Phase-Based Window Matching with Geometric Correction for Multi-View Stereo
Phase-Based Window Matching with Geometric Correction for Multi-View Stereo
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DOI：
10.1587/transinf.2014edp7409
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发表时间：
2015-10
期刊：
影响因子：
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通讯作者：
S. Sakai;Koichi Ito;T. Aoki;Takafumi Watanabe;Hiroki Unten
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文献类型：
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作者：
S. Sakai;Koichi Ito;T. Aoki;Takafumi Watanabe;Hiroki Unten
摘要窗口匹配估计三维点的方法是影响多视点立体(MVS)算法精度、稳健性和计算代价的最严重因素。现有的MVS算法大多采用基于归一化交叉相关(NCC)的窗口匹配算法来估计3D点的深度。基于NCC的窗口匹配通过线性/三次插值法以亚像素精度估计匹配窗口之间的位移，但不能准确表示匹配窗口的亚像素值。本文提出了一种基于仅相位相关(POC)和几何校正的MVS窗口匹配技术。通过对POC函数的解析相关峰模型进行拟合，可以估计出两个匹配窗口之间精确的亚像素位移。该方法还考虑了目标物体的三维形状，对匹配窗口的几何变换进行了校正。利用所提出的几何校正方法，即使对于大变形的图像，也可以从多视角图像中实现精确的三维重建。与传统的三维重建方法相比，该方法具有更高的重建精度
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 CrossCorrelation (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