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

Author

Takizawa, Hotaka ; Yamamoto, Shinji

Author_Institution

Tsukuba Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

27

Lastpage

30

Abstract

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

Keywords

Markov processes; computer vision; edge detection; image matching; image reconstruction; object recognition; stereo image processing; 3D Markov random field model; discrete object models; object surface reconstruction; stereovision data; Cameras; Computer vision; Image reconstruction; Layout; Markov random fields; Object recognition; Pattern recognition; Solid modeling; Stereo vision; Surface reconstruction; 3-D; 3-D discrete object models; Fitness; Interrelation; Markov random field model; Stereo vision; Surface reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.1097

Filename

1698825