Estimating the 3D layout of indoor scenes and its clutter from depth sensors

Jian Zhang, Chen Kan, Alexander Gerhard Schwing, Raquel Urtasun

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

Abstract

In this paper we propose an approach to jointly estimate the layout of rooms as well as the clutter present in the scene using RGB-D data. Towards this goal, we propose an effective model that is able to exploit both depth and appearance features, which are complementary. Furthermore, our approach is efficient as we exploit the inherent decomposition of additive potentials. We demonstrate the effectiveness of our approach on the challenging NYU v2 dataset and show that employing depth reduces the layout error by 6% and the clutter estimation by 13%.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Computer Vision, ICCV 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1273-1280
Number of pages8
ISBN (Print)9781479928392
DOIs
StatePublished - Jan 1 2013
Externally publishedYes
Event2013 14th IEEE International Conference on Computer Vision, ICCV 2013 - Sydney, NSW, Australia
Duration: Dec 1 2013Dec 8 2013

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2013 14th IEEE International Conference on Computer Vision, ICCV 2013
CountryAustralia
CitySydney, NSW
Period12/1/1312/8/13

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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