2017/08/29 by Maneesh Bilalpur, Bilalpur, Maneesh, Seyed Mostafa Kia +6
Computer Science · Neuroscience · Psychology · #Emotion and Mood Recognition #FOS: Computer and information sciences #Face Recognition and Perception #Face recognition and analysis #H.1.2 #H.5.2 #Human-Computer Interaction (cs.HC) #I.3.6 #cs.HC
paper · pdf · doi:10.48550/arxiv.1708.08729
To be published in the Proceedings of Seventh International Conference on Affective Computing and Intelligent Interaction.2017
arxiv created 2017/08/29 · openalex publication_date 2017/08/29 · arxiv updated 2017/08/30 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
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.