Xiao, Pengdong; Barnes, Nick; Caetano, Tiberio; Lieby, Paulette
Matching and registration of shapes is a key issue in Computer Vision, Pattern Recognition, and Medical Image Analysis. This paper presents a shape representation framework based on Gaussian curvature and Markov random fields (MRFs) for the purpose of shape matching. The method is based on a surface mesh model in ℝ3, which is projected into a two-dimensional space and there modeled as an extended boundary closed Markov random field. The surface is homeomorphic to double struk D sign2. The MRF...[Show more]
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