This thesis shows how to detect boundaries on the basis of motion information alone. The detection is performed in two stages: (i) the local estimation of motion discontinuities and of the visual flowsfield; (ii) the extraction of complete boundaries belonging to differently moving objects. For the first stage, three new methods are presented: the "Bimodality Tests,'' the "Bi-distribution Test,'' and the "Dynamic Occlusion Method.'' The second stage consists of applying the "Structural Saliency Method,'' by Sha'ashua and Ullman to extract complete and unique boundaries from the output of the first stage. The developed methods can successfully segment complex motion sequences.

A representation of visual motion convenient for recognition shouldsmake prominent the qualitative differences among simple motions. Wesargue that the first stage in such a motion representation is to makesexplicit boundaries that we define as starts, stops, and forcesdiscontinuities. When one of these boundaries occurs in motion, humansobservers have the subjective impression that some fleeting,ssignificant event has occurred. We go farther and hypothesize that onesof the subjective motion boundaries is seen if and only if one of oursdefined boundaries occurs. We enumerate all possible motion boundariessand provide evidence that they are psychologically real.