基于Mean-Shift的运动目标跟踪

Mean-Shift跟踪算法由于计算复杂度低、跟踪效果好、实时性强等优点被越来越多地应用到视觉跟踪领域.对Mean-Shift算法的跟踪原理进行详细分析,给出基于该算法的运动目标跟踪过程及实现方法.最后,对复杂背景下人物序列图像进行跟踪实验,实验结果表明,该方法具有很好的跟踪性能,对于短暂小幅遮挡具有很好的鲁棒性.

Moving object tracking based on Mean-Shift

Mean-Shift tracking algorithm is widely used in vision tracking field because its low computarion complexity, better tracking effect and good real-time performance. Mean-Shift tracking principle is analyzed particularly. The moving object tracking course and realization mthod based on Mean-Shift are proposed. At last, experiments are taken using human sequence images in complex background. The experiment results indicate that this method takes on the better tracking performance, and better robust for transitory small occulusion.