Completing 3D object shape from one depth image

Jason Rock, Tanmay Gupta, Justin Thorsen, Junyoung Gwak, Daeyun Shin, Derek Hoiem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Our goal is to recover a complete 3D model from a depth image of an object. Existing approaches rely on user interaction or apply to a limited class of objects, such as chairs. We aim to fully automatically reconstruct a 3D model from any category. We take an exemplar-based approach: retrieve similar objects in a database of 3D models using view-based matching and transfer the symmetries and surfaces from retrieved models. We investigate completion of 3D models in three cases: novel view (model in database); novel model (models for other objects of the same category in database); and novel category (no models from the category in database).

Original languageEnglish (US)
Title of host publicationIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
PublisherIEEE Computer Society
Pages2484-2493
Number of pages10
ISBN (Electronic)9781467369640
DOIs
StatePublished - Oct 14 2015
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States
Duration: Jun 7 2015Jun 12 2015

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume07-12-June-2015
ISSN (Print)1063-6919

Other

OtherIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
CountryUnited States
CityBoston
Period6/7/156/12/15

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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