To create a realistic image we need to characterize how light reflects off a surface.In optics terminology, the complete Bidirectional Reflectance Distribution Function is needed. At a given point on a surface the BRDF is a function of two directions, one toward the light and one toward the viewer. Any device for measuring the 4D reflectance data has to obtain measurements over the hemisphere of incident and exitant directions which can be quite tedious if done using the brute-force approach.In this thesis, we describe an efficient image-based acquisition setup that has no moving parts and can acquire reflectance data in a matter of a few minutes. We make this possible by using curved reflective surfaces that eliminate the need to move either the camera or the light source. The acquisition speedup mostly comes from the way we optically sample the BRDF data into a suitable basis. This also saves us the postprocess compression of data. We then encode the data into a compact form that is suitable for use in various rendering systems. ContentsAbstract .

Realistic descriptions of surface reflectance have long been a topic of interest in both computer vision and computer graphics research. In this paper, we describe a novel high speed approach for the acquisition of bidirectional reflectance distribution functions (BRDFs). We develop a new theory for directly measuring BRDFs in a basis representation by projecting incident light as a sequence of basis functions from a spherical zone of directions. We derive an orthonormal basis over spherical zones that is ideally suited for this task. BRDF values outside the zonal directions are extrapolated by re-projecting the zonal measurements into a spherical harmonics basis, or by fitting analytical reflection models to the data. For specular materials, we experiment with alternative basis acquisition approaches such as compressive sensing with a random subset of the higher order orthonormal zonal basis functions, as well as measuring the response to basis defined by an analytical model as a way of optically fitting the BRDF to such a representation. We verify this approach with a compact optical setup that requires no moving parts and only a small number of image measurements. Using this approach, a BRDF can be measured in just a few minutes.A. Ghosh ( ) ·