(Full text is available in Postscript ).

Computing occluding and transparent motions
Michal Irani, Benny Rousso, and Shmuel Peleg

Computing the motions of several moving objects in image sequences involves simultaneous motion analysis and segmentation. This task can become complicated when image motion changes significantly between frames, as with camera vibrations. Such vibrations make tracking in longer sequences harder, as temporal motion constancy can not be assumed. The problem becomes even more difficult in the case of transparent motions.

A method is presented for detecting and tracking occluding and transparent moving objects, which uses temporal integration without assuming motion constancy. Each new frame in the sequence is compared to a dynamic internal representation image of the tracked object. The internal representation image is constructed by temporally integrating frames after registration based on the motion computation. The temporal integration maintains sharpness of the tracked object, while blurring objects having other motions. Comparing new frames to the internal representation image causes the motion analysis algorithm to continue tracking the same object in subsequent frames, and to improve the segmentation.