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Tube-embodied gradient vector flow fields for unsupervised video object plane (VOP) segmentation

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dc.contributor.author Ntalianis, KS en
dc.contributor.author Doulamis, ND en
dc.contributor.author Doulamis, AD en
dc.contributor.author Kollias, SD en
dc.date.accessioned 2014-03-01T02:42:02Z
dc.date.available 2014-03-01T02:42:02Z
dc.date.issued 2001 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/30739
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-0035167231&partnerID=40&md5=fecc8df393b206d8dbc0854beb375c8e en
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-0035167231&partnerID=40&md5=fecc8df393b206d8dbc0854beb375c8e en
dc.subject.other Algorithms en
dc.subject.other Calculations en
dc.subject.other Edge detection en
dc.subject.other Feature extraction en
dc.subject.other Partial differential equations en
dc.subject.other Video signal processing en
dc.subject.other Canny edge detector en
dc.subject.other Euler equations en
dc.subject.other Gradient vector flow fields en
dc.subject.other Stereo analysis method en
dc.subject.other Video object plane segmentation en
dc.subject.other Image segmentation en
dc.title Tube-embodied gradient vector flow fields for unsupervised video object plane (VOP) segmentation en
heal.type conferenceItem en
heal.publicationDate 2001 en
heal.abstract In this paper constrained Gradient Vector Flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The edge map is used for tube estimation inside which the GVF field evolves. After generation of the GVF field an active contour is unsupervisedly initialized onto the outer bound of the tube. Finally a greedy approach is adopted and the active contour, guided by the GVF field, extracts the VOP. Experimental results on real life stereoscopic video sequences indicate the efficiency of the proposed scheme. en
heal.journalName IEEE International Conference on Image Processing en
dc.identifier.volume 2 en
dc.identifier.spage 637 en
dc.identifier.epage 640 en


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