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An improved mixture-of-Gaussians model for background subtraction

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4 Author(s)
Heng-hui Li ; Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, 300300, China ; Jin-feng Yang ; Xiao-hui Ren ; Ren-biao Wu

The process of background subtraction is always a key step in surveillance. Currently, the mixture of Gaussians (MOG) works well in the background modeling and has been widely used in practice. In this paper, some new additional constrains are imposed on the updating process of statistics of Gaussian models. To reduce computational cost, the numbers of Gaussian models are selected dynamically based on the maximum recurrence time interval (MRTI). The experimental results show that the proposed method performs well in complex background modeling, and the efficiency in object detection is improved significantly.

Published in:

2008 9th International Conference on Signal Processing

Date of Conference:

26-29 Oct. 2008