Multi-View Reconstruction using Narrow-Band Graph-Cuts and Surface Normal Optimization

This paper presents a new algorithm for reducing the minimal surface bias associated with volumetric graph cuts for 3D reconstruction from multiple calibrated images. The algorithm is based on an iterative graph-cut over narrow bands combined with an accurate surface normal estimation. At each iteration, we first optimize the normal to each surface patch in order to obtain a precise value for the photometric consistency measure. This helps in preserving narrow protrusions with high curvature which are very sensitive to the choice of normal. We then apply a volumetric graph-cut on a narrow band around the current surface estimate to determine the optimal surface inside this band. Using graph cuts on a narrow band allows us to avoid local minima inside the band while at the same time reducing the danger of taking ”shortcuts” and converging to a wrong ”global” minimum when using a wide band. Reconstruction results obtained on standard data sets clearly show the merits of the proposed algorithm.