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Surface Reconstruction from Stereovision Data Using a 3-D MRF of Discrete Object Models

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2 Author(s)
Takizawa, H. ; Tsukuba Univ. ; Yamamoto, S.

In the present paper, we propose a method for reconstructing the surfaces of objects from stereovision data. Both the fitness of stereo data to surfaces and interrelation between the surfaces are defined in the framework of a three-dimensional (3D) Markov random field (MRF) model. The surface reconstruction is accomplished by searching for the most likely state of the MRF model. An experimental result is shown for a real scene

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Pattern Recognition, 2006. ICPR 2006. 18th International Conference on  (Volume:1 )

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