Recognising facial expressions with noisy data

Techniques to improve the automated analysis of natural and spontaneous facial expressions have been developed. The outcome of the research has applications in several fields including national security (eg: expression invariant face recognition); education (eg: affect aware interfaces); mental and physical health (eg: depression and pain recognition).

Brain networks subserving the evaluation of static and dynamic facial expressions

Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Social perception and cognition : processing of gestures, postures and facial expressions in the human brain

Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.

The relationship between the recognition of facial expressions and self-reported anger in people with intellectual disabilities

Background This study aims to examine the relationship between how individuals with intellectual disabilities report their own levels of anger, and the ability of those individuals to recognize emotions. It was hypothesized that increased expression of anger would be linked to lower ability to recognize facial emotional expressions and increased tendency to interpret facial expressions in a hostile or negative manner. It was also hypothesized increased levels of anger may lead to the altered perception of a particular emotion.

Method A cross-sectional survey design was used. Thirty participants completed a test of facial emotion recognition (FER), and a self-report anger inventory (Benson & Ivins 1992) as part of a structured interview.

Results Individuals with higher self-reported anger did not show significantly reduced performance in FER, or interpret facial expressions in a more hostile manner compared with individuals with less self-reported anger. However, they were less accurate in recognizing neutral facial emotions.

Conclusions It is tentatively suggested that individuals with high levels of anger may be likely to perceive emotional content in a neutral facial expression because of their high levels of emotional arousal.

Gender Differences in the Perceptions of Genuine and Simulated Laughter and Amused Facial Expressions

This article addresses gender differences in laughter and smiling from an evolutionary perspective. Laughter and smiling can be responses to successful display behavior or signals of affiliation amongst conversational partners—differing social and evolutionary agendas mean there are different motivations when interpreting these signals. Two experiments assess perceptions of genuine
and simulated male and female laughter and amusement social signals. Results show male simulation can always be distinguished. Female simulation is more complicated as males seem to distinguish cues of simulation yet judge simulated signals to be genuine. Females judge other female’s genuine signals to have higher levels of simulation. Results highlight the importance of laughter and smiling in human interactions, use of dynamic stimuli, and using multiple methodologies to assess perception.

Correlates of facial expressions in the primary visual cortex

Face detection and recognition should be complemented by recognition of facial expression, for example for social robots which must react to human emotions. Our framework is based on two multi-scale representations in cortical area V1: keypoints at eyes, nose and mouth are grouped for face detection [1]; lines and edges provide information for face recognition [2].

Recognition of facial expressions by cortical multi-scale line and edge coding

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extraction. Simple, complex and end-stopped cells provide input for line, edge and keypoint detection. Detected events provide a rich, multi-scale object representation, and this representation can be stored in memory in order to identify objects. In this paper, the above context is applied to face recognition. The multi-scale line/edge representation is explored in conjunction with keypoint-based saliency maps for Focus-of-Attention. Recognition rates of up to 96% were achieved by combining frontal and 3/4 views, and recognition was quite robust against partial occlusions.

Sensitivity to differences between posed and genuine facial expressions : are children easily fooled? /

Adults and children can discriminate various emotional expressions, although there is limited research on sensitivity to the differences between posed and genuine expressions. Adults have shown implicit sensitivity to the difference between posed and genuine happy smiles in that they evaluate T-shirts paired with genuine smiles more favorably than T-shirts paired with posed smiles or neutral expressions (Peace, Miles, & Johnston, 2006). Adults also have shown some explicit sensitivity to posed versus genuine expressions; they are more likely to say that a model i?,feeling happy if the expression is genuine than posed. Nonetheless they are duped by posed expressions about 50% of the time (Miles, & Johnston, in press). There has been no published study to date in which researchers report whether children's evaluation of items varies with expression and there is little research investigating children's sensitivity to the veracity of facial expressions. In the present study the same face stimuli were used as in two previous studies (Miles & Johnston, in press; Peace et al., 2006). The first question to be addressed was whether adults and 7-year-olds have a cognitive understanding of the differences between posed and genuine happiness {scenario task). They evaluated the feelings of children who expressed gratitude for a present that they did or did not want. Results indicated that all participants had a fundamental understanding of the difference between real and posed happiness. The second question involved adults' and children's implicit sensitivity to the veracity of posed and genuine smiles. Participants rated and ranked beach balls paired with faces showing posed smiles, genuine smiles, and neutral expressions. Adults ranked.but did not rate beach balls paired with genuine smiles more favorably than beach balls paired with posed smiles. Children did not demonstrate implicit sensitivity as their ratings and rankings of beach balls did not vary with expressions; they did not even rank beach balls paired with genuine expressions higher than beach balls paired with neutral expressions. In the explicit (show/feel) task, faces were presented without the beach balls and participants were first asked whether each face was showing happy and then whether each face wasfeeling happy. There were also two matching trials that presented two faces at once; participants had to indicate which person was actuallyfeeling happy. In the show condition both adults and 7-year-olds were very accurate on genuine and neutral expressions but made some errors on posed smiles. Adults were fooled about 50% of the time by posed smiles in thefeel condition (i.e., they were likely to say that a model posing happy was really feeling happy) and children were even less accurate, although they showed weak sensitivity to posed versus genuine expressions. Future research should test an older age group of children to determine when explicit sensitivity to posed versus genuine facial expressions becomes adult-like and modify the ranking task to explore the influence of facial expressions on object evaluations.

