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Inverse Reflectometry for Spatial Materials under General illumination

Li Shen, Proc. Meeting on Image Recognition and Understanding (MIRU), pp. 1000-1005, Jul. 2006.

Abstract

Studies on inverse rendering have shown that the bidirectional reflection distribution functions (BRDFs) of object surface can be estimated from images. Under general illumination, recovery of spatially varying BRDFs generally requires very costly processes and dense images. In this paper, we present a method to recover spatial reflectance from a sparse set of images under general illumination. We assume object surfaces are composed of a number of different materials, and may have complex textures. Specifically, we first remove the high-frequency varying diffuse reflection term by using a low-order spherical harmonic approximation. Then, an efficient clustering process is applied to estimate the specular reflectance of the multiple materials with the specular reflection components. With the specular reflectance obtained, the diffuse reflectance is estimated at each point. As a result, we can reconstruct a truly spatially varying BRDF model of the surface from a sparse set of images. Experimental results will be presented to demonstrate the effectiveness of the proposed algorithm. (pdf file)

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