A novel fast full frame video stabilization via three-layer model

Long, W; Yang, J; Song, D; Chen, X; He, X

A novel fast full frame video stabilization via three-layer model

Long, W Yang, J Song, D Chen, X He, X

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 8935 pp. 246 - 256
Issue Date:: 2015-01-01

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Field	Value	Language
dc.contributor.author	Long, W	en_US
dc.contributor.author	Yang, J	en_US
dc.contributor.author	Song, D	en_US
dc.contributor.author	Chen, X	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 8935 pp. 246 - 256	en_US
dc.identifier.isbn	9783319144443	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41822
dc.description.abstract	© Springer International Publishing Switzerland 2015. Video stabilization is an important video enhancement technology which aims at removing undesired shaking from input videos. A challenging task in stabilization is to inpaint the missing pixels of undefined areas in the motion-compensated frames. This paper describes a new video stabilization method. It adopts a multi-layer model to improve the efficiency of the video stabilization. The undefined areas can be inpainted in real-time. Compared with traditional methods, our proposed algorithm only need maintain a single updated mosaic image for video completion, while previous methods require to store all neighboring frames and then registered with the current frame. The experimental results demonstrated the effectiveness of the proposed approach.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A novel fast full frame video stabilization via three-layer model	en_US
dc.type	Conference Proceeding
utslib.citation.volume	8935	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	080106 Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	8935	en_US

Abstract:

© Springer International Publishing Switzerland 2015. Video stabilization is an important video enhancement technology which aims at removing undesired shaking from input videos. A challenging task in stabilization is to inpaint the missing pixels of undefined areas in the motion-compensated frames. This paper describes a new video stabilization method. It adopts a multi-layer model to improve the efficiency of the video stabilization. The undefined areas can be inpainted in real-time. Compared with traditional methods, our proposed algorithm only need maintain a single updated mosaic image for video completion, while previous methods require to store all neighboring frames and then registered with the current frame. The experimental results demonstrated the effectiveness of the proposed approach.

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http://hdl.handle.net/10453/41822