Discovering gender differences in facial emotion recognition via implicit behavioral cues

Maneesh Bilalpur, Seyed Mostafa Kia, Tat Seng Chua, Ramanathan Subramanian

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
EditorsCarlos Busso, Julien Epps
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages119-124
Number of pages6
ISBN (Electronic)9781538605639
ISBN (Print)9781538605639
DOIs
Publication statusPublished - 2 Jul 2017
Externally publishedYes
Event7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017 - San Antonio, United States
Duration: 23 Oct 201726 Oct 2017

Publication series

Name2017 7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
Volume2018-January

Conference

Conference7th International Conference on Affective Computing and Intelligent Interaction, ACII 2017
Country/TerritoryUnited States
CitySan Antonio
Period23/10/1726/10/17

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