Classification Of Human Facial Expressions For Emotion Recognition Using A Distributed Computer System

2020 ◽  
Author(s):  
Timucin Korkmaz ◽  
Hamza Erol
Keyword(s):  
Emotion Recognition ◽  
Computer System ◽  
Facial Expressions ◽  
Distributed Computer System

scholarly journals Acting Surprised: Comparing Perceptions of Different Dynamic Deliberate Expressions

2020 ◽  
Author(s):  
Mircea Zloteanu ◽  
Eva G. Krumhuber ◽  
Daniel C. Richardson
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Affective State ◽  
External Condition ◽  
Internal Condition ◽  
Minimal Effort ◽  
Better Than

AbstractPeople are accurate at classifying emotions from facial expressions but much poorer at determining if such expressions are spontaneously felt or deliberately posed. We explored if the method used by senders to produce an expression influences the decoder’s ability to discriminate authenticity, drawing inspiration from two well-known acting techniques: the Stanislavski (internal) and Mimic method (external). We compared spontaneous surprise expressions in response to a jack-in-the-box (genuine condition), to posed displays of senders who either focused on their past affective state (internal condition) or the outward expression (external condition). Although decoders performed better than chance at discriminating the authenticity of all expressions, their accuracy was lower in classifying external surprise compared to internal surprise. Decoders also found it harder to discriminate external surprise from spontaneous surprise and were less confident in their decisions, perceiving these to be similarly intense but less genuine-looking. The findings suggest that senders are capable of voluntarily producing genuine-looking expressions of emotions with minimal effort, especially by mimicking a genuine expression. Implications for research on emotion recognition are discussed.

Emotion Recognition of Facial Expressions Presented in Profile

2021 ◽  
pp. 003329412110184
Author(s):  
Paola Surcinelli ◽  
Federica Andrei ◽  
Ornella Montebarocci ◽  
Silvana Grandi
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Response Times ◽  
Recognition Accuracy ◽  
Recognition Of Facial Expressions ◽  
Profile View ◽  
The Face ◽  
Within Subjects ◽  
Face Stimuli ◽  
Affective Information

Aim of the research The literature on emotion recognition from facial expressions shows significant differences in recognition ability depending on the proposed stimulus. Indeed, affective information is not distributed uniformly in the face and recent studies showed the importance of the mouth and the eye regions for a correct recognition. However, previous studies used mainly facial expressions presented frontally and studies which used facial expressions in profile view used a between-subjects design or children faces as stimuli. The present research aims to investigate differences in emotion recognition between faces presented in frontal and in profile views by using a within subjects experimental design. Method The sample comprised 132 Italian university students (88 female, Mage = 24.27 years, SD = 5.89). Face stimuli displayed both frontally and in profile were selected from the KDEF set. Two emotion-specific recognition accuracy scores, viz., frontal and in profile, were computed from the average of correct responses for each emotional expression. In addition, viewing times and response times (RT) were registered. Results Frontally presented facial expressions of fear, anger, and sadness were significantly better recognized than facial expressions of the same emotions in profile while no differences were found in the recognition of the other emotions. Longer viewing times were also found when faces expressing fear and anger were presented in profile. In the present study, an impairment in recognition accuracy was observed only for those emotions which rely mostly on the eye regions.

scholarly journals Negative parental emotional environment increases the association between childhood behavioral problems and impaired recognition of negative facial expressions

2021 ◽  
pp. 1-10
Author(s):  
Daniel T. Burley ◽  
Christopher W. Hobson ◽  
Dolapo Adegboye ◽  
Katherine H. Shelton ◽  
Stephanie H.M. van Goozen
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Behavioral Problems ◽  
Expressed Emotion ◽  
Interactive Effect ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Emotional Environment ◽  
Negative Comments ◽  
Child Behavioral Problems

Abstract Impaired facial emotion recognition is a transdiagnostic risk factor for a range of psychiatric disorders. Childhood behavioral difficulties and parental emotional environment have been independently associated with impaired emotion recognition; however, no study has examined the contribution of these factors in conjunction. We measured recognition of negative (sad, fear, anger), neutral, and happy facial expressions in 135 children aged 5–7 years referred by their teachers for behavioral problems. Parental emotional environment was assessed for parental expressed emotion (EE) – characterized by negative comments, reduced positive comments, low warmth, and negativity towards their child – using the 5-minute speech sample. Child behavioral problems were measured using the teacher-informant Strengths and Difficulties Questionnaire (SDQ). Child behavioral problems and parental EE were independently associated with impaired recognition of negative facial expressions specifically. An interactive effect revealed that the combination of both factors was associated with the greatest risk for impaired recognition of negative faces, and in particular sad facial expressions. No relationships emerged for the identification of happy facial expressions. This study furthers our understanding of multidimensional processes associated with the development of facial emotion recognition and supports the importance of early interventions that target this domain.

