Using line consistency to estimate 3D indoor Manhattan scene layout from a single image

Hsing Chun Chang, Szu-Hao Huang, Shang Hong Lai

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

4 Scopus citations

Abstract

In this paper, an optimization approach is proposed to estimate the 3D indoor Manhattan scene layout from a single input image. The proposed system models the interior space as a three-dimensional box which includes ceiling, floor, and walls. The regions corresponding to different surfaces can be calculated by projecting the 3D box onto the two-dimensional image with suitable camera and box parameters. This paper also utilizes the consistency of coplanar lines and the boundary edges between different surfaces to design a cost function. The rotation, translation, and box parameters of the interior layout can be estimated with an energy minimization process. In the experimental results, we apply the proposed algorithm to a number of real images of interior scenes to demonstrate the effectiveness of the proposed system.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherIEEE Computer Society
Pages4723-4727
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - 9 Dec 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 27 Sep 201530 Sep 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing, ICIP 2015
CountryCanada
CityQuebec City
Period27/09/1530/09/15

Keywords

  • 3D Manhattan scene
  • interior layout estimation
  • line consistency
  • optimization

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  • Cite this

    Chang, H. C., Huang, S-H., & Lai, S. H. (2015). Using line consistency to estimate 3D indoor Manhattan scene layout from a single image. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings (pp. 4723-4727). [7351703] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December). IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7351703