Universitätspublikationen
Refine
Year of publication
- 2018 (2)
Document Type
- Article (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- videos (2) (remove)
Institute
- Medizin (1)
- Psychologie (1)
When mapping eye-movement behavior to the visual information presented to an observer, Areas of Interest (AOIs) are commonly employed. For static stimuli (screen without moving elements), this requires that one AOI set is constructed for each stimulus, a possibility in most eye-tracker manufacturers' software. For moving stimuli (screens with moving elements), however, it is often a time-consuming process, as AOIs have to be constructed for each video frame. A popular use-case for such moving AOIs is to study gaze behavior to moving faces. Although it is technically possible to construct AOIs automatically, the standard in this field is still manual AOI construction. This is likely due to the fact that automatic AOI-construction methods are (1) technically complex, or (2) not effective enough for empirical research. To aid researchers in this field, we present and validate a method that automatically achieves AOI construction for videos containing a face. The fully-automatic method uses an open-source toolbox for facial landmark detection, and a Voronoi-based AOI-construction method. We compared the position of AOIs obtained using our new method, and the eye-tracking measures derived from it, to a recently published semi-automatic method. The differences between the two methods were negligible. The presented method is therefore both effective (as effective as previous methods), and efficient; no researcher time is needed for AOI construction. The software is freely available from https://osf.io/zgmch/.
According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.