An efficient image matching method for multi-view stereo

Shuji Sakai, Koichi Ito, Takafumi Aoki, Tomohito Masuda, Hiroki Unten

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

6 Citations (Scopus)


Most existing Multi-View Stereo (MVS) algorithms employ the image matching method using Normalized Cross-Correlation (NCC) to estimate the depth of an object. The accuracy of the estimated depth depends on the step size of the depth in NCC-based window matching. The step size of the depth must be small for accurate 3D reconstruction, while the small step significantly increases computational cost. To improve the accuracy of depth estimation and reduce the computational cost, this paper proposes an efficient image matching method for MVS. The proposed method is based on Phase-Only Correlation (POC), which is a high-accuracy image matching technique using the phase components in Fourier transforms. The advantages of using POC are (i) the correlation function is obtained only by one window matching and (ii) the accurate sub-pixel displacement between two matching windows can be estimated by fitting the analytical correlation peak model of the POC function. Thus, using POC-based window matching for MVS makes it possible to estimate depth accurately from the correlation function obtained only by one window matching. Through a set of experiments using the public MVS datasets, we demonstrate that the proposed method performs better in terms of accuracy and computational cost than the conventional method.

Original languageEnglish
Title of host publicationComputer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
Number of pages14
EditionPART 4
Publication statusPublished - 2013
Event11th Asian Conference on Computer Vision, ACCV 2012 - Daejeon, Korea, Republic of
Duration: 2012 Nov 52012 Nov 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume7727 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th Asian Conference on Computer Vision, ACCV 2012
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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