July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Beyond Facial Morphology: Social Impressions from Dynamic Face Gestures
Author Affiliations
  • Daniel Gill
    Institute of Neuroscience and Psychology, University of Glasgow
  • Oliver Garrod
    Institute of Neuroscience and Psychology, University of Glasgow
  • Rachael Jack
    Institute of Neuroscience and Psychology, University of Glasgow
  • Philippe Schyns
    Institute of Neuroscience and Psychology, University of Glasgow
Journal of Vision July 2013, Vol.13, 1270. doi:10.1167/13.9.1270
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      Daniel Gill, Oliver Garrod, Rachael Jack, Philippe Schyns; Beyond Facial Morphology: Social Impressions from Dynamic Face Gestures. Journal of Vision 2013;13(9):1270. doi: 10.1167/13.9.1270.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 

Social trait inference from faces exerts a huge impact on social outcomes ranging from mate choice to voting preferences (Todorov et al. 2005; Rhodes, G., 2006). Although previous studies have identified from static faces the morphological face features which influence social judgements (Dotsch & Todorov, 2012), the question is whether the dynamics of facial muscles can flexibly and transiently produce specific expressions that signal important social traits for social interactions. We addressed this question by: (i) quantifying the influence of dynamic facial expressions on judgments of social traits; (ii) teasing apart the contribution of facial morphology and facial expressions to social trait judgments; and (iii) measuring the similarities of facial expressions between social traits and emotions.

 

We used a computer graphics platform that parametrically controls the dynamics of any facial muscle group (coded as 41 different Action Units, Ekman, 1978), each animated with 6 temporal parameters: peak amplitude, peak latency, onset latency, offset latency, acceleration, deceleration (Yu et al. 2012). Twelve participants judged the trustworthiness, dominance, attractiveness (and perceived intensity) of a series of facial animations of randomly chosen Action Units and their dynamic parameters. Reverse correlation estimated the expressions as sets of facial movements associated with the perception of each social trait and their intensity. Results were highly consistent between participants, with attractiveness and trustworthiness positively correlated with each other and negatively correlated with dominance. In addition, a comparison of these facial expressions with those similarly derived for facial emotions (Jack et al. 2012) showed that social trait expressions are not simple one-to-one overgeneralisations of emotional expressions, but a distinct set of signals composed of movements from different emotion categories. To conclude, we show that the face can flexibly and transiently produce facial movements that modulate social signals of attractiveness, trustworthiness and dominance that are paramount for social interactions.

 

Meeting abstract presented at VSS 2013

 
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