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Zakia Hammal, Frédéric Gosselin, Isabelle Fortin; How efficient are the recognition of dynamic and static facial expressions?. Journal of Vision 2009;9(8):499. doi: 10.1167/9.8.499.
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© ARVO (1962-2015); The Authors (2016-present)
Recently, Ambadar, Schooler and Cohn (2005) compared facial expression recognition performance with static and dynamic stimuli. To control for task difficulty, the researchers equated the information content in their dynamic and in their so-called “multi-static” condition, in which the frames of the dynamic stimuli were separated by noise masks and were played very slowly. Observers were better at discriminating dynamic than multi-static stimuli but only when the facial expressions were subtle. This result, however, might be due to low-level masking or to some high-level memory decay rather than to observer's sensitivity to facial expression movement per se. Here, we factored out task difficulty by measuring the calculation efficiency for the static vs. dynamic recognition of eight facial expressions (happiness, fear, sadness, disgust, surprise, anger, and pain). Contrary to sensitivity measures, such as the d', efficiency measures are directly comparable across tasks. Twenty naïve observers will participate to the experiment. We will extract their energy thresholds for the recognition of static and dynamic facial expressions (drawn from sets of 80 static and 80 dynamic stimuli) in five levels of external noise using the method of constant stimuli (5–10 levels of energy per noise level). Calculation efficiencies will be computed by dividing the slopes of the lines that best fit the energy thresholds of ideal and human observers. Preliminary results obtained on three observers yield efficiencies of about 20.43%, 11.46%, 11.95% and 10.4%, 8.76%, 7.36%, respectively, for the recognition of static and dynamic facial expressions.
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