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.