scholarly journals The Expressive Triad: Structure, Color, and Texture Similarity of Emotion Expressions Predict Impressions of Neutral Faces

2021 ◽  
Vol 12 ◽  
Author(s):  
Daniel N. Albohn ◽  
Reginald B. Adams
Keyword(s):  
Computer Vision ◽  
Impression Formation ◽  
Emotional Expressions ◽  
Connectionist Model ◽  
Specific Expression ◽  
Face Shape ◽  
Structural Resemblance ◽  
Neutral Face ◽  
The Face ◽  
Bayesian Network Classifier

Previous research has demonstrated how emotion resembling cues in the face help shape impression formation (i. e., emotion overgeneralization). Perhaps most notable in the literature to date, has been work suggesting that gender-related appearance cues are visually confounded with certain stereotypic expressive cues (see Adams et al., 2015 for review). Only a couple studies to date have used computer vision to directly map out and test facial structural resemblance to emotion expressions using facial landmark coordinates to estimate face shape. In one study using a Bayesian network classifier trained to detect emotional expressions structural resemblance to a specific expression on a non-expressive (i.e., neutral) face was found to influence trait impressions of others (Said et al., 2009). In another study, a connectionist model trained to detect emotional expressions found different emotion-resembling cues in male vs. female faces (Zebrowitz et al., 2010). Despite this seminal work, direct evidence confirming the theoretical assertion that humans likewise utilize these emotion-resembling cues when forming impressions has been lacking. Across four studies, we replicate and extend these prior findings using new advances in computer vision to examine gender-related, emotion-resembling structure, color, and texture (as well as their weighted combination) and their impact on gender-stereotypic impression formation. We show that all three (plus their combination) are meaningfully related to human impressions of emotionally neutral faces. Further when applying the computer vision algorithms to experimentally manipulate faces, we show that humans derive similar impressions from them as did the computer.

Judgements of facial expressions of emotions in context and no-context Conditions

1984 ◽  
Vol 1 ◽  
pp. 29-35
Author(s):  
Michael P. O'Driscoll ◽  
Barry L. Richardson ◽  
Dianne B. Wuillemin
Keyword(s):  
Facial Expressions ◽  
Impression Formation ◽  
Person Perception ◽  
Contextual Information ◽  
Experimental Studies ◽  
Real Life ◽  
Emotion Perception ◽  
Important Variable ◽  
Emotional Expressions ◽  
The Face

Thirty photographs depicting diverse emotional expressions were shown to a sample of Melanesian students who were assigned to either a face plus context or face alone condition. Significant differences between the two groups were obtained in a substantial proportion of cases on Schlosberg's Pleasant Unpleasant, and Attention – Rejection scales and the emotional expressions were judged to be appropriate to the context. These findings support the suggestion that the presence or absence of context is an important variable in the judgement of emotional expression and lend credence to the universal process theory.Research on perception of emotions has consistently illustrated that observers can accurately judge emotions in facial expressions (Ekman, Friesen, & Ellsworth, 1972; Izard, 1971) and that the face conveys important information about emotions being experienced (Ekman & Oster, 1979). In recent years, however, a question of interest has been the relative contributions of facial cues and contextual information to observers' overall judgements. This issue is important for theoretical and methodological reasons. From a theoretical viewpoint, unravelling the determinants of emotion perception would enhance our understanding of the processes of person perception and impression formation and would provide a framework for research on interpersonal communication. On methodological grounds, the researcher's approach to the face versus context issue can influence the type of research procedures used to analyse emotion perception. Specifically, much research in this field has been criticized for use of posed emotional expressions as stimuli for observers to evaluate. Spignesi and Shor (1981) have noted that only one of approximately 25 experimental studies has utilized facial expressions occurring spontaneously in real-life situations.

scholarly journals Testing the face shape hypothesis in twins discordant for nonsyndromic orofacial clefting

2017 ◽  
Vol 173 (11) ◽  
pp. 2886-2892 ◽  
Author(s):  
Jasmien Roosenboom ◽  
Karlijne Indencleef ◽  
Greet Hens ◽  
Hilde Peeters ◽  
Kaare Christensen ◽  
...  
Keyword(s):  
Face Shape ◽  
Orofacial Clefting ◽  
The Face

scholarly journals Dogs recognize dog and human emotions

2016 ◽  
Vol 12 (1) ◽  
pp. 20150883 ◽  
Author(s):  
Natalia Albuquerque ◽  
Kun Guo ◽  
Anna Wilkinson ◽  
Carine Savalli ◽  
Emma Otta ◽  
...  
Keyword(s):  
Information Processing ◽  
Domestic Dogs ◽  
Emotional Expressions ◽  
Emotional Information ◽  
Auditory Cues ◽  
Cognitive Representations ◽  
Negative Valence ◽  
The Social ◽  
The Face ◽  
High Level

