Discovering Gender Differences in Facial Emotion Recognition via Implicit Behavioral Cues
This work addresses gender-specific cognitive processing in emotion recognition, which could inform personalized human-computer interaction systems, but it is incremental as it builds on existing EEG and eye-tracking methods.
The study tackled gender differences in facial emotion recognition by analyzing EEG and eye movement cues from 28 participants, finding reliable gender and emotion recognition with differential cognitive processing for negative emotions between males and females, even under partial face occlusion.
We examine the utility of implicit behavioral cues in the form of EEG brain signals and eye movements for gender recognition (GR) and emotion recognition (ER). Specifically, the examined cues are acquired via low-cost, off-the-shelf sensors. We asked 28 viewers (14 female) to recognize emotions from unoccluded (no mask) as well as partially occluded (eye and mouth masked) emotive faces. Obtained experimental results reveal that (a) reliable GR and ER is achievable with EEG and eye features, (b) differential cognitive processing especially for negative emotions is observed for males and females and (c) some of these cognitive differences manifest under partial face occlusion, as typified by the eye and mouth mask conditions.