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
Link To Document :
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