Improved target tracking algorithm based on Mean-shift

Abstract

Traditional Mean-shift target tracking algorithm is rather sensitive to background environment. The use of kernel weighted histogram for target template and target candidates can not always get exact center of the target. Therefore, an improved feature selection mechanism was proposed, in which background weighted histogram was chosen for target template and kernel weighted histogram for target candidates. The simulation results show that the method achieves more accurate target tracking in complex environments.