Introduction - If you have any usage issues, please Google them yourself
Background modeling is a key technology to realize the moving target detection and tracking. In real-time video surveillance system, there are high demands on uptime and background modeling algorithm is proposed to remove the background image in real time, for this problem, a Chebyshev inequality based on adaptive threshold background modeling algorithm. Cut algorithm uses to calculate the probability of Chebyshev inequality pixel color change estimates, an adaptive threshold classification method, it will be classified as pre-fast pixel of interest, background points and suspicious points, re-use kernel density estimation method suspicious point for further classification. Finally, background updating algorithm to extract real-time background image. Experimental results show that the algorithm can quickly and efficiently in the background of significant features of the region of interest with the previous point, improving the speed of extraction of the background image, the point of s