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dc.contributor.advisorTomas Lozano-Perez
dc.contributor.authorLozano-Perez, Tomasen_US
dc.contributor.authorKaelbling, Leslie Packen_US
dc.contributor.authorChiu, Han-Pangen_US
dc.contributor.otherLearning and Intelligent Systemsen_US
dc.date.accessioned2009-02-19T19:15:05Z
dc.date.available2009-02-19T19:15:05Z
dc.date.issued2009-02-18
dc.identifier.urihttp://hdl.handle.net/1721.1/44615
dc.description.abstractOur goal is to automatically reconstruct 3D objects from a single image, by using prior 3D shape models of classes. The shape models, defined as a collection of oriented primitive shapes centered at fixed 3D positions, can be learned from a few labeled images for each class. The 3D class model can then be used to estimate the 3D shape of an object instance, including occluded parts, from a single image. We provide a quantitative evaluation of the shape estimation process on real objects and demonstrate its usefulness in three applications: robot manipulation, object detection, and generating 3D 'pop-up' models from photos.en_US
dc.format.extent9 p.en_US
dc.relation.ispartofseriesMIT-CSAIL-TR-2009-008
dc.titleAutomatic Class-Specific 3D Reconstruction from a Single Imageen_US


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