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An MRF and Gaussian Curvature Based Shape Representation for Shape Matching

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]

CollectionsANU Research Publications
Date published: 2007
Type: Conference paper
Source: Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR 2007)
DOI: 10.1109/CVPR.2007.383359


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