Complex event recognition with uncertainty reasoning

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

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Citations (Scopus)

    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
    PublisherIEEE Computer Society
    Pages1823-1828
    Number of pages6
    ISBN (Electronic)9781479902576
    DOIs
    Publication statusPublished - 2013
    Event12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 - Tianjin, China
    Duration: 14 Jul 201317 Jul 2013

    Publication series

    NameProceedings - International Conference on Machine Learning and Cybernetics
    Volume4
    ISSN (Print)2160-133X
    ISSN (Electronic)2160-1348

    Conference

    Conference12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
    CountryChina
    CityTianjin
    Period14/07/1317/07/13

    Keywords

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

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