Complex event recognition with uncertainty reasoning

Xueqin Liu, Kathy Clawson, Hui Wang, Bryan Scotney, Jun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios.
Original languageEnglish
Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
Place of PublicationUnited States
PublisherIEEE Computer Society
Pages1823-1828
Number of pages6
ISBN (Electronic)978-1-4799-0260-6
DOIs
Publication statusPublished - 08 Sep 2014
Externally publishedYes

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
PublisherIEEE Computer Society
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Bibliographical note

Publisher Copyright: © 2013 IEEE.; 12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 ; Conference date: 14-07-2013 Through 17-07-2013

Keywords

  • Complex event recognition
  • Hierarchical approach
  • Knowledge base
  • Uncertainty reasoning
  • Video pattern recognition

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