Thinking inside the box: Using appearance models and context based on room geometry

Varsha Hedau, Derek Hoiem, David Forsyth

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

Abstract

In this paper we show that a geometric representation of an object occurring in indoor scenes, along with rich scene structure can be used to produce a detector for that object in a single image. Using perspective cues from the global scene geometry, we first develop a 3D based object detector. This detector is competitive with an image based detector built using state-of-the-art methods; however, combining the two produces a notably improved detector, because it unifies contextual and geometric information. We then use a probabilistic model that explicitly uses constraints imposed by spatial layout - the locations of walls and floor in the image - to refine the 3D object estimates. We use an existing approach to compute spatial layout [1], and use constraints such as objects are supported by floor and can not stick through the walls. The resulting detector (a) has significantly improved accuracy when compared to the state-of-the-art 2D detectors and (b) gives a 3D interpretation of the location of the object, derived from a 2D image. We evaluate the detector on beds, for which we give extensive quantitative results derived from images of real scenes.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
PublisherSpringer-Verlag
Pages224-237
Number of pages14
EditionPART 6
ISBN (Print)3642155669, 9783642155666
DOIs
StatePublished - Jan 1 2010
Event11th European Conference on Computer Vision, ECCV 2010 - Heraklion, Crete, Greece
Duration: Sep 10 2010Sep 11 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 6
Volume6316 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th European Conference on Computer Vision, ECCV 2010
CountryGreece
CityHeraklion, Crete
Period9/10/109/11/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Hedau, V., Hoiem, D., & Forsyth, D. (2010). Thinking inside the box: Using appearance models and context based on room geometry. In Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings (PART 6 ed., pp. 224-237). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6316 LNCS, No. PART 6). Springer-Verlag. https://doi.org/10.1007/978-3-642-15567-3_17