The Classification of Facial Expressions of Emotion: A Multidimensional-Scaling Approach

Perception ◽  
1997 ◽  
Vol 26 (5) ◽  
pp. 613-626 ◽  
Author(s):  
Mary Katsikitis
Keyword(s):  
Multidimensional Scaling ◽  
Facial Expressions ◽  
Line Drawing ◽  
Two Dimensions ◽  
Lower Face ◽  
Line Drawings ◽  
Scaling Procedure ◽  
Facial Expressions Of Emotion ◽  
Upper Face

Photographs (study 1) or line-drawing representations (study 2) of posed facial expressions and a list of emotion words (happiness, surprise, fear, disgust, anger, sadness, neutral) were presented to two groups of observers who were asked to match the photographs or line drawings, respectively, with the emotion categories provided. A multidimensional-scaling procedure was applied to the judgment data. Two dimensions were revealed; pleasantness – unpleasantness and upper-face – lower-face dominance. Furthermore, the similarity shown by the two-dimensional structures derived first from the judgments of photographs and second from the line drawings suggests that line drawings are a viable alternative to photographs in facial-expression research.

Classification of dynamic facial expressions of emotion presented briefly

2013 ◽  
Vol 27 (8) ◽  
pp. 1486-1494 ◽  
Author(s):  
Guillermo Recio ◽  
Annekathrin Schacht ◽  
Werner Sommer
Keyword(s):  
Facial Expressions ◽  
Dynamic Facial Expressions ◽  
Facial Expressions Of Emotion

scholarly journals Time Pressure Inhibits Dynamic Advantage in the Classification of Facial Expressions of Emotion

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e100162 ◽  
Author(s):  
Zhongqing Jiang ◽  
Wenhui Li ◽  
Guillermo Recio ◽  
Ying Liu ◽  
Wenbo Luo ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Time Pressure ◽  
Facial Expressions Of Emotion

Preschool Children's Interpretation of Facial Expressions of Emotion

1984 ◽  
Vol 7 (2) ◽  
pp. 193-214 ◽  
Author(s):  
Merry Bullock ◽  
James A. Russell
Keyword(s):  
Facial Expressions ◽  
Structural Model ◽  
Focal Point ◽  
Age Groups ◽  
Two Dimensions ◽  
Dimensional Structure ◽  
Emotional Facial Expressions ◽  
Emotion Words ◽  
Facial Expressions Of Emotion ◽  
Wide Awake

A structural model of emotions was used to reveal patterns in how children interpret the emotional facial expressions of others. Three-, four-, five-year-olds, and adults (n = 38 in each group) were asked to match 15 emotion-descriptive words (happy, excited, surprised, afraid, scared, angry, mad, disgusted, miserable, sad, sleepy, calm, relaxed, wide awake, and, as a check on response bias, insipid) with still photographs of actors showing different facial expressions. Whereas prior research had indicated that preschool-aged children are "inaccurate" in associating labels with faces, our results indicated that that research may have severely underestimated children's knowledge of emotions. In this study children used terms systematically to refer to a specifiable range of expressions, centered around a focal point. Multidimensional scaling of the word/facial expression associations yielded a two-dimensional structure able to account for the interrelationships among emotions, and this structure was the same for all age groups. The nature of this structure, the blurry boundaries between emotion words, and developmental shifts in the referents of emotion words suggested the primacy of two dimensions, pleasure-displeasure and arousal-sleep, in children's interpretation of emotion.

scholarly journals Differences in Facial Expressions between Spontaneous and Posed Smiles: Automated Method by Action Units and Three-Dimensional Facial Landmarks

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1199
Author(s):  
Seho Park ◽  
Kunyoung Lee ◽  
Jae-A Lim ◽  
Hyunwoong Ko ◽  
Taehoon Kim ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Three Dimensional ◽  
Lower Face ◽  
Facial Landmarks ◽  
Automated Method ◽  
Discrete Movement ◽  
The Face ◽  
Upper Face ◽  
The Right

Research on emotion recognition from facial expressions has found evidence of different muscle movements between genuine and posed smiles. To further confirm discrete movement intensities of each facial segment, we explored differences in facial expressions between spontaneous and posed smiles with three-dimensional facial landmarks. Advanced machine analysis was adopted to measure changes in the dynamics of 68 segmented facial regions. A total of 57 normal adults (19 men, 38 women) who displayed adequate posed and spontaneous facial expressions for happiness were included in the analyses. The results indicate that spontaneous smiles have higher intensities for upper face than lower face. On the other hand, posed smiles showed higher intensities in the lower part of the face. Furthermore, the 3D facial landmark technique revealed that the left eyebrow displayed stronger intensity during spontaneous smiles than the right eyebrow. These findings suggest a potential application of landmark based emotion recognition that spontaneous smiles can be distinguished from posed smiles via measuring relative intensities between the upper and lower face with a focus on left-sided asymmetry in the upper region.

scholarly journals Face masks influence how facial expressions are perceived: A drift-diffusion model of emotion judgments

2021 ◽  
Author(s):  
W. Craig Williams ◽  
Eisha Haque ◽  
Becky Mai ◽  
Vinod Venkatraman
Keyword(s):  
Diffusion Model ◽  
Facial Expressions ◽  
Drift Rate ◽  
Diffusion Modeling ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Lower Face ◽  
Upper Face

Face masks slow the spread of SARS-CoV-2, but it has been unknown whether masks influence how individuals communicate emotion through facial expressions. Masks could influence how accurately—or how quickly—individuals perceive expressions, and how rapidly they accumulate evidence for emotion. Over two independent pre-registered studies, conducted three and six months into the COVID-19 pandemic, participants judged expressions of 6 emotions (anger, disgust, fear, happiness, sadness, surprise) with the lower or upper face “masked” or unmasked. Participants in Study 1 (N = 228) identified expressions above chance with lower face masks. However, they were less likely—and slower—to correctly identify these expressions versus without masks, and they accumulated evidence for emotion more slowly—via decreased drift rate in drift-diffusion modeling. This pattern replicated and intensified three months later in Study 2 (N = 264). These data could inform interventions to promote mask wearing by addressing concerns with emotion communication.

Emotion Space as a Predictor of Binocular Rivalry

2000 ◽  
Vol 90 (1) ◽  
pp. 291-298 ◽  
Author(s):  
Tokihiro Ogawa ◽  
Naoto Suzuki
Keyword(s):  
Multidimensional Scaling ◽  
Facial Expressions ◽  
Binocular Rivalry ◽  
Dimensional Structure ◽  
Two Dimensional ◽  
Facial Expressions Of Emotion ◽  
Emotion Space

In our 1999 report, we examined robustness of a two-dimensional structure of facial expressions of emotion under the condition of some perceptual ambiguity, using a stereoscope. The current study aimed to replicate and extend the previous work by adding facial photographs of different persons and by measuring participants' perception of stereoscopically presented faces. Multidimensional scaling provided a two-dimensional configuration of facial expressions comparable with the previous studies. Although binocular rivalry was a less frequent phenomenon, it was suggested that the distances between facial expressions in the derived space were a contributing factor in eliciting binocular rivalry.

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