We show how to overcome the single weakness of an existing fully automatic system for acquisition of spatially varying optical material behavior of real object surfaces. While the expression of spatially varying material behavior with spherical dependence on incoming light as a 4D texture (an ABTF material model) allows flexible mapping onto arbitrary 3D geometry, with photo-realistic rendering and interaction in real time, this very method of texture-like representation exposes it to common problems of texturing, striking in two disadvantages. Firstly, non-seamless textures create visible artifacts at boundaries. Secondly, even a perfectly seamless texture causes repetition artifacts due to their organised placement in large numbers over a 3D surface. We have solved both problems through our novel texture synthesis method that generates a set of seamless texture variations randomly distributed over the surface at shading time. When compared to regular 2D textures, the inter-dimensional coherence of the 4D ABTF material model poses entirely new challenges to texture synthesis, which includes maintaining the consistency of material behavior throughout the 4D space spanned by the spatial image domain and the angular illumination hemisphere. In addition, we tackle the increased memory consumption caused by the numerous variations through a fitting scheme specifically designed to reconstruct the most prominent effects captured in the material model.
ASJC Scopus subject areas
- !!Computer Vision and Pattern Recognition
- !!Computer Graphics and Computer-Aided Design
- Artificial intelligence
Fields of Expertise
- Information, Communication & Computing