Ph. D. Dissertation Dense Estimation of Surface Reflectance Properties Based on Inverse Rendering

In computer graphics (CG), making photorealistic images using a computer is now commonplace. As a result, directors can create convincing, imaginary worlds, and designers can virtually prototype, visualize, and evaluate potential products and spaces. In order to achieve these purposes, rendering methods such as ray tracing and radiosity rendering methods have been developed. However, the rendering of more photorealistic images requires both accurate object surface reflectance parameters and object surface geometries to be obtained. Therefore, in augmented virtuality, it is important to estimate surface reflectometry and surface geometry from real objects or scenes. In particular, object surface reflectometry estimation is of primary importance because, unlike object surface geometry, which can be measured using a range finder, no device has been developed to measure the variation of object surface reflectance properties. The present study investigates the problem of object surface reflectance estimation, which is sometimes referred to as inverse reflectometry, for photorealistic rendering and effective multimedia applications. A number of methods have been developed for estimating object surface reflectance properties in order to render real objects under arbitrary illumination conditions. However, it is difficult to densely estimate surface reflectance properties faithfully for complex objects with interreflections. This thesis describes three new methods for densely estimating the non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces. Specifically, we use registered range and surface color texture images obtained by a laser rangefinder. The proposed methods determine the positions of light sources in order to capture color Ph. D. Dissertation, Department of Information Systems, Graduate School of Information Science, Nara Institute of Science and Technology, March 17, 2005.