The influence of emotional body posture on adults' and 8-year-olds' perception facial expressions

The present set of experiments was designed to investigate the development of children's sensitivity of facial expressions observed within emotional contexts. Past research investigating both adults' and children's perception of facial expressions has been limited primarily to the presentation of isolated faces. During daily social interactions, however, facial expressions are encountered within contexts conveying emotions (e.g., background scenes, body postures, gestures). Recently, research has shown that adults' perception of facial expressions is influenced by these contexts. When emotional faces are shown in incongruent contexts (e.g., when an angry face is presented in a context depicting fear) adults' accuracy decreases and their reaction times increase (e.g., Meeren et a1. 2005). To examine the influence of emotional body postures on children's perception of facial expressions, in each of the experiments in the current study adults and 8-year-old children made two-alternative forced choice decisions about facial expressions presented in congruent (e.g., a face displayed sadness on a body displaying sadness) and incongruent (e.g., a face displaying fear on a body displaying sadness) contexts. Consistent with previous studies, a congruency effect (better performance on congruent than incongruent trials) was found for both adults and 8-year-olds when the emotions displayed by the face and body were similar to each other (e.g., fear and sad, Experiment l a ) ; the influence of context was greater for 8-year-olds than adults for these similar expressions. To further investigate why the congruency effect was larger for children than adults in Experiment 1 a, Experiment 1 b was conducted to examine if increased task difficulty would increase the magnitude of adults' congruency effects. Adults were presented with subtle facial and despite successfully increasing task difficulty the magnitude of the. congruency effect did not increase suggesting that the difference between children's and adults' congruency effects in Experiment l a cannot be explained by 8-year-olds finding the task difficult. In contrast, congruency effects were not found when the expressions displayed by the face and body were dissimilar (e.g., sad and happy, see Experiment 2). The results of the current set of studies are examined with respect to the Dimensional theory and the Emotional Seed model and the developmental timeline of children's sensitivity to facial expressions. A secondary aim of the series of studies was to examine one possible mechanism underlying congruency effe cts-holistic processing. To examine the influence of holistic processing, participants completed both aligned trials and misaligned trials in which the faces were detached from the body (designed to disrupt holistic processing). Based on the principles of holistic face processing we predicted that participants would benefit from misalignment of the face and body stimuli on incongruent trials but not on congruent trials. Collectively, our results provide some evidence that both adults and children may process emotional faces and bodies holistically. Consistent with the pattern of results for congruency effects, the magnitude of the effect of misalignment varied with the similarity between emotions. Future research is required to further investigate whether or not facial expressions and emotions conveyed by the body are perceived holistically.

Asymmetries of Influence: Differential Effects of Body Postures on Perceptions of Emotional Facial Expressions

The accuracy and speed with which emotional facial expressions are identified is influenced by body postures. Two influential models predict that these congruency effects will be largest when the emotion displayed in the face is similar to that displayed in the body: the emotional seed model and the dimensional model. These models differ in whether similarity is based on physical characteristics or underlying dimensions of valence and arousal. Using a 3- alternative forced-choice task in which stimuli were presented briefly (Exp 1a) or for an unlimited time (Exp 1b) we provide evidence that congruency effects are more complex than either model predicts; the effects are asymmetrical and cannot be accounted for by similarity alone. Fearful postures are especially influential when paired with facial expressions, but not when presented in a flanker task (Exp 2). We suggest refinements to each model that may account for our results and suggest that additional studies be conducted prior to drawing strong theoretical conclusions.

