Biologically inspired features for scene classification in video surveillance

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 41, Issue 1, 2011, Pages 307-313

  Huang, Kaiqi ^a   Tao, Dacheng ^b   Yuan, Yuan ^c   Li, Xuelong ^d   Tan, Tieniu ^a  

^a INSTITUTE OF AUTOMATION   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c ASTON UNIVERSITY   (United Kingdom)

^d XI AN INSTITUTE OF OPTICS AND PRECISION MECHANICS   (China)

Author keywords

Biologically inspired; scene classification; video surveillance

Indexed keywords

BIOLOGICALLY INSPIRED; HUMAN VISUAL; LOWER COMPLEXITY; SCENE CLASSIFICATION; STANDARD MODEL; VIDEO SURVEILLANCE;

MONITORING;

SECURITY SYSTEMS;

ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; FACTUAL DATABASE; HEALTH SURVEY; HUMAN; IMAGE PROCESSING; METHODOLOGY; VIDEORECORDING; VISION;

ARTIFICIAL INTELLIGENCE; BAYES THEOREM; DATABASES, FACTUAL; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; POPULATION SURVEILLANCE; VIDEO RECORDING; VISUAL PERCEPTION;

EID: 79551681231     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2009.2037923     Document Type: Article

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