observed in younger adults' performance. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Virtual faces expressing emotions: an initial concomitant and construct validity study.

PubMed

Joyal, Christian C; Jacob, Laurence; Cigna, Marie-Hélène; Guay, Jean-Pierre; Renaud, Patrice

2014-01-01

Facial expressions of emotions represent classic stimuli for the study of social cognition. Developing virtual dynamic facial expressions of emotions, however, would open-up possibilities, both for fundamental and clinical research. For instance, virtual faces allow real-time Human-Computer retroactions between physiological measures and the virtual agent. The goal of this study was to initially assess concomitants and construct validity of a newly developed set of virtual faces expressing six fundamental emotions (happiness, surprise, anger, sadness, fear, and disgust). Recognition rates, facial electromyography (zygomatic major and corrugator supercilii muscles), and regional gaze fixation latencies (eyes and mouth regions) were compared in 41 adult volunteers (20 ♂, 21 ♀) during the presentation of video clips depicting real vs. virtual adults expressing emotions. Emotions expressed by each set of stimuli were similarly recognized, both by men and women. Accordingly, both sets of stimuli elicited similar activation of facial muscles and similar ocular fixation times in eye regions from man and woman participants. Further validation studies can be performed with these virtual faces among clinical populations known to present social cognition difficulties. Brain-Computer Interface studies with feedback-feedforward interactions based on facial emotion expressions can also be conducted with these stimuli.
Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.
Repetition Blindness for Faces: A Comparison of Face Identity, Expression, and Gender Judgments.

PubMed

Murphy, Karen; Ward, Zoe

2017-01-01

Repetition blindness (RB) refers to the impairment in reporting two identical targets within a rapid serial visual presentation stream. While numerous studies have demonstrated RB for words and picture of objects, very few studies have examined RB for faces. This study extended this research by examining RB when the two faces were complete repeats (same emotion and identity), identity repeats (same individual, different emotion), and emotion repeats (different individual, same emotion) for identity, gender, and expression judgment tasks. Complete RB and identity RB effects were evident for all three judgment tasks. Emotion RB was only evident for the expression and gender judgments. Complete RB effects were larger than emotion or identity RB effects across all judgment tasks. For the expression judgments, there was more emotion than identity RB. The identity RB effect was larger than the emotion RB effect for the gender judgments. Cross task comparisons revealed larger complete RB effects for the expression and gender judgments than the identity decisions. There was a larger emotion RB effect for the expression than gender judgments and the identity RB effect was larger for the gender than for the identity and expression judgments. These results indicate that while faces are subject to RB, this is affected by the type of repeated information and relevance of the facial characteristic to the judgment decision. This study provides further support for the operation of separate processing mechanisms for face gender, emotion, and identity information within models of face recognition.
Repetition Blindness for Faces: A Comparison of Face Identity, Expression, and Gender Judgments

PubMed Central

Murphy, Karen; Ward, Zoe

2017-01-01

Repetition blindness (RB) refers to the impairment in reporting two identical targets within a rapid serial visual presentation stream. While numerous studies have demonstrated RB for words and picture of objects, very few studies have examined RB for faces. This study extended this research by examining RB when the two faces were complete repeats (same emotion and identity), identity repeats (same individual, different emotion), and emotion repeats (different individual, same emotion) for identity, gender, and expression judgment tasks. Complete RB and identity RB effects were evident for all three judgment tasks. Emotion RB was only evident for the expression and gender judgments. Complete RB effects were larger than emotion or identity RB effects across all judgment tasks. For the expression judgments, there was more emotion than identity RB. The identity RB effect was larger than the emotion RB effect for the gender judgments. Cross task comparisons revealed larger complete RB effects for the expression and gender judgments than the identity decisions. There was a larger emotion RB effect for the expression than gender judgments and the identity RB effect was larger for the gender than for the identity and expression judgments. These results indicate that while faces are subject to RB, this is affected by the type of repeated information and relevance of the facial characteristic to the judgment decision. This study provides further support for the operation of separate processing mechanisms for face gender, emotion, and identity information within models of face recognition. PMID:29038663
Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

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

PubMed Central

Fox, Christopher J.; Moon, So Young; Iaria, Giuseppe; Barton, Jason J.S.

2009-01-01

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network. PMID:18852053
The correlates of subjective perception of identity and expression in the face network: an fMRI adaptation study.

PubMed

Fox, Christopher J; Moon, So Young; Iaria, Giuseppe; Barton, Jason J S

2009-01-15

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network.
General and specific responsiveness of the amygdala during explicit emotion recognition in females and males.

PubMed

Derntl, Birgit; Habel, Ute; Windischberger, Christian; Robinson, Simon; Kryspin-Exner, Ilse; Gur, Ruben C; Moser, Ewald

2009-08-04

The ability to recognize emotions in facial expressions relies on an extensive neural network with the amygdala as the key node as has typically been demonstrated for the processing of fearful stimuli. A sufficient characterization of the factors influencing and modulating amygdala function, however, has not been reached now. Due to lacking or diverging results on its involvement in recognizing all or only certain negative emotions, the influence of gender or ethnicity is still under debate. This high-resolution fMRI study addresses some of the relevant parameters, such as emotional valence, gender and poser ethnicity on amygdala activation during facial emotion recognition in 50 Caucasian subjects. Stimuli were color photographs of emotional Caucasian and African American faces. Bilateral amygdala activation was obtained to all emotional expressions (anger, disgust, fear, happy, and sad) and neutral faces across all subjects. However, only in males a significant correlation of amygdala activation and behavioral response to fearful stimuli was observed, indicating higher amygdala responses with better fear recognition, thus pointing to subtle gender differences. No significant influence of poser ethnicity on amygdala activation occurred, but analysis of recognition accuracy revealed a significant impact of poser ethnicity that was emotion-dependent. Applying high-resolution fMRI while subjects were performing an explicit emotion recognition task revealed bilateral amygdala activation to all emotions presented and neutral expressions. This mechanism seems to operate similarly in healthy females and males and for both in-group and out-group ethnicities. Our results support the assumption that an intact amygdala response is fundamental in the processing of these salient stimuli due to its relevance detecting function.
Unconscious presentation of fearful face modulates electrophysiological responses to emotional prosody.

PubMed

Doi, Hirokazu; Shinohara, Kazuyuki

2015-03-01

Cross-modal integration of visual and auditory emotional cues is supposed to be advantageous in the accurate recognition of emotional signals. However, the neural locus of cross-modal integration between affective prosody and unconsciously presented facial expression in the neurologically intact population is still elusive at this point. The present study examined the influences of unconsciously presented facial expressions on the event-related potentials (ERPs) in emotional prosody recognition. In the experiment, fearful, happy, and neutral faces were presented without awareness by continuous flash suppression simultaneously with voices containing laughter and a fearful shout. The conventional peak analysis revealed that the ERPs were modulated interactively by emotional prosody and facial expression at multiple latency ranges, indicating that audio-visual integration of emotional signals takes place automatically without conscious awareness. In addition, the global field power during the late-latency range was larger for shout than for laughter only when a fearful face was presented unconsciously. The neural locus of this effect was localized to the left posterior fusiform gyrus, giving support to the view that the cortical region, traditionally considered to be unisensory region for visual processing, functions as the locus of audiovisual integration of emotional signals. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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