Shock Posture for Shape Matching

In this paper, the aim is to develop a framework to efficiently match human posture. We will use shock graphs as our shape representation. The algorithms developed are for detection of end points and junction points present in every region of the shock graph for modelling of human posture. We will propose a relatively simple posture matching system based on key point's correspondences. It will be shown that this framework is effective in matching human shape posture. The algorithms were tested with wide varieties of 2D human shapes representing a range of posture. Six key points were determined and preserved. These key points will serve as tool for matching of human postures. Initial results of the experiments are encouraging and found that our method can efficiently be applied for posture matching. Research on this promising approach is ongoing, focusing both on new applications and on techniques that will further enhance its performance.