Discovering texture regularity as a higher-order correspondence problem

James Hays, Marius Leordeanu, Alexei A. Efros, Yanxi Liu

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

94 Scopus citations

Abstract

Understanding texture regularity in real images is a challenging computer vision task. We propose a higher-order feature matching algorithm to discover the lattices of near-regular textures in real images. The underlying lattice of a near-regular texture identifies all of the texels as well as the global topology among the texels. A key contribution of this paper is to formulate lattice-finding as a correspondence problem. The algorithm finds a plausible lattice by iteratively proposing texels and assigning neighbors between the texels. Our matching algorithm seeks assignments that maximize both pair-wise visual similarity and higher-order geometric consistency. We approximate the optimal assignment using a recently developed spectral method. We successfully discover the lattices of a diverse set of unsegmented, real-world textures with significant geometric warping and large appearance variation among texels.

Original languageEnglish (US)
Title of host publicationComputer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings
Pages522-535
Number of pages14
DOIs
StatePublished - 2006
Event9th European Conference on Computer Vision, ECCV 2006 - Graz, Austria
Duration: May 7 2006May 13 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3952 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th European Conference on Computer Vision, ECCV 2006
CountryAustria
CityGraz
Period5/7/065/13/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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