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.
|Number of pages||7|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics|
|Early online date||22 Jan 2010|
|Publication status||Published - 1 Feb 2011|
- biologically inspired
- scene classification
- video surveillance