提出一种基于背景码本模型的视频图像中运动目标的检测算法。该算法利用归一化的Mann-Whitney秩和统计量自适应调整判决阈值，使用Mean Shift进行码本中码字和方差的更新，实现在检测过程中同时更新码本模型适应图像背景的变化。不同背景条件下的实验结果表明该算法利用Mann-Whitney秩和统计量的分布无关性，提高了运动目标检测精度。\r\n。

In this paper an algorithm of moving objects detection in video image was proposed, which is based on the background codebook model. In this algorithm, normalized Mann-Whitney rank-sum test was used to adjust the detection threshold of codebook model, and Mean Shift was also used to update the code and variance. So this algorithm can achieve the updating of codebook model and the detection of moving objects at the same time. The experimental results show that based on the distribution independence of Mann-Whitney rank-sum test this method can detect the moving objects efficiently under different conditions.