Phase-Based Window Matching with Geometric Correction for Multi-View Stereo

Shuji SAKAI  Koichi ITO  Takafumi AOKI  Takafumi WATANABE  Hiroki UNTEN  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.10   pp.1818-1828
Publication Date: 2015/10/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7409
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword: 
multi-view stereo,  window matching,  geometric correction,  phase-only correlation,  

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Summary: 
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.