A global sparse stereo matching method under structure tensor constraint

  • Ying Mu*
  • , Hong Zhang
  • , Junwei Li
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a global algorithm based on graph cuts theory is proposed to solve the sparse stereo matching problem. The sparse feature points are extracted by the Harris corner detector. The matching problem is transformed into a labeling problem in the sparse graph which can be solved by energy minimization. In this algorithm, the graph is constructed by sparse feature points instead of pixels, which can lead to simple graph structure. In addition, a structure tensor descriptor, which is invariant to varying illumination, is used as similarity measurement to obtain more accurate result. The experimental results show that this algorithm can obtain accurate matching result.

Original languageEnglish
Title of host publicationProceedings - 2009 International Conference on Information Technology and Computer Science, ITCS 2009
Pages609-612
Number of pages4
DOIs
StatePublished - 2009
Event2009 International Conference on Information Technology and Computer Science, ITCS 2009 - Kiev, Ukraine
Duration: 25 Jul 200926 Jul 2009

Publication series

NameProceedings - 2009 International Conference on Information Technology and Computer Science, ITCS 2009
Volume1

Conference

Conference2009 International Conference on Information Technology and Computer Science, ITCS 2009
Country/TerritoryUkraine
CityKiev
Period25/07/0926/07/09

Keywords

  • Feature point extraction
  • Graph cuts theory
  • Sparse point matching
  • Stereo correspondence

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