The perception of emotional expressions allows animals to evaluate the social intentions and motivations of each other. This usually takes place within species; however, in the case of domestic dogs, it might be advantageous to recognize the emotions of humans as well as other dogs. In this sense, the combination of visual and auditory cues to categorize others' emotions facilitates the information processing and indicates high-level cognitive representations. Using a cross-modal preferential looking paradigm, we presented dogs with either human or dog faces with different emotional valences (happy/playful versus angry/aggressive) paired with a single vocalization from the same individual with either a positive or negative valence or Brownian noise. Dogs looked significantly longer at the face whose expression was congruent to the valence of vocalization, for both conspecifics and heterospecifics, an ability previously known only in humans. These results demonstrate that dogs can extract and integrate bimodal sensory emotional information, and discriminate between positive and negative emotions from both humans and dogs.

Personalised‐face neutralisation using best‐matched face shape with a neutral‐face database

2017 ◽  
Vol 12 (3) ◽  
pp. 252-260 ◽  
Author(s):  
Chayanut Petpairote ◽  
Suthep Madarasmi ◽  
Kosin Chamnongthai
Keyword(s):  
Face Database ◽  
Face Shape ◽  
Neutral Face

scholarly journals The spatial distribution of eye movements predicts the (false) recognition of emotional facial expressions

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245777
Author(s):  
Fanny Poncet ◽  
Robert Soussignan ◽  
Margaux Jaffiol ◽  
Baptiste Gaudelus ◽  
Arnaud Leleu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Eye Movements ◽  
Eye Tracking ◽  
Facial Expressions ◽  
False Recognition ◽  
Recognition Task ◽  
Visual Exploration ◽  
Emotional Expressions ◽  
Facial Emotions ◽  
The Face

Recognizing facial expressions of emotions is a fundamental ability for adaptation to the social environment. To date, it remains unclear whether the spatial distribution of eye movements predicts accurate recognition or, on the contrary, confusion in the recognition of facial emotions. In the present study, we asked participants to recognize facial emotions while monitoring their gaze behavior using eye-tracking technology. In Experiment 1a, 40 participants (20 women) performed a classic facial emotion recognition task with a 5-choice procedure (anger, disgust, fear, happiness, sadness). In Experiment 1b, a second group of 40 participants (20 women) was exposed to the same materials and procedure except that they were instructed to say whether (i.e., Yes/No response) the face expressed a specific emotion (e.g., anger), with the five emotion categories tested in distinct blocks. In Experiment 2, two groups of 32 participants performed the same task as in Experiment 1a while exposed to partial facial expressions composed of actions units (AUs) present or absent in some parts of the face (top, middle, or bottom). The coding of the AUs produced by the models showed complex facial configurations for most emotional expressions, with several AUs in common. Eye-tracking data indicated that relevant facial actions were actively gazed at by the decoders during both accurate recognition and errors. False recognition was mainly associated with the additional visual exploration of less relevant facial actions in regions containing ambiguous AUs or AUs relevant to other emotional expressions. Finally, the recognition of facial emotions from partial expressions showed that no single facial actions were necessary to effectively communicate an emotional state. In contrast, the recognition of facial emotions relied on the integration of a complex set of facial cues.

scholarly journals Which facial features are central in impression formation?

2020 ◽  
Author(s):  
Bastian Jaeger ◽  
Alex Lee Jones
Keyword(s):  
Machine Learning ◽  
Social Perception ◽  
Impression Formation ◽  
Emotional Expressions ◽  
Facial Features ◽  
Relative Importance ◽  
Height Ratio ◽  
Wide Range

Which facial characteristics do people rely on when forming personality impressions from faces? Previous research has uncovered an array of facial features that influence people’s impressions. Even though some (classes of) features, such as facial width-to-height ratio or resemblances to emotional expressions, play a central role in theories of social perception, their relative importance in impression formation remains unclear. Here, we model faces along a wide range of theoretically important dimensions. We use machine learning to test how well 31 features predict impressions of trustworthiness and dominance in a diverse set of 597 faces. In line with overgeneralization theory, emotion resemblances were most predictive of both traits. Other features that have received a lot of attention in the literature, such as facial width-to-height ratio, were relatively uninformative. Our results highlight the importance of modeling faces along a wide range of dimensions to elucidate their relative importance in impression formation.

