NDLI: Pocket reflectometry

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Pocket reflectometry

Content Provider	ACM Digital Library
Author	Ren, Peiran Tong, Xin Snyder, John Wang, Jiaping Guo, Baining
Abstract	We present a simple, fast solution for reflectance acquisition using tools that fit into a pocket. Our method captures video of a flat target surface from a fixed video camera lit by a hand-held, moving, linear light source. After processing, we obtain an SVBRDF. We introduce a BRDF chart, analogous to a color "checker" chart, which arranges a set of known-BRDF reference tiles over a small card. A sequence of light responses from the chart tiles as well as from points on the target is captured and matched to reconstruct the target's appearance. We develop a new algorithm for BRDF reconstruction which works directly on these LDR responses, without knowing the light or camera position, or acquiring HDR lighting. It compensates for spatial variation caused by the local (finite distance) camera and light position by warping responses over time to align them to a specular reference. After alignment, we find an optimal linear combination of the Lambertian and purely specular reference responses to match each target point's response. The same weights are then applied to the corresponding (known) reference BRDFs to reconstruct the target point's BRDF. We extend the basic algorithm to also recover varying surface normals by adding two spherical caps for diffuse and specular references to the BRDF chart. We demonstrate convincing results obtained after less than 30 seconds of data capture, using commercial mobile phone cameras in a casual environment.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF MP4
ISBN	9781450309431
DOI	10.1145/1964921.1964940
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-08-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Dynamic time warping (dtw) Reflectance sequence/response Spatially varying brdf (svbrdf) Brdf chart Local linear embedding
Content Type	Audio Text
Resource Type	Article

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