Phase-based window matching with geometric correction for multi-view stereo

Shuji Sakaiy, Koichi Itoy, Takafumi Aoki, Takafumi Watanabe, Hiroki Unten

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Methods of window matching to estimate 3D points are the most serious factors affecting the accuracy, robustness, and computational cost of Multi-View Stereo (MVS) algorithms. Most existing MVS algorithms employ window matching based on Normalized Cross- Correlation (NCC) to estimate the depth of a 3D point. NCC-based window matching estimates the displacement between matching windows with sub-pixel accuracy by linear/cubic interpolation, which does not represent accurate sub-pixel values of matching windows. This paper proposes a technique of window matching that is very accurate using Phase-Only Correlation (POC) with geometric correction for MVS. The accurate sub-pixel displacement between two matching windows can be estimated by fitting the analytical correlation peak model of the POC function. The proposed method also corrects the geometric transformations of matching windows by taking into consideration the 3D shape of a target object. The use of the proposed geometric correction approach makes it possible to achieve accurate 3D reconstruction from multi-view images even for images with large transformations. The proposed method demonstrates more accurate 3D reconstruction from multi-view images than the conventional methods in a set of experiments.

Original languageEnglish
Pages (from-to)1818-1828
Number of pages11
JournalIEICE Transactions on Information and Systems
Issue number10
Publication statusPublished - 2015 Oct 1


  • Geometric correction
  • Multi-view stereo
  • Phase-only correlation
  • Window matching

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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