scholarly journals A EEG-based emotion recognition model with rhythm and time characteristics

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jianzhuo Yan ◽  
Shangbin Chen ◽  
Sinuo Deng
Keyword(s):  
Emotion Recognition ◽  
Time Scales ◽  
Time Scale ◽  
Short Term Memory ◽  
Recognition Model ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Valence And Arousal ◽  
Memory Characteristics

Abstract As an advanced function of the human brain, emotion has a significant influence on human studies, works, and other aspects of life. Artificial Intelligence has played an important role in recognizing human emotion correctly. EEG-based emotion recognition (ER), one application of Brain Computer Interface (BCI), is becoming more popular in recent years. However, due to the ambiguity of human emotions and the complexity of EEG signals, the EEG-ER system which can recognize emotions with high accuracy is not easy to achieve. Based on the time scale, this paper chooses the recurrent neural network as the breakthrough point of the screening model. According to the rhythmic characteristics and temporal memory characteristics of EEG, this research proposes a Rhythmic Time EEG Emotion Recognition Model (RT-ERM) based on the valence and arousal of Long–Short-Term Memory Network (LSTM). By applying this model, the classification results of different rhythms and time scales are different. The optimal rhythm and time scale of the RT-ERM model are obtained through the results of the classification accuracy of different rhythms and different time scales. Then, the classification of emotional EEG is carried out by the best time scales corresponding to different rhythms. Finally, by comparing with other existing emotional EEG classification methods, it is found that the rhythm and time scale of the model can contribute to the accuracy of RT-ERM.

scholarly journals Effects of early institutionalization on emotion processing in 12-year-old youth

2017 ◽  
Vol 29 (5) ◽  
pp. 1749-1761 ◽  
Author(s):  
Johanna Bick ◽  
Rhiannon Luyster ◽  
Nathan A. Fox ◽  
Charles H. Zeanah ◽  
Charles A. Nelson
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Positive Impact ◽  
Developmental Trajectories ◽  
Emotion Processing ◽  
Institutional Care ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Emotional Facial Expressions ◽  
Fearful Faces

AbstractWe examined facial emotion recognition in 12-year-olds in a longitudinally followed sample of children with and without exposure to early life psychosocial deprivation (institutional care). Half of the institutionally reared children were randomized into foster care homes during the first years of life. Facial emotion recognition was examined in a behavioral task using morphed images. This same task had been administered when children were 8 years old. Neutral facial expressions were morphed with happy, sad, angry, and fearful emotional facial expressions, and children were asked to identify the emotion of each face, which varied in intensity. Consistent with our previous report, we show that some areas of emotion processing, involving the recognition of happy and fearful faces, are affected by early deprivation, whereas other areas, involving the recognition of sad and angry faces, appear to be unaffected. We also show that early intervention can have a lasting positive impact, normalizing developmental trajectories of processing negative emotions (fear) into the late childhood/preadolescent period.

scholarly journals Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Dina Tell ◽  
Denise Davidson ◽  
Linda A. Camras
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Eye Gaze ◽  
Children With Autism ◽  
Gaze Direction ◽  
Emotional Expressions ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Expression Intensity ◽  
Autism Disorder

Eye gaze direction and expression intensity effects on emotion recognition in children with autism disorder and typically developing children were investigated. Children with autism disorder and typically developing children identified happy and angry expressions equally well. Children with autism disorder, however, were less accurate in identifying fear expressions across intensities and eye gaze directions. Children with autism disorder rated expressions with direct eyes, and 50% expressions, as more intense than typically developing children. A trend was also found for sad expressions, as children with autism disorder were less accurate in recognizing sadness at 100% intensity with direct eyes than typically developing children. Although the present research showed that children with autism disorder are sensitive to eye gaze direction, impairments in the recognition of fear, and possibly sadness, exist. Furthermore, children with autism disorder and typically developing children perceive the intensity of emotional expressions differently.

Sign in / Sign up

Export Citation Format

Share Document