Multi-view shape from shading constrained by stereo image analysis

Abstract

In this paper we present the combination of Shape from Shading and stereo vision based on a fully integrated approach. The surface gradients of two camera views of an object are employed to refine an initial disparity map subject to the constraint of integrability of the resulting surface. The gradient field of the object’s surface is computed using Photometric Stereo and analytical reflectance models with spatially varying parameters. We evaluate the proposed algorithm on three data sets including a metallic object and objects with depth discontinuities and small details. We achieve compelling results on all data sets including the cast iron where our method is less noise-sensitive than the reference 3D scanner. However, since the scanner exhibits high-frequency noise, we use its low-passed depth data as reference. The mean error of all data sets is 1 mm and below with a low-cost acquisition setup, consisting of two cameras and 18 light sources only. Furthermore, a new method to calibrate the lighting of a multi-view Photometric Stereo setup is briefly introduced.