Polarization-based Shape Estimation of Transparent Objects for Digitizing Cultural Assets

Though there are many cultural assets which are made of glasses, most of the existing methods cannot estimate the shape of transparent objects with enough accuracy. We propose a novel method for estimating the surface shape of transparent objects by analyzing the polarization state of the light. Existing methods slightly consider the reflection, refraction, and transmission of the light occurring inside a transparent object. We employ a polarization raytracing method to compute both the path of the light and its polarization state. Our proposed iterative computation method estimates the surface shape of the transparent object by minimizing the difference between the polarization data rendered by the polarization ray-tracing method and the polarization data obtained from a real object.