DocumentCode :
900854
Title :
Polarization Multiplexing and Demultiplexing for Appearance-Based Modeling
Author :
Cula, Oana G. ; Dana, Kristin J. ; Pai, Dinesh K. ; Wang, Dongsheng
Author_Institution :
Johnson & Johnson, Skillman, NJ
Volume :
29
Issue :
2
fYear :
2007
Firstpage :
362
Lastpage :
367
Abstract :
Polarization has been used in numerous prior studies for separating diffuse and specular reflectance components, but in this work we show that it also can be used to separate surface reflectance contributions from individual light sources. Our approach is called polarization multiplexing and it has a significant impact in appearance modeling where the image as a function of illumination direction is needed. Multiple unknown light sources can illuminate the scene simultaneously, and the individual contributions to the overall surface reflectance are estimated. Polarization multiplexing relies on the relationship between the light source direction and the intensity modulation. Inverting this transformation enables the individual intensity contributions to be estimated. In addition to polarization multiplexing, we show that phase histograms from the intensity modulations can be used to estimate scene properties including the number of light sources
Keywords :
image processing; matrix algebra; polarisation; reflectivity; appearance-based modeling; illumination; image appearance modeling; intensity modulation; polarization demultiplexing; polarization multiplexing; surface reflectance; Demultiplexing; Intensity modulation; Layout; Light sources; Lighting; Optical modulation; Optical polarization; Reflectivity; Rough surfaces; Surface roughness; Reflectance; appearance; appearance-based modeling.; body reflectance; diffuse reflectance; multiplexing; polarization; specular reflectance; surface reflectance; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Lighting; Microscopy, Polarization; Photometry; Refractometry;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2007.39
Filename :
4042710
Link To Document :
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