Photo-realistic Rendering of Metallic Car Paint from Image-Based Measurements

Abstract

State-of-the-art car paint shows not only interesting and subtle angular dependency but also significant spatial variation. Especially in sunlight these variations remain visible even for distances up to a few meters and give the coating a strong impression of depth which cannot be reproduced by a single BRDF model and the kind of procedural noise textures typically used. Instead of explicitly modeling the responsible effect particles we propose to use image-based reflectance measurements of real paint samples and represent their spatial varying part by Bidirectional Texture Functions (BTF). We use classical BRDF models like Cook-Torrance to represent the reflection behavior of the base paint and the highly specular finish and demonstrate how the parameters of these models can be derived from the BTF measurements. For rendering, the image-based spatially varying part is compressed and efficiently synthesized. This paper introduces the first hybrid analytical and image-based representation for car paint and enables the photo-realistic rendering of all significant effects of highly complex coatings.