A new Sequential Monte Carlo-Mean Shift Monte Carlo(MSMC) algorithm is proposed for visual tracking in image sequences. The MSMC invokes Mean Shift to converge the samples with smaller weight to the local maximum ones

and can maintain the diversity with fewer samples

so the computational load can be decreased greatly. Experimental results in real video data show that the algorithm outperforms in terms of accuracy in estimating the target position and completing in real-time.