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Published in: International Journal of Computer Vision 2/2014

01-11-2014

Fast Spectral Reflectance Recovery Using DLP Projector

Authors: Shuai Han, Imari Sato, Takahiro Okabe, Yoichi Sato

Published in: International Journal of Computer Vision | Issue 2/2014

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Abstract

Spectral reflectance is an intrinsic characteristic of objects that is independent of illumination and the used imaging sensors. This direct representation of objects is useful for various computer vision tasks, such as color constancy and material discrimination. In this work, we present a novel system for spectral reflectance recovery with high temporal resolution by exploiting the unique color-forming mechanism of digital light processing (DLP) projectors. DLP projectors use color wheels, which are composed of a number of color segments and rotate quickly to produce the desired colors. Making effective use of this mechanism, we show that a DLP projector can be used as a light source with spectrally distinct illuminations when the appearance of a scene under the projector’s irradiation is captured with a high-speed camera. Based on the measurements, the spectral reflectance of scene points can be recovered using a linear approximation of the surface reflectance. Our imaging system is built from off-the-shelf devices, and is capable of taking multi-spectral measurements as fast as 100 Hz. We carefully evaluated the accuracy of our system and demonstrated its effectiveness by spectral relighting of static as well as dynamic scenes containing different objects.

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Appendix
Available only for authorised users
Footnotes
1
Conventional RGB cameras cannot capture very fast moving objects and would not be able to get images under distinct illuminations produced by the fast switching DLP projector, i.e. we would only get an image under white light.
 
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Metadata
Title
Fast Spectral Reflectance Recovery Using DLP Projector
Authors
Shuai Han
Imari Sato
Takahiro Okabe
Yoichi Sato
Publication date
01-11-2014
Publisher
Springer US
Published in
International Journal of Computer Vision / Issue 2/2014
Print ISSN: 0920-5691
Electronic ISSN: 1573-1405
DOI
https://doi.org/10.1007/s11263-013-0687-z

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