In this paper we propose a novel method for measuring reflectance of isotropic materials efficiently by carefully choosing a set of sampling directions which yields less modeling error. The analysis is based on the empirical observation that most isotropic BRDFs can be approximated using 2D bivariate representation. Further a compact representation in the form of basis is computed for a large database of densely measured materials. Using these basis and an iterative optimization process, an appropriate set of sampling directions necessary for acquiring reflectance of new materials are selected. Finally, the measured data using selected sampling directions is projected onto the compact basis to obtain weighting factors for linearly representing new material as a combination of basis of several previously measured materials. This compact representation with an appropriate BRDF parameterization allows us to significantly reduce the time and effort required for making new reflectance measurements of any isotropic material. Experimental results obtained using few sampling directions on the MERL dataset show comparative performance to an exhaustively captured set of BRDFs.
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