Motion-based segmentation using a thresholded merging strategy on watershed segments

We assess the performance of a thresholded merging technique used as part of a procedure to obtain a motion-based segmentation of an image sequence. First an initial estimate for the motion field is obtained by using an improved block matching method. Then, an intensity-based initial segmentation is performed, using watershed segmentation on a non-linearly diffused version of the image. Next, a motion vector based on the initial motion field is calculated for each segment, and, finally, the obtained segments and their motion vectors are fed into the motion-based merging scheme, yielding the final segmentation. Results for a thresholded minimum distance merging technique are given and are compared with a K-means clustering algorithm