Surfaces in the real world exhibit complex appearance due to spatial variations in both their reflectance and local shading frames (i.e. the local coordinate system defined by the normal and tangent direction). For opaque surfaces, existing fabrication solutions can reproduce well only the spatial variations of isotropic reflectance. In this paper, we present a system for fabricating surfaces with desired spatially-varying reflectance, including anisotropic ones, and local shading frames. We approximate each input reflectance, rotated by its local frame, as a small patch of oriented facets coated with isotropic glossy inks. By assigning different ink combinations to facets with different orientations, this bi-scale material can reproduce a wider variety of reflectance than the printer gamut, including anisotropic materials. By orienting the facets appropriately, we control the local shading frame. We propose an algorithm to automatically determine the optimal facets orientations and ink combinations that best approximate a given input appearance, while obeying manufacturing constraints on both geometry and ink gamut. We fabricate the resulting surface with commercially available hardware, a 3D printer to fabricate the facets and a flatbed UV printer to coat them with inks. We validate our method by fabricating a variety of isotropic and anisotropic materials with rich variations in normals and tangents.

Abstract We present a technique for rapid capture of high quality bidirectional reflection distribution functions(BRDFs) of surface points. Our method represents the BRDF at each point by a generalized microfacet model with tabulated normal distribution function (NDF) and assumes that the BRDF is symmetrical. A compact and light‐weight reflectometry apparatus is developed for capturing reflectance data from each surface point within one second. The device consists of a pair of condenser lenses, a video camera, and six LED light sources. During capture, the reflected rays from a surface point lit by a LED lighting are refracted by a condenser lenses and efficiently collected by the camera CCD. Taking advantage of BRDF symmetry, our reflectometry apparatus provides an efficient optical design to improve the measurement quality. We also propose a model fitting algorithm for reconstructing the generalized microfacet model from the sparse BRDF slices captured from a material surface point. Our new algorithm addresses the measurement errors and generates more accurate results than previous work. Our technique provides a practical and efficient solution for BRDF acquisition, especially for materials with anisotropic reflectance. We test the accuracy of our approach by comparing our results with ground truth. We demonstrate the efficiency of our reflectometry by measuring materials with different degrees of specularity, values of Fresnel factor, and angular variation.

Manifold bootstrapping is a new method for data-driven modeling of real-world, spatially-varying reflectance, based on the idea that reflectance over a given material sample forms a low-dimensional manifold. It provides a high-resolution result in both the spatial and angular domains by decomposing reflectance measurement into two lower-dimensional phases. The first acquires representatives of high angular dimension but sampled sparsely over the surface, while the second acquires keys of low angular dimension but sampled densely over the surface. We develop a hand-held, high-speed BRDF capturing device for phase one measurements. A condenser-based optical setup collects a dense hemisphere of rays emanating from a single point on the target sample as it is manually scanned over it, yielding 10 BRDF point measurements per second. Lighting directions from 6 LEDs are applied at each measurement; these are amplified to a full 4D BRDF using the general (NDF-tabulated) microfacet model. The second phase captures N =20-200 images of the entire sample from a fixed view and lit by a varying area source. We show that the resulting N -dimensional keys capture much of the distance information in the original BRDF space, so that they effectively discriminate among representatives, though they lack sufficient angular detail to reconstruct the SVBRDF by themselves. At each surface position, a local linear combination of a small number of neighboring representatives is computed to match each key, yielding a high-resolution SVBRDF. A quick capture session (10-20 minutes) on simple devices yields results showing sharp and anisotropic specularity and rich spatial detail.