English

Discovering Gender Differences in Facial Emotion Recognition via Implicit Behavioral Cues

Human-Computer Interaction 2017-08-30 v1

Abstract

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.

Keywords

Cite

@article{arxiv.1708.08729,
  title  = {Discovering Gender Differences in Facial Emotion Recognition via Implicit Behavioral Cues},
  author = {Maneesh Bilalpur and Seyed Mostafa Kia and Tat-Seng Chua and Ramanathan Subramanian},
  journal= {arXiv preprint arXiv:1708.08729},
  year   = {2017}
}

Comments

To be published in the Proceedings of Seventh International Conference on Affective Computing and Intelligent Interaction.2017

R2 v1 2026-06-22T21:26:26.938Z