对运动人体颜色与背景颜色近似时，单个颜色空间不能很好地刻画人体与背景之间的差别这一问题，本文提出一种多颜色空间不同颜色分量融合的策略，即对多个颜色空间的各个分量进行单独的人体检测，统计人体检测性能最好的若干个通道，对这些通道的前景进行融合，得到最终的人体检测结果。另外，为了处理动态背景问题，设计一种基于帧间差分法和定时刷新的背景更新算法。实验结果表明，在复杂场景中，该算法的检测结果要好于基于单颜色空间的人体检测结果，并且该算法能够有效地处理动态背景问题。

When the color of a moving human is similar to the color of the background, one single color space can not very vell describe the differences between the moving human and the background.Faced with this problem,we propose a multi-color space merging strategy. Moving human detection is conducted separately by finding channels which have the best performance, based on a single channel of color space. Moving human detection then can be concluded by merging these channels. Moreover to solve the dynamic background problem, we designed a background updating algorithm which depends on temporal differencing and refreshing. Experiments confirm that in a complex environment, results of our algorithm are better than test results of the algorithm based on a single color space. The algorithm also can deal with dynamic backgrounds effectively.