DocumentCode
1886794
Title
Motion Estimation via Belief Propagation
Author
Boccignone, Giuseppe ; Marcelli, Angelo ; Napoletano, Paolo ; Ferraro, Mario
Author_Institution
Univ. of Salerno, Salerno
fYear
2007
fDate
10-14 Sept. 2007
Firstpage
55
Lastpage
60
Abstract
We present a probabilistic model for motion estimation in which motion characteristics are inferred on the basis of a finite mixture of motion models. The model is graphically represented in the form of a pairwise Markov random field network upon which a Loopy belief propagation algorithm is exploited to perform inference. Experiments on different video clips are presented and discussed.
Keywords
Markov processes; belief networks; inference mechanisms; motion estimation; probability; random processes; inference mechanism; loopy belief propagation algorithm; motion estimation; pairwise Markov random field network; probabilistic model; Belief propagation; Graphical models; Inference algorithms; Layout; Markov random fields; Motion estimation; Random variables; Video sequences; Visual system; Yttrium;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on
Conference_Location
Modena
Print_ISBN
978-0-7695-2877-9
Type
conf
DOI
10.1109/ICIAP.2007.4362757
Filename
4362757
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