Group interaction analysis in dynamic context

Peng Dai*, Huijun Di, Ligeng Dong, Linmi Tao, Guangyou Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.

Original languageEnglish
Pages (from-to)34-42
Number of pages9
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume39
Issue number1
DOIs
Publication statusPublished - 2009
Externally publishedYes

Keywords

  • Dynamic Bayesian network (DBN)
  • Dynamic context model
  • Group interaction analysis
  • Meeting analysis

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