实际场景中往往存在运动阴影和障碍物遮挡等情况，严重影响了目标检测和跟踪的效果。为解决此问题，提出了一种抗阴影和遮挡的的运动目标检测与跟踪方法。该方法首先引入分类浮动更新策略，有效减轻了运算负担；其次，利用基于纹理梯度差和颜色特征不变量的阴影检测模块，为后续更加准确的分割前景创造了条件；然后采用基于 MeanShift框架和最大化后验概率匹配相结合的方式跟踪目标，并引入了障碍遮挡跟踪机制，以降低运动目标在遮挡场景跟丢的可能性。实验表明，该方法可有效检测出运动目标的阴影，实现在遮挡场景对运动目标的稳定跟踪。

Moving shadow interference and obstacles occlusion problem is very universal in the actual scene, and it seriously influenced the effect of object detecting and tracking. To solve the problems, a detecting and tracking method based on shadow detecting and occlusion environment is presented. Firstly, the classification floating refresh strategy is performed to lighten operation burden. Then, a shadow detecting module based on texture gradient difference and color feature invariant is introduced to more precise distinguish foreground. While tracking movind objects, the method based on meanshift combines with maximum posterior probability is used. Meanwhile, the mechanism of obstacles occlusion tracking is introduced to reduce the possibility of moving objects missing in the occlusion environment. Experiments show, the proposed algorithm can effectively detect the shadow of moving objects, and it also can precisely track the objects occluded.