Recognition of Facial Expressions with Autoencoders and Convolutional-Nets

Les humains communiquent via différents types de canaux: les mots, la voix, les gestes du corps, des émotions, etc. Pour cette raison, un ordinateur doit percevoir ces divers canaux de communication pour pouvoir interagir intelligemment avec les humains, par exemple en faisant usage de microphones et de webcams. Dans cette thèse, nous nous intéressons à déterminer les émotions humaines à partir d’images ou de vidéo de visages afin d’ensuite utiliser ces informations dans différents domaines d’applications. Ce mémoire débute par une brève introduction à l'apprentissage machine en s’attardant aux modèles et algorithmes que nous avons utilisés tels que les perceptrons multicouches, réseaux de neurones à convolution et autoencodeurs. Elle présente ensuite les résultats de l'application de ces modèles sur plusieurs ensembles de données d'expressions et émotions faciales. Nous nous concentrons sur l'étude des différents types d’autoencodeurs (autoencodeur débruitant, autoencodeur contractant, etc) afin de révéler certaines de leurs limitations, comme la possibilité d'obtenir de la coadaptation entre les filtres ou encore d’obtenir une courbe spectrale trop lisse, et étudions de nouvelles idées pour répondre à ces problèmes. Nous proposons également une nouvelle approche pour surmonter une limite des autoencodeurs traditionnellement entrainés de façon purement non-supervisée, c'est-à-dire sans utiliser aucune connaissance de la tâche que nous voulons finalement résoudre (comme la prévision des étiquettes de classe) en développant un nouveau critère d'apprentissage semi-supervisé qui exploite un faible nombre de données étiquetées en combinaison avec une grande quantité de données non-étiquetées afin d'apprendre une représentation adaptée à la tâche de classification, et d'obtenir une meilleure performance de classification. Finalement, nous décrivons le fonctionnement général de notre système de détection d'émotions et proposons de nouvelles idées pouvant mener à de futurs travaux.

Recognition of static and dynamic facial expressions: Influences of sex, type and intensity of emotion

Ecological validity of static and intense facial expressions in emotional recognition has been questioned. Recent studies have recommended the use of facial stimuli more compatible to the natural conditions of social interaction, which involves motion and variations in emotional intensity. In this study, we compared the recognition of static and dynamic facial expressions of happiness, fear, anger and sadness, presented in four emotional intensities (25 %, 50 %, 75 % and 100 %). Twenty volunteers (9 women and 11 men), aged between 19 and 31 years, took part in the study. The experiment consisted of two sessions in which participants had to identify the emotion of static (photographs) and dynamic (videos) displays of facial expressions on the computer screen. The mean accuracy was submitted to an Anova for repeated measures of model: 2 sexes x [2 conditions x 4 expressions x 4 intensities]. We observed an advantage for the recognition of dynamic expressions of happiness and fear compared to the static stimuli (p < .05). Analysis of interactions showed that expressions with intensity of 25 % were better recognized in the dynamic condition (p < .05). The addition of motion contributes to improve recognition especially in male participants (p < .05). We concluded that the effect of the motion varies as a function of the type of emotion, intensity of the expression and sex of the participant. These results support the hypothesis that dynamic stimuli have more ecological validity and are more appropriate to the research with emotions.

Gender differences among undergraduates in the recognition of emotional facial expressions

The perceptive accuracy of university students was compared between men and women, from sciences and humanities courses, to recognize emotional facial expressions. emotional expressions have had increased interest in several areas involved with human interaction, reflecting the importance of perceptive skills in human expression of emotions for the effectiveness of communication. Two tests were taken: one was a quick exposure (0.5 s) of 12 faces with an emotional expression, followed by a neutral face. subjects had to tell if happiness, sadness, anger, fear, disgust or surprise was flashed, and each emotion was shown twice, at random. on the second test 15 faces with the combination of two emotional expressions were shown without a time limit, and the subject had to name one of the emotions of the previous list. in this study, women perceived sad expressions better while men realized more happy faces. there was no significant difference in other emotions detection like anger, fear, surprise, disgust. Students of humanities and sciences areas of both sexes, when compared, had similar capacities to perceive emotional expressions