Bayesian dense motion field estimation with landmark constraint

Yi Chin*, Chun-Jen Tsai

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

In this paper, a dense motion field estimation technique based on the Bayesian framework is proposed to estimate the true dense motion fields of video sequences. Previous stochastic techniques of dense motion field estimation adopts piecewise smooth motion model and use MAP estimation to find the motion field with joint minimization of motion compensation errors and maximization of motion smoothness. However, such random process does not guarantee to converge to the true motion field. In this paper, the motion of landmark points in the video sequence is introduced into the MAP estimation process to regularize the estimated motion field. Experimental results show that the proposed algorithm produces estimated motion fields which preserve piecewise smooth nature and are visually close to the true motion of the video sequences.

原文English
主出版物標題2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
頁面773-776
頁數4
DOIs
出版狀態Published - 2010
事件2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
持續時間: 26 9月 201029 9月 2010

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
ISSN(列印)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
國家/地區Hong Kong
城市Hong Kong
期間26/09/1029/09/10

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