Dense estimation of surface reflectance properties based on inverse global illumination rendering

In augmented virtuality, estimating object surface reflectance properties is important when rendering objects under arbitrary illumination conditions. However, faithfully estimating surface reflectance properties is difficult for objects having interreflections. The present paper describes a new method for densely estimating the non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces having diffuse and specular interreflections. The registered range and surface color texture images were obtained using a laser rangefinder. In the proposed method, the light positions are first determined in order to take color images, which are then used to discriminate diffuse and specular reflection components of surface reflection. Surface reflectance parameters are then estimated based on an inverse global illumination rendering. Experiments were conducted to reveal the usefulness of the proposed method.