Using Motion Histories for Eye Contact Detection in Multiperson Group Conversations

Eugene Yujun Fu, Michael W. Ngai

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Eye contact detection in group conversations is the key to developing artificial mediators that can understand and interact with a group. In this paper, we propose to model a group's appearances and behavioral features to perform eye contact detection for each participant in the conversation. Specifically, we extract the participants' appearance features at the detection moment, and extract the participants' behavioral features based on their motion history image, which is encoded with the participants' body movements within a small time window before the detection moment. In order to attain powerful representative features from these images, we propose to train a Convolutional Neural Network (CNN) to model them. A set of relevant features are obtained from the network, which achieves an accuracy of 0.60 on the validation set in the eye contact detection challenge in ACM MM 2021. Furthermore, our experimental results also demonstrate that making use of both participants' appearance and behavior features can lead to higher accuracy at eye detection than only using one of them.

Original languageEnglish
Title of host publicationMM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages4873-4877
Number of pages5
ISBN (Electronic)9781450386517
DOIs
Publication statusPublished - 17 Oct 2021
Event29th ACM International Conference on Multimedia, MM 2021 - Virtual, Online, China
Duration: 20 Oct 202124 Oct 2021

Publication series

NameMM 2021 - Proceedings of the 29th ACM International Conference on Multimedia

Conference

Conference29th ACM International Conference on Multimedia, MM 2021
Country/TerritoryChina
CityVirtual, Online
Period20/10/2124/10/21

Keywords

  • deep learning
  • eye contact detection
  • group behavior
  • motion history image

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software
  • Computer Graphics and Computer-Aided Design

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