鉴于现有的均值漂移跟踪算法不能适应目标运动速度过快和全部遮挡，并且由于存在开方、除法等大量浮点运算，在定点DSPs数字信号处理器中应用难于满足实时跟踪要求。本文在核密度估计，均值漂移算法迭代权值，Bhattacharyya系数等方面进行改进，给出优化的算法流程。不仅增强了目标与背景相似时搜索目标的能力，而且全部使用整点运算，计算时间满足实时跟踪要求。通过将优化算法与卡尔曼轨迹预测相结合，解决了目标运动速度过快和全部遮挡问题。目前该算法已经成功嵌入TMS320C6416硬件平台，实验结果表明，在混乱背景、目标发生旋转、遮挡、形状变化、运动速度过快等情况下，该算法能够保持连续稳定的实时跟踪。

The current mean shift tracking algorithm is not suitable for the targets that move fast and with entire occlusions and is hard to realize real time tracking when it is applied in the pointing digital signal processors due to much floating point operation. This paper provides the optimal algorithm which contains some improvements of the kernel function, Mean Shift alterative weight and Bhattacharyya coefficient. These improvements not only enhance the capacity of tracking the object which resembles the background but also employ pointing operation to satisfy the need of the real time tracking. Furthermore, the target moving fast and entire occlusions are resolved through combining the optimal algorithm with the Kalman forecast. Now, the algorithm is applied in the TMS320C6416 hardware system and successfully copes with clutter, target occlusions, revolution, scale variations and moving fast in the real time tracking.