Efficient structured parsing of facades using dynamic programming

Andrea Cohen, Alexander Gerhard Schwing, Marc Pollefeys

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

Abstract

We propose a sequential optimization technique for segmenting a rectified image of a facade into semantic categories. Our method retrieves a parsing which respects common architectural constraints and also returns a certificate for global optimality. Contrasting the suggested method, the considered facade labeling problem is typically tackled as a classification task or as grammar parsing. Both approaches are not capable of fully exploiting the regularity of the problem. Therefore, our technique very significantly improves the accuracy compared to the state-of-the-art while being an order of magnitude faster. In addition, in 85% of the test images we obtain a certificate for optimality.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Pages3206-3213
Number of pages8
ISBN (Electronic)9781479951178, 9781479951178
DOIs
StatePublished - Sep 24 2014
Externally publishedYes
Event27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014 - Columbus, United States
Duration: Jun 23 2014Jun 28 2014

Publication series

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

Other

Other27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014
Country/TerritoryUnited States
CityColumbus
Period6/23/146/28/14

Keywords

  • dynamic programming
  • facade parsing
  • structured segmentation
  • urban scene understanding

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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