scholarly journals Web Application for Emotion-based Music Player

2021 ◽  
Vol 9 (12) ◽  
pp. 11-14
Author(s):  
Kamal Naina Soni
Keyword(s):  
Computer Vision ◽  
Human Brain ◽  
Facial Expressions ◽  
Web Application ◽  
Emotional State ◽  
Current State ◽  
The Face ◽  
Current Mood ◽  
The Individual ◽  
Music Player

Abstract: Human expressions play an important role in the extraction of an individual's emotional state. It helps in determining the current state and mood of an individual, extracting and understanding the emotion that an individual has based on various features of the face such as eyes, cheeks, forehead, or even through the curve of the smile. A survey confirmed that people use Music as a form of expression. They often relate to a particular piece of music according to their emotions. Considering these aspects of how music impacts a part of the human brain and body, our project will deal with extracting the user’s facial expressions and features to determine the current mood of the user. Once the emotion is detected, a playlist of songs suitable to the mood of the user will be presented to the user. This can be a big help to alleviate the mood or simply calm the individual and can also get quicker song according to the mood, saving time from looking up different songs and parallel developing a software that can be used anywhere with the help of providing the functionality of playing music according to the emotion detected. Keywords: Music, Emotion recognition, Categorization, Recommendations, Computer vision, Camera

The Auditory Kuleshov Effect: Multisensory Integration in Movie Editing

Perception ◽  
2016 ◽  
Vol 46 (5) ◽  
pp. 624-631 ◽  
Author(s):  
Andreas M. Baranowski ◽  
H. Hecht
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Multisensory Integration ◽  
Interaction Effect ◽  
Neutral Face ◽  
The Face ◽  
Sad Music ◽  
Ambiguous Situations

Almost a hundred years ago, the Russian filmmaker Lev Kuleshov conducted his now famous editing experiment in which different objects were added to a given film scene featuring a neutral face. It is said that the audience interpreted the unchanged facial expression as a function of the added object (e.g., an added soup made the face express hunger). This interaction effect has been dubbed “Kuleshov effect.” In the current study, we explored the role of sound in the evaluation of facial expressions in films. Thirty participants watched different clips of faces that were intercut with neutral scenes, featuring either happy music, sad music, or no music at all. This was crossed with the facial expressions of happy, sad, or neutral. We found that the music significantly influenced participants’ emotional judgments of facial expression. Thus, the intersensory effects of music are more specific than previously thought. They alter the evaluation of film scenes and can give meaning to ambiguous situations.

Face aftereffect in haptic perception

2012 ◽  
Vol 25 (0) ◽  
pp. 46-47
Author(s):  
Kazumichi Matsumiya
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Haptic Perception ◽  
Three Dimensional ◽  
Eyes Closed ◽  
Neutral Face ◽  
Visual Phenomenon ◽  
The Face ◽  
The Right ◽  
Graphics Software

Adaptation to a face belonging to a facial category, such as expression, causes a subsequently neutral face to be perceived as belonging to an opposite facial category. This is referred to as the face aftereffect (FAE) (Leopold et al., 2001; Rhodes et al., 2004; Webster et al., 2004). The FAE is generally thought of as being a visual phenomenon. However, recent studies have shown that humans can haptically recognize a face (Kilgour and Lederman, 2002; Lederman et al., 2007). Here, I investigated whether FAEs could occur in haptic perception of faces. Three types of facial expressions (happy, sad and neutral) were generated using a computer-graphics software, and three-dimensional masks of these faces were made from epoxy-cured resin for use in the experiments. An adaptation facemask was positioned on the left side of a table in front of the participant, and a test facemask was placed on the right. During adaptation, participants haptically explored the adaptation facemask with their eyes closed for 20 s, after which they haptically explored the test facemask for 5 s. Participants were then requested to classify the test facemask as either happy or sad. The experiment was performed under two adaptation conditions: (1) with adaptation to a happy facemask and (2) with adaptation to a sad facemask. In both cases, the expression of the test facemask was neutral. The results indicate that adaptation to a haptic face that belongs to a specific facial expression causes a subsequently touched neutral face to be perceived as having the opposite facial expression, suggesting that FAEs can be observed in haptic perception of faces.

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