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Surface Reconstruction from Stereovision Data Using a 3-D MRF of Discrete Object Models
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.109718th International Conference on Patt ...
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Hotaka Takizawa, University of Tsukuba, Japan
Shinji Yamamoto, Chukyo University, Japan
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 (3-D) 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.
Index Terms:
Stereo vision, Surface reconstruction, 3-D Markov random field model, 3-D discrete object models, Fitness, Interrelation
Citation:
Hotaka Takizawa, Shinji Yamamoto, "Surface Reconstruction from Stereovision Data Using a 3-D MRF of Discrete Object Models," icpr, vol. 1, pp.27-30, 18th International Conference on Pattern Recognition (ICPR'06) Volume 1, 2006
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