Photometric stereo with non-Lambertian preprocessing and Hayakawa lighting estimation for highly detailed shape reconstruction

In many realistic scenarios, the use of highly detailed photometric 3D reconstruction techniques is hindered by several challenges in given imagery. Especially the light sources are often unknown and need to be estimated, and the light reflectance is often non-Lambertian. In addition, when approaching the problem to apply photometric techniques at real-world imagery, several parameters appear that need to be fixed in order to obtain high quality reconstructions. In this work, we attempt to tackle these issues by combining photometric stereo with non-Lambertian preprocessing and Hayakawa lighting estimation. At hand of a dedicated study we discuss the applicability of these techniques for their use in automated 3D geometry recovery for 3D printing.