Document Detail

Occlusion-Aware Motion Layer Extraction Under Large Inter-Frame Motions.
MedLine Citation:
PMID:  21421444     Owner:  NLM     Status:  Publisher    
Extracting motion layers from videos is an important task for video representation, analysis and compression. For videos with large inter-frame motions, motion layer extraction is challenging in two respects: the estimation of large disparity motions, and the awareness of large occluded regions. In this paper, we propose an effective method for motion layer extraction under large disparity motions. To robustly estimate large displacement motions, we have developed an efficient voting-based method which estimates planar homographies from sparse feature matches. To handle occlusions, we first integrate color and motion consistency into a Markov random field framework to achieve per-pixel assignment with occlusion detection. Then, we perform motion-color segmentation and an earth movers distance-based comparison to determine motion labels for occluded pixels. Experimental results show that our proposed method achieves good performance in automatically extracting multiple moving objects under large disparity motions while maintaining a low computational cost.
F Xu; Q Dai
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-3-17
Journal Detail:
Title:  IEEE transactions on image processing : a publication of the IEEE Signal Processing Society     Volume:  -     ISSN:  1941-0042     ISO Abbreviation:  -     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-3-22     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9886191     Medline TA:  IEEE Trans Image Process     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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