Abstract: We proposed an automatic motion segmentation operating on sparse feature points.Feature points are detected and tracked throughout an image sequence,and feature points are grouped using a mean shift algorithm．The motion segmentation is driven by the density of the motion vector in feature space．The kernel density estimation is performed on the mean-shifted motion vector and the number of motion present is estimated by the number of peaks in the kernel density curve.Experimental results on a number of challenging image sequences demonstrate the effectiveness and robustness of the technique.

Key words: Mean shift,Motion segmentation,Kernel density estimation