A novel highway background generate approach
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
A novel robust statistical method for background initialization and visual surveillance
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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Initializing a background model requires robust statistical methods as the task should be robust against random occurrences of foreground objects, as well as against general image noise. The median has been employed for the problem of background initialization. However, the median has only a breakdown point of 50%. In this paper, we propose a new robust method which can tolerate more than 50% of noise and foreground pixels in the background initialization process. We compare our new method with five others and give quantitative evaluations on background initialization. Experiments show that the proposed method achieves very promising results in background initialization.