Single-shot Acquisition of Cylindrical Mesostructure Normals using Diffuse Illumination

Abstract

Capturing high-quality surface normals is critical to acquire the surface geometry of mesostructures, such as hair and metal wires with high resolution. Existing image-based acquisition methods have assumed a specific type of surface reflectance. The shape-from-shading approach, a.k.a. photometric stereo, makes use of the shading information by a point light, assuming that surfaces are perfectly diffuse. The shape-from-specularity approach captures specular reflection densely, assuming that surfaces are overly smooth. These existing methods often fail, however, due to the difference between the presumed and the actual reflectance of real-world objects. Also, these existing methods require multiple images with different light vectors. In this work, we present a single-shot normal acquisition method, designed especially for cylindrical mesostructures on a near-flat geometry. We leverage diffuse illumination to eliminate the reflectance assumption. We then propose a local shape-from-intensity approach combined with local orientation detection. We conducted several experiments with synthetic and real objects. Quantitative and qualitative results validate that our method can capture surface normals of cylindrical mesostructures with high accuracy.