2013 CVPR CVPR 2013

BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition

Abstract

In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We use this dense data as a reference for performance evaluation of the proposed BRDF sparse angular sampling and interpolation approach. The method is based on sampling of BRDF subspaces at fixed elevations by means of several adaptively-represented, uniformly distributed, perpendicular slices. Although this proposed method requires only a sparse sampling of material, the interpolation provides a very accurate reconstruction, visually and computationally comparable to densely measured reference. Due to the simple slices measurement and method's robustness it allows for a highly accurate acquisition of BRDFs. This in comparison with standard uniform angular sampling, is considerably faster yet uses far less samples.

🚀 Conference Pioneer — CVPR 2013
🌉 Interdisciplinary Bridge — Computer Science and Computer Vision and Deep Learning and Machine Learning and Mathematics & Optimization
📈 Trend Setter — Representation Learning
🧭 Keyword Pioneer — anisotropic appearance
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio