Abstract: Traditional multi feature fusion particle filter algorithm has huge amount of computation,which is not conducive to timeliness.Meanwhile,the algorithm often generates error for tracking and matching.To solve these problem better,this paper adopted the multi feature fusion particle filter algorithm founded in direction vector.Firstly,the algorithm adds the value of multiplicative fusion and additive fusion through the body color feature and contour feature.In addition,on the basis of the uncertainty multiplication of two features,the respective weights proportion in the tracking process is adjusted according to the actual contribution rate of two kinds of features.Moreover,the probable range of the movement of objects can be predicted to reduce the amount of calculation of particle iteration by combining the direction vector.At last,the merge human’s body can be separated by adjusting the window automatically and precisely.The test shows our method can realize the human tracking accurately in the complex environment.

Key words: Particle filter,Multi feature fusion,Human tracking,Uncertainty