DocumentCode
625125
Title
Recovering Dense Stereo Depth Maps Using a Single Gaussian Blurred Structured Light Pattern
Author
Xida Chen ; Yee-Hong Yang
Author_Institution
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear
2013
fDate
28-31 May 2013
Firstpage
295
Lastpage
302
Abstract
In this paper, we present a new single shot structured light method to recover dense depth maps. Contrary to most temporal coding methods which require projecting a series of patterns, our method needs one color pattern only. Unlike most single shot spatial coding methods which establish correspondence along the edges of the captured images, our method produces a dense set of correspondences. Our method is built based on a new important observation that a Gaussian blurred De Bruijn pattern preserves the desirable windowed uniqueness property. A Gaussian blurred De Bruijn pattern is used so that the color of every illuminated pixel is used to its fullest advantage. The simulated experiments show that the proposed method establishes a correspondence set whose density and accuracy are close to that of using a temporal coding method. We also demonstrate the robustness of our approach by applying it to several real-world datasets.
Keywords
Gaussian processes; image coding; stereo image processing; Gaussian blurred De Bruijn pattern; dense stereo depth maps recovery; illuminated pixel; single Gaussian blurred structured light pattern; single shot structured light method; spatial coding methods; temporal coding methods; Accuracy; Encoding; Image coding; Image color analysis; Image edge detection; Kernel; Stereo vision; De Bruijn; Dense Correspondence; Structured Light;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Robