Abstract
This paper proposes an algorithm for extracting the boundary of an object. In order to take full advantage of global shape, our approach uses global shape parameters derived from Point Distribution Model (PDM). Unlike PDM, the proposed method models global shape using curvature as well as edge. The objective function for applying the shape model is formulated using Bayesian rule. This method can extract a boundary of an object by evaluating the solution maximizing the objective function iteratively. Experimental results show that the proposed method requires less computational cost than the PDM and it is robust to noise, pose variation, and some occlusion.
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