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.