Recognition of Occluded Objects

Abstract

Matching of occluded objects is one of the prime capabilities of any computer vision system. In this paper a hierarchical stochastic labeling technique to do shape matching of 2-D occluded objects is presented. The technique explicitly maximizes a criterion function based on theambiguity and inconsistency of classification. The 2-D shapes are represented by their polygonal approximation. For each of the objects participating in the occlusion, there is a hierarchical process. These processes are executed in parallel and are coordinated in such a way that the same segment of the apparent object, formed as a result of occlusion of two or more actual objects, is not matched to the segments of different actual objects. Results are presented when two or three objects partially occlude.