针对多目标跟踪,运动目标身份标号在目标发生遮挡、交错时容易混淆的问题,提出一种基于颜色特征信息的多目标跟踪算法。即在目标跟踪过程中,充分利用背景减除法所获取的前景团块区域,对其进行有效分类,如噪声区域、单目标区域和多目标区域,根据分类情况采用不同的处理机制。算法利用修正时间印机制处理噪声区域,利用Kalman预测处理快速运动,利用均值移动算法处理目标标识混淆问题。通过多组实验可以看出,新算法处理速度达到30帧/s、实时性能好,具有很强地抑制背景干扰、目标长时间跟踪的特性。

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.