Adaptive background model

Xiaochun Lu; Yijun Xiao; Zhi Chai; Bangping Wang

doi:10.1117/12.750992

15 November 2007 Adaptive background model

Xiaochun Lu, Yijun Xiao, Zhi Chai, Bangping Wang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678651 (2007) https://doi.org/10.1117/12.750992
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

An adaptive background model aiming at outdoor vehicle detection is presented in this paper. This model is an improved model of PICA (pixel intensity classification algorithm), it classifies pixels into K-distributions by color similarity, and then a hypothesis that the background pixel color appears in image sequence with a high frequency is used to evaluate all the distributions to determine which presents the current background color. As experiments show, the model presented in this paper is a robust, adaptive and flexible model, which can deal with situations like camera motions, lighting changes and so on.

Citation Download Citation

Xiaochun Lu, Yijun Xiao, Zhi Chai, and Bangping Wang "Adaptive background model", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678651 (15 November 2007); https://doi.org/10.1117/12.750992

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