DocumentCode
2711979
Title
Depth from optical turbulence
Author
Tian, Yuandong ; Narasimhan, Srinivasa G. ; Vannevel, Alan J.
fYear
2012
fDate
16-21 June 2012
Firstpage
246
Lastpage
253
Abstract
Turbulence near hot surfaces such as desert terrains and roads during the summer, causes shimmering, distortion and blurring in images. While recent works have focused on image restoration, this paper explores what information about the scene can be extracted from the distortion caused by turbulence. Based on the physical model of wave propagation, we first study the relationship between the scene depth and the amount of distortion caused by homogenous turbulence. We then extend this relationship to more practical scenarios such as finite extent and height-varying turbulence, and present simple algorithms to estimate depth ordering, depth discontinuity and relative depth, from a sequence of short exposure images. In the case of general non-homogenous turbulence, we show that a statistical property of turbulence can be used to improve long-range structure-from-motion (or stereo). We demonstrate the accuracy of our methods in both laboratory and outdoor settings and conclude that turbulence (when present) can be a strong and useful depth cue.
Keywords
image restoration; optical distortion; turbulence; wave propagation; desert terrains; height-varying turbulence; hot surfaces; image blurring; image distortion; image restoration; long-range structure-from-motion; nonhomogenous turbulence; optical turbulence; roads; shimmering; summer; wave propagation; Cameras; Computational modeling; Optical distortion; Refractive index; Roads; Surface waves;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4673-1226-4
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2012.6247682
Filename
6247682
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