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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2009, Vol. 10 Issue (7): 976-984    DOI: 10.1631/jzus.A0820489
Electrical and Electronic Engineering     
General moving objects recognition method based on graph embedding dimension reduction algorithm
Yi ZHANG, Jie YANG, Kun LIU
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China
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Abstract  Effective and robust recognition and tracking of objects are the key problems in visual surveillance systems. Most existing object recognition methods were designed with particular objects in mind. This study presents a general moving objects recognition method using global features of targets. Targets are extracted with an adaptive Gaussian mixture model and their silhouette images are captured and unified. A new objects silhouette database is built to provide abundant samples to train the subspace feature. This database is more convincing than the previous ones. A more effective dimension reduction method based on graph embedding is used to obtain the projection eigenvector. In our experiments, we show the effective performance of our method in addressing the moving objects recognition problem and its superiority compared with the previous methods.

Key words： Moving objects recognition      Adaptive Gaussian mixture model      Principal component analysis      Linear discriminant analysis      Marginal Fisher analysis     
Received: 25 June 2008     
CLC:  TP317.4  
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Yi ZHANG
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Yi ZHANG, Jie YANG, Kun LIU. General moving objects recognition method based on graph embedding dimension reduction algorithm. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2009, 10(7): 976-984.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.A0820489     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2009/V10/I7/976

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