A Photometric Sampling Strategy for Reflectance Characterization and Transference

Mario Castelán


Rendering 3D models with real world reflectance properties is an open research problem with significant applications in the field of computer graphics and image understanding. In this paper, our interest lies on the characterization and transference of appearance from a source object onto a target 3D shape. To this end, a three-step strategy is proposed. In the first step, reflectance is sampled by rotating a light source in concentric circles around the source object. Singular value decomposition is then used for describing, in a pixel-wise manner, appearance features such as color, texture and specular regions. The second step introduces a Markov random field transference method based on surface normal correspondence between the source object and a synthetic sphere. The aim of this step is to generate a sphere whose appearance emulates that of the source material. In the third step, final transference of properties is performed from the surface normals of the generated sphere to the surface normals of the target 3D model. Experimental evaluation validates the suitability of the proposed strategy for transferring appearance from a variety of materials between diverse shapes.


Reflectance transference, singular value decomposition, random Markov fields.

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