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
fDate :
5/1/2002 12:00:00 AM
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;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
