Research Abstracts - 2007

Abstract

We propose a simple method to acquire and reconstruct material appearance with sparsely sampled data. Our technique renders elaborate view- and light-dependent effects and faithfully reproduces materials such as fabrics and knitwears. Our approach uses sparse measurements to reconstruct a full six-dimensional Bidirectional Texture Function (BTF). Our reconstruction only require input images from the top view to be registered, which is easy to achieve with a fixed camera setup. Bidirectional properties are acquired from a sparse set of viewing directions through image statistics and therefore precise registrations for these views are unnecessary. Our technique is based on multi-scale histograms of image pyramids. The full BTF is generated by matching the corresponding pyramid histograms to interpolated top-view images. We show that the use of multi-scale image statistics achieves a visually plausible appearance. However, our technique does not fully capture sharp specularities or the geometric aspects of parallax. Nonetheless, a large class of materials can be reproduced well with our technique, and our statistical characterization enables acquisition of such materials efficiently using a simple setup.

Acquisition setup - both the camera and the measured target are fixed, and a handheld wireless flash is used as the light source. During measurement, the user moves the flash source around to roughly cover all possible directions, and remotely triggers the camera shutter to take pictures.

Indoor scene rendered using 4 textures acquired and reconstructed with our technique.

References:

[1] 1. Addy Ngan and Frédo Durand. Statistical Acquisition of Texture Appearance. Eurographics Symposium on Rendering 2006.