An MRF and Gaussian Curvature Based Shape Representation for Shape Matching
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]
|Collections||ANU Research Publications|
|Source:||Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR 2007)|
|01_Xiao_An_MRF_and_Gaussian_Curvature_2007.pdf||206.1 kB||Adobe PDF||Request a copy|
|02_Xiao_An_MRF_and_Gaussian_Curvature_2007.pdf||106.41 kB||Adobe PDF||Request a copy|
|03_Xiao_An_MRF_and_Gaussian_Curvature_2007.pdf||88.02 kB||Adobe PDF||Request a copy|
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