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dc.contributor.authorHuang, Qixing
dc.contributor.authorKoltun, Vladlen
dc.contributor.authorGuibas, Leonidas
dc.date.accessioned2016-02-25T13:34:23Z
dc.date.available2016-02-25T13:34:23Z
dc.date.issued2011
dc.identifier.citationHuang Q, Koltun V, Guibas L (2011) Joint shape segmentation with linear programming. Proceedings of the 2011 SIGGRAPH Asia Conference on - SA ’11. Available: http://dx.doi.org/10.1145/2024156.2024159.
dc.identifier.doi10.1145/2024156.2024159
dc.identifier.doi10.1145/2070781.2024159
dc.identifier.urihttp://hdl.handle.net/10754/598683
dc.description.abstractWe present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.
dc.description.sponsorshipWe are grateful to Mirela Ben-Chen, Siddhartha Chaudhuri, and Evangelos Kalogerakis for their comments on this paper. This work was supported in part by NSF grants 0808515 and 1011228, a Stanford-KAUST AEA grant, and a Stanford Graduate Fellowship.
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectLinear programming
dc.subjectShape correspondence
dc.subjectShape segmentation
dc.titleJoint shape segmentation with linear programming
dc.typeConference Paper
dc.identifier.journalProceedings of the 2011 SIGGRAPH Asia Conference on - SA '11
dc.contributor.institutionStanford University, Palo Alto, United States


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