Multi-target tracking algorithms with identification label
具有身份标识的多目标跟踪

In order to solve the problem of target identification label confusion in multi-target tracking,especially with occluded or stacked targets, an algorithm based on color features is proposed for multi-target tracking. In the process of target tracking, the foreground is derived using the background subtraction method. The blobs in the foreground are classified into noise regions, single target regions,and multi-target regions. According to the blob classification, a different processing mechanism is used. The system adapts the correction time stamp to process noise regions, using Kalman prediction processing for fast motions and using the mean shift algorithm for processing target identification labels.Through several experiments, we show that the new algorithm has a good real-time performance (the tracking speed is 30 f/s), has a very strong background suppression, and has the characteristics for long-time target tracking.