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Journal article

Minimal BRDF Sampling for Two-Shot Near-Field Reflectance Acquisition

From

University of California at San Diego1

Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3

We develop a method to acquire the BRDF of a homogeneous flat sample from only two images, taken by a near-field perspective camera, and lit by a directional light source. Our method uses the MERL BRDF database to determine the optimal set of lightview pairs for data-driven reflectance acquisition. We develop a mathematical framework to estimate error from a given set of measurements, including the use of multiple measurements in an image simultaneously, as needed for acquisition from near-field setups.

The novel error metric is essential in the near-field case, where we show that using the condition-number alone performs poorly. We demonstrate practical near-field acquisition of BRDFs from only one or two input images. Our framework generalizes to configurations like a fixed camera setup, where we also develop a simple extension to spatially-varying BRDFs by clustering the materials.

Language: English
Publisher: ACM
Year: 2016
Pages: 1-12
ISSN: 15577368 and 07300301
Types: Journal article
DOI: 10.1145/2980179.2982396

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