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dc.contributor.authorKo, Cheng-Hungen_US
dc.contributor.authorTsai, Yu-Paoen_US
dc.contributor.authorShih, Zen-Chungen_US
dc.contributor.authorHung, Yi-Pingen_US
dc.date.accessioned2017-04-21T06:48:31Z-
dc.date.available2017-04-21T06:48:31Z-
dc.date.issued2006en_US
dc.identifier.isbn0-7695-2521-0en_US
dc.identifier.issn1051-4651en_US
dc.identifier.urihttp://hdl.handle.net/11536/135181-
dc.description.abstractThis paper proposes a new object movie (OM) segmentation method that incorporates shape priors into the segmentation algorithm. ne shape prior introduced into every image of the OM is learned from the 3D model reconstructed by the volumetric graph cuts. Here, the constraint derived from the discrete medial axis is used to improve the reconstruction algorithm. Our segmentation method requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the OM after the initial segmentation process. Compared to other techniques, our method provides not only the better segmentation result but also the better 3D reconstruction result.en_US
dc.language.isoen_USen_US
dc.titleA new image segmentation method for removing background of object movies by learning shape priorsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1, PROCEEDINGSen_US
dc.citation.spage323en_US
dc.citation.epage+en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000240678200080en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper