DocumentCode
744857
Title
Estimation of occlusion and dense motion fields in a bidirectional Bayesian framework
Author
Lim, Keng Pang ; Das, Amitabha ; Chong, Man Nang
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
24
Issue
5
fYear
2002
fDate
5/1/2002 12:00:00 AM
Firstpage
712
Lastpage
718
Abstract
This paper presents new MRF (Markov random field) models in a bidirectional Bayesian framework for accurate motion and occlusion field estimation. With careful selection of the five free parameters required by the models, good experimental results have been obtained. The resultant computational speed is also 5.5 times faster compared with the conventional "iterated conditional mode" relaxation using the proposed fast bidirectional relaxation
Keywords
Bayes methods; Markov processes; hidden feature removal; image sequences; motion estimation; relaxation theory; Markov random field models; bidirectional Bayesian framework; computational speed; dense motion field estimation; fast bidirectional relaxation; free parameter selection; iterated conditional mode relaxation; occlusion detection; occlusion field estimation; Bayesian methods; Motion estimation;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.1000246
Filename
1000246
Link To Document