DocumentCode
2239926
Title
Conformal transplantation of lightness to varying resolution sensors
Author
Funt, Brian V. ; Brockington, Michael ; Tong, Frank
Author_Institution
Sch. of Comput. Sci., Simon Fraser Univ., Vancouver, BC, Canada
fYear
1993
fDate
15-17 Jun 1993
Firstpage
563
Lastpage
569
Abstract
Many standard computer vision algorithms for shape from shading, optical flow, color constancy or surface reconstruction depend upon the solution of Poisson equations. Using retinex lightness computation as an example, it is shown how these algorithms can be dramatically sped up using a varying resolution sensor, so long as the sensor architecture is based on a conformal mapping. The varying resolution lightness algorithm is developed by the technique of using a conformal transplant. In the final analysis, very little of the algorithm needs to be changed, but a speed up in running time of roughly 50 times is obtained, even though the total amount of data is reduced by only a factor of 28. The speed increases at the expense of peripheral resolution
Keywords
computer vision; stochastic processes; Poisson equations; color constancy; computer vision; conformal mapping; conformal transplantation lightness transplantation; optical flow; peripheral resolution; retinex lightness computation; shape from shading; surface reconstruction; varying resolution sensors; Algorithm design and analysis; Computer architecture; Computer vision; Conformal mapping; Humans; Image motion analysis; Image resolution; Image sensors; Optical sensors; Pixel; Poisson equations; Retina; Shape; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location
New York, NY
ISSN
1063-6919
Print_ISBN
0-8186-3880-X
Type
conf
DOI
10.1109/CVPR.1993.341074
Filename
341074
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