Single-image RGB Photometric Stereo With Spatially-varying Albedo
This addresses the challenge of 3D reconstruction from single images for objects with non-uniform albedo, which is incremental as it builds on existing photometric stereo methods.
The paper tackles the problem of recovering surface geometry from a single RGB image under varying albedo by assuming piece-wise constant albedo and using a calibrated photometric stereo setup, demonstrating efficacy through experiments on synthetic and real images.
We present a single-shot system to recover surface geometry of objects with spatially-varying albedos, from images captured under a calibrated RGB photometric stereo setup---with three light directions multiplexed across different color channels in the observed RGB image. Since the problem is ill-posed point-wise, we assume that the albedo map can be modeled as piece-wise constant with a restricted number of distinct albedo values. We show that under ideal conditions, the shape of a non-degenerate local constant albedo surface patch can theoretically be recovered exactly. Moreover, we present a practical and efficient algorithm that uses this model to robustly recover shape from real images. Our method first reasons about shape locally in a dense set of patches in the observed image, producing shape distributions for every patch. These local distributions are then combined to produce a single consistent surface normal map. We demonstrate the efficacy of the approach through experiments on both synthetic renderings as well as real captured images.