Surface reconstruction from stereo data using a three-dimensional Markov Random Field model

被引：2
|
作者：
Takizawa, Hotaka [1 ]
Yamamoto, Shinji
机构：
[1] Univ Tsukuba, Dept Comp Sci, Tsukuba, Ibaraki 3058573, Japan
[2] Chukyo Univ, Toyota 4700393, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2006年 / E89D卷 / 07期
关键词：
stereo vision; surface reconstruction; 3-D Markov Random Field model; fitness; interrelation;
D O I：
10.1093/ietisy/e89-d.7.2028
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the present paper, we propose a method for reconstructing the surfaces of objects from stereo 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. Three experimental results are shown for synthetic and real stereo data.
引用
收藏
页码：2028 / 2035
页数：8
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