背景建模是实现运动目标检测与跟踪的关键技术之一。在实时视频监控系统中，对背景建模算法的运行时间及所提取出的背景图像的实时性有很高的要求，针对这一问题，提出了一种基于切比雪夫不等式的自适应阈值背景建模算法。算法利用切比雪夫不等式计算像素点色度变化的概率估计值，提出了一种自适应阈值分类方法，它将像素点快速分类为前景点、背景点及可疑点，再利用核密度估计方法对可疑点进行进一步分类，最后利用背景更新算法提取实时背景图像。实验结果证明，该算法能快速有效地区分特征明显的背景点与前景点，提高了背景图像提取的速度，对可疑点利用核密度估计方法降低了背景分割的误差，背景建模效果理想，运算速度快，适用于实时视频监控系统。-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