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Improving Robustness and Accuracy in Moving Object Detection Using Section-Distribution Background Model

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3 Author(s)
Yi Tang ; Sch. of Civil & Transp. Eng., South China Univ. of Technol., Guangzhou ; Wei-Ming Liu ; Liang Xiong

In this paper, a new integrated approach for moving object detection is proposed. In initialization, a statistical algorithm is used to obtain the section-distribution background model which provides a scheme of choosing every parameter value in algorithm. The model is also updated real time in order to adapt to changes of illumination and objects in the scene. After applying a threshold to separate candidates in foreground and background, a shadow detection scheme is also introduced in this paper. It is based on HSV color space information and makes use of our background model. Finally, a comparison has been made among our algorithm and other algorithms. The results show improving robustness and accuracy of the model using our update algorithm.

Published in:

2008 Fourth International Conference on Natural Computation  (Volume:6 )

Date of Conference:

18-20 Oct. 2008