A Hand Finding and Segmenting in a Partially Cluttered Scene

In this paper, we discuss a system for finding and segmenting a human hand, which is holding an object. This is a difficult computer vision problem, because of the many degrees of freedom, the flexibility, and the clutter problem of the hand. In order to find the correspondences, we have used a lateral similarity function. In the lateral excitation we have not only compare-ed different features at one point but also the features at that point and its neighbors ( e.g. Gobar feature, and skin color feature). The system is an extension of the Elastic Graph Matching (EGM) algorithm. EGM has been shown to be successful in numerous object vision tasks, its best performance being in face recognition.