Adaptive Sampling and Upsampling of Reflectance Fields

 

Martin Fuchs, MPI Informatik
Volker Blanz, Siegen University
Hans-Peter Seidel, MPI Informatik
Hendrik P. A. Lensch, MPI Informatik

 

Abstract

Captured reflectance fields tend to provide a relatively coarse sampling of the incident light directions. As a result, sharp illumination features, such as highlights or shadow boundaries, are poorly reconstructed during relighting; highlights are disconnected, and shadows show banding artefacts. In this paper, we propose a novel interpolation technique for 4D reflectance fields that reconstructs plausible images even for non-observed light directions. Given a sparsely sampled reflectance field, we can effectively synthesize images as they would have been obtained from denser sampling. The processing pipeline consists of three steps: (1) segmentation of regions where intermediate lighting cannot be obtained by blending, (2) appropriate flow algorithms for highlights and shadows, plus (3) a final reconstruction technique that uses image-based priors to faithfully correct errors that might be introduced by the segmentation or flow step. The algorithm reliably reproduces scenes that contain specular highlights, interreflections, shadows or caustics.

 

(a)

(b)

(a) Our acquisition setup allows for capturing reflectance samples for arbitrary incident light directions and varying light source extent. We can perform pre-filtering and adaptive sampling. (b) By performing non-linear interpolation of high lights, caustics and shadows we can hierarchically synthesize images for for arbitrary light source directions (red dots) even from a sparse input (black triangulation).

(a)

(b)

(c)

(a) Linear interpolation of reflectance samples lead to an artificial segmentation of the highlight region. (b) Our non-linear interpolation generates a smooth highlight from the same input data with about 230 directions. The result comes close to the ground truth captured for about 10000 direction.

 

Movies:

(a) linear interpolation

(b) non-linear interpolation

(c) linear interpolation

(d) non-linear interpolation

 

Publications:

Martin Fuchs, Volker Blanz, Hendrik P. A. Lensch, and Hans-Peter Seidel.
Reflectance from Images: A Model-Based Approach for Human Faces
. IEEE Transactions on Visualization and Computer Graphics, 11(3), 2005, pages 296-305.

Martin Fuchs, Hendrik P. A. Lensch, Volker Blanz, and Hans-Peter Seidel.
Superresolution Reflectance Fields: Synthesizing images for intermediate light directions. In Proceedings EUROGRAPHICS 2007, pages 447-456.