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Article: Lazy texture selection based on active learning

TitleLazy texture selection based on active learning
Authors
KeywordsGraph Cut
Scribbles
Segmentation
Supervised Classification
Texture Descriptors
Issue Date2010
PublisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00371/index.htm
Citation
Visual Computer, 2010, v. 26 n. 3, p. 157-169 How to Cite?
AbstractInteractive selection of desired textures and textured objects from a video is a challenging problem in video editing. In this paper, we present a scalable framework that accurately selects textured objects with only moderate user interaction. Our method applies the active learning methodology, and the user only needs to label minimal initial training data and subsequent query data. An active learning algorithm uses these labeled data to obtain an initial classifier and iteratively improves it until its performance becomes satisfactory. A revised graph-cut algorithm based on the trained classifier has also been developed to improve the spatial coherence of selected texture regions. We show that our system is responsive even with videos of a large number of frames, and it frees the user from extensive labeling work. A variety of operations, such as color editing, compositing, and texture cloning, can be then applied to the selected textures to achieve interesting editing effects. © 2009 Springer-Verlag.
Persistent Identifierhttp://hdl.handle.net/10722/152428
ISSN
2015 Impact Factor: 1.06
2015 SCImago Journal Rankings: 0.560
ISI Accession Number ID
Funding AgencyGrant Number
National Natural Science Foundation of China60728204/F020404
Funding Information:

Four dynamic textures used in this paper, FLOWER, SEA PLANT, SMOKE, and BUBBLES, are from the DynTex database at Center for Mathematics and Computer Science (CWI), The Netherlands. This work was partially supported by National Natural Science Foundation of China (60728204/F020404).

References

 

DC FieldValueLanguage
dc.contributor.authorXia, Ten_US
dc.contributor.authorWu, Qen_US
dc.contributor.authorChen, Cen_US
dc.contributor.authorYu, Yen_US
dc.date.accessioned2012-06-26T06:38:57Z-
dc.date.available2012-06-26T06:38:57Z-
dc.date.issued2010en_US
dc.identifier.citationVisual Computer, 2010, v. 26 n. 3, p. 157-169en_US
dc.identifier.issn0178-2789en_US
dc.identifier.urihttp://hdl.handle.net/10722/152428-
dc.description.abstractInteractive selection of desired textures and textured objects from a video is a challenging problem in video editing. In this paper, we present a scalable framework that accurately selects textured objects with only moderate user interaction. Our method applies the active learning methodology, and the user only needs to label minimal initial training data and subsequent query data. An active learning algorithm uses these labeled data to obtain an initial classifier and iteratively improves it until its performance becomes satisfactory. A revised graph-cut algorithm based on the trained classifier has also been developed to improve the spatial coherence of selected texture regions. We show that our system is responsive even with videos of a large number of frames, and it frees the user from extensive labeling work. A variety of operations, such as color editing, compositing, and texture cloning, can be then applied to the selected textures to achieve interesting editing effects. © 2009 Springer-Verlag.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00371/index.htmen_US
dc.relation.ispartofVisual Computeren_US
dc.subjectGraph Cuten_US
dc.subjectScribblesen_US
dc.subjectSegmentationen_US
dc.subjectSupervised Classificationen_US
dc.subjectTexture Descriptorsen_US
dc.titleLazy texture selection based on active learningen_US
dc.typeArticleen_US
dc.identifier.emailYu, Y:yzyu@cs.hku.hken_US
dc.identifier.authorityYu, Y=rp01415en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s00371-009-0359-8en_US
dc.identifier.scopuseid_2-s2.0-77949275260en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77949275260&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume26en_US
dc.identifier.issue3en_US
dc.identifier.spage157en_US
dc.identifier.epage169en_US
dc.identifier.isiWOS:000274719200001-
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridXia, T=35876042700en_US
dc.identifier.scopusauthoridWu, Q=51964899100en_US
dc.identifier.scopusauthoridChen, C=9333688600en_US
dc.identifier.scopusauthoridYu, Y=8554163500en_US
dc.identifier.citeulike4364796-

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