Extrapolating Large-Scale Material BTFs under Cross-Device Constraints

Abstract

In this paper, we address the problem of acquiring bidirectional texture functions (BTFs) of large-scale material samples. Our approach fuses gonioreflectometric measurements of small samples with few constraint images taken on a flatbed scanner under semi-controlled conditions. Underlying our method is a lightweight texture synthesis scheme using a local texture descriptor that combines shading and albedo across devices. Since it operates directly on SVD-compressed BTF data, our method is computationally efficient and can be implemented on a moderate memory footprint.