• DocumentCode
    3114306
  • Title

    Abnormal behavior detection based on spatial-temporal features

  • Author

    Jinhai Xiang ; Heng Fan ; Jun Xu

  • Author_Institution
    Coll. of Sci., Huazhong Agric. Univ., Wuhan, China
  • Volume
    02
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    871
  • Lastpage
    876
  • Abstract
    Abnormal behavior detection is an important issue in video surveillance. This paper presents an approach for abnormal behavior detection based on spatial-temporal features. First, the proposed method extracts moving objects from video sequence. Then, it tracks moving objects to detect their overlapping. Finally, a clutter-model is built up based on the changes of spatial-temporal feature to detect abnormal behavior. Experimental results show the effectiveness of the proposed approach.
  • Keywords
    object tracking; video surveillance; abnormal behavior detection; clutter model; moving object tracking; spatial-temporal features; video sequence; video surveillance; Abstracts; Abnormal behavior detection; Clutter-model; Object tracking; Spatial-temporal features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890406
  • Filename
    6890406
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3114306