A New Motion Detection Algorithm Based on Snake and Mean Shift
Yulan Liu, Silong Peng · 2008
Active contour model and mean shift are both motion detection algorithms. Each of them has its own merits and shortcomings. An active contour tends to be tracked by noise points and results in a false boundary. A mean shift vector always points to the edge area when the start point is around the object With initial curves given near the objects in each image automatically, we presented a new motion detection algorithm which used the internal energy of active contour to keep a curve continuous and smooth, and also used the mean shift vector to track the curve to the real object boundary step by step, with an iterative process. Experimental results showed that this algorithm can improve the segmenting results greatly in noisy videos.