DocumentCode
2458435
Title
MRF Optimization via Dual Decomposition: Message-Passing Revisited
Author
Komodakis, Nikos ; Paragios, Nikos ; Tziritas, Georgios
Author_Institution
Ecole Centrale Paris, Paris
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
Abstract
A new message-passing scheme for MRF optimization is proposed in this paper. This scheme inherits better theoretical properties than all other state-of-the-art message passing methods and in practice performs equally well/outperforms them. It is based on the very powerful technique of Dual Decomposition [1] and leads to an elegant and general framework for understanding/designing message-passing algorithms that can provide new insights into existing techniques. Promising experimental results and comparisons with the state of the art demonstrate the extreme theoretical and practical potentials of our approach.
Keywords
computer vision; message passing; nonlinear programming; MRF optimization; computer vision; dual decomposition; message passing scheme; Algorithm design and analysis; Belief propagation; Computer vision; Integer linear programming; Message passing; Optimization methods; Tree graphs;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4408890
Filename
4408890
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