A probabilistic approach for solving Poisson equations in computer vision problems

Author

Tian, Jie ; Tai, Juwei ; Zhang, Xinsheng

Author_Institution

Inst. of Autom., Chinese Acad. of Sci., Beijing, China

fYear

1992

fDate

30 Aug-3 Sep 1992

Firstpage

737

Lastpage

740

Abstract

Describes the probabilistic approach to solve Poisson equations and show this method may be used to solve computer vision problems. The authors also give a complexity analysis of this method and compare it method with BEM, FEM and FDM in terms of storage and time complexity. Some examples are given and show that the authors method is better than BEM, FEM and FDM in certain aspects. Finally, the authors use the probabilistic approach for solving several computer vision problems, such as shape from shading, surface interpolation and brightness based stereo vision, the experimental results show that the probabilistic approach is very effective

Keywords

boundary-elements methods; computational complexity; computer vision; finite difference methods; finite element analysis; partial differential equations; probability; BEM; FDM; FEM; Poisson equations; brightness based stereo vision; complexity analysis; computer vision; probabilistic approach; shape from shading; storage; surface interpolation; time complexity; Automation; Brightness; Computer vision; Finite difference methods; Finite element methods; Iterative methods; Poisson equations; Shape; Stereo vision; Surface reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on

Conference_Location

The Hague

Print_ISBN

0-8186-2920-7

Type

conf

DOI

10.1109/ICPR.1992.202092

Filename

202092