Biologically inspired features for scene classification in video surveillance

Kaiqi Huang*, Dacheng Tao, Yuan Yuan, Xuelong Li, Tieniu Tan

*Corresponding author for this work

Research output: Contribution to journalLetter, comment/opinion or interviewpeer-review


Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

Original languageEnglish
Pages (from-to)307-313
Number of pages7
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number1
Early online date22 Jan 2010
Publication statusPublished - 1 Feb 2011


  • biologically inspired
  • scene classification
  • video surveillance


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