ABSTRACTDynamic changes in emotional expressions are a valuable source of information in social interactions. As the expressive behaviour of a person changes, the inferences drawn from the behaviour may also change. Here, we test the possibility that dynamic changes in emotional expressions affect person perception in terms of stable trait attributions. Across three experiments, we examined perceivers’ inferences about others’ personality traits from changing emotional expressions. Expressions changed from one emotion to another emotion, allowing us to disentangle potential primacy, recency, (...) and averaging effects. Drawing on three influential models of person perception, we examined perceptions of dominance and affiliation, competence and warmth, and dominance and trustworthiness. A strong recency effect was consistently found across all trait judgments, that is, the end emotion of dynamic expressions had a strong impact on t... (shrink)

Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers categorized (...) the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community. (shrink)