This paper presents a high-accuracy 3D (three-dimen-sional) measurement system using multi-camera passive stereo vision to reconstruct 3D surfaces of free form objects. The proposed system is based on an efficient stereo correspondence technique, which consists of (i) coarse-to-fine correspondence search, and (ii) outlier detection and correction, both employing phase-based image matching. The proposed sub-pixel correspondence search technique contributes to dense reconstruction of arbitrary-shaped 3D surfaces with high accuracy. The outlier detection and correction technique contributes to high reliability of reconstructed 3D points. Through a set of experiments, we show that the proposed system measures 3D surfaces of objects with sub-mm accuracy. Also, we demonstrate high-quality dense 3D reconstruction of a human face as a typical example of free form objects. The result suggests a potential possibility of our approach to be used in many computer vision applications.

This paper presents a technique for high-accuracy correspondence search between two images using Phase-Only Correlation (POC) and its performance evaluation in a 3D measurement application. The proposed technique employs (i) a coarse-to-fine strategy using image pyramids for correspondence search and (ii) a sub-pixel window alignment technique for finding a pair of corresponding points with sub-pixel displacement accuracy. Experimental evaluation shows that the proposed method makes possible to estimate the displacement between corresponding points with approximately 0.05-pixel accuracy when using 1111-pixel matching windows. This paper also describes an application of the proposed technique to passive 3D measurement system.