Quantifying dynamic facial expressions under naturalistic conditions.

ABSTRACT: Facial affect is expressed dynamically - a giggle, grimace, or an agitated frown. However, the characterisation of human affect has relied almost exclusively on static images. This approach cannot capture the nuances of human communication or support the naturalistic assessment of affective disorders. Using the latest in machine vision and systems modelling, we studied dynamic facial expressions of people viewing emotionally salient film clips. We found that the apparent complexity of dynamic facial expressions can be captured by a small number of simple spatiotemporal states - composites of distinct facial actions, each expressed with a unique spectral fingerprint. Sequential expression of these states is common across individuals viewing the same film stimuli but varies in those with the

SUBMITTER: Jeganathan J 

PROVIDER: S-EPMC9439684 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature