Biologically Inspired Features for Scene Classification in Video Surveillance

Authors:
Kaiqi Huang;Dacheng Tao;Yuan Yuan;Xuelong Li;Tieniu Tan
Affiliations:
Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China;-;-;-;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2011

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Abstract

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.