利用离散目标模型的三维磁共振成像从立体视觉数据中重建表面

18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI:10.1109/ICPR.2006.1097

H. Takizawa, Shinji Yamamoto

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引用次数: 1

摘要

本文提出了一种利用立体视觉数据重建物体表面的方法。在三维马尔可夫随机场(MRF)模型框架中定义了立体数据与曲面的适合度和曲面之间的相互关系。通过寻找磁流变函数模型的最可能状态来完成表面重建。给出了一个实际场景的实验结果

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

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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18th International Conference on Pattern Recognition (ICPR'06)

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