: Examples of interpolation between two anisotropic sampled BRDFs (a,b). Naive linear interpolation generates an unrealistic double highlight (c). Working with a flattened BRDF representation in a Euclidean space produces large conspicuous errors (d). Since we used a parametric BRDF model, we can compute the ground-truth in-between BRDF by interpolating the parameters (e). Our approach has no knowledge of the parametric BRDF representation but is nonetheless able to produce a similar output (f). Interpolation between pairs of values, typically vectors, is a fundamental operation in many computer graphics applications. In some cases simple linear interpolation yields meaningful results without requiring domain knowledge. However, interpolation between pairs of distributions or pairs of functions often demands more care because features may exhibit translational motion between exemplars. This property is not captured by linear interpolation. This paper develops the use of displacement interpolation for this class of problem, which provides a generic method for interpolating between distributions or functions based on advection instead of blending. The functions can be non-uniformly sampled, high-dimensional, and defined on non-Euclidean manifolds, e.g., spheres and tori. Our method decomposes distributions or functions into sums of radial basis functions (RBFs). We solve a mass transport problem to pair the RBFs and apply partial transport to obtain the interpolated function. We describe practical methods for computing the RBF decomposition and solving the transport problem. We demonstrate the interpolation approach on synthetic examples, BRDFs, color distributions, environment maps, stipple patterns, and value functions.
Another option is displacement interpolation REF based on solving the generalized masstransport optimization problem.
Displacement interpolation using Lagrangian mass transport
SA '11
Computer Science