The target tracking only using single feature is difficult to overcome the influence of external conditions such as the illumination and target deformation etc.,a particle filter target tracking algorithm based on the covariance region descriptor is proposed. The covariance descriptor can fuse different features of the target region to handle target tracking under complex background. And then,the tracking robustness is improved. Moreover,aiming at the problem that calculation of particle filter is large,the integral covariance matrix computation is introduced to Bayesian tracking framework,which makes the tracking process realtime. The comparative experiments show that the proposed algorithm is more robust and faster than the single feature tracking.