针对复杂背景的视频图像多目标跟踪遮挡问题，提出了一种多特征融合匹配的多目标跟踪方法。基于自适应高斯混合背景模型重构和更新背景策略，实现当前帧背景减除和多目标检测；采用目标的颜色特征、质心位置、运动速度等特征进行融合匹配跟踪；最后，通过区域辅助判定策略将场景下的目标状态分为目标进入场景、目标退出场景、目标暂消、目标重现、目标融合和分裂5种状态，用质心预测方法和遮挡因子辅助匹配来提高匹配正确率。仿真实验结果表明：采用该方法跟踪同一目标和不同目标的相似度平均值分别为0949 71和0505 73，优于单一颜色特征信息匹配；目标遮挡结束后重新匹配相似度为0972 83，实现了复杂背景下具有表面相似性的多目标实时跟踪。

In order to solve the occlusion problem in multi-object tracking for the complex background of a video image, an approach for the multi-object tracking based on multi-feature joint matching is presented. First, the adaptive Gaussian mixture background model is used for reconstructing and updating the background to achieve the background subtraction of current frame and multi-object detection. Then, the joint matching tracking is developed based on matching color characteristics, positions and objects velocities. Finally, the objects in the scene are divided into entering, exiting, temporarily disappear of the object, the re-emergence of the object and the merge and split of the object, and the predicted position and the occlusion factor of the object are used to improve the accuracy of multi-feature joint matching. Experimental results indicate that the similarities of the same object and the different objects are 0949 71 and 0505 73 respectively in the tracking with the proposed approach, which is better than that of matching with the color characteristics. Furthermore, the similarity of object is 0972 83 after occlusion. The approach is satisfactory for real-time tracking of multi-object with appearance similarity in a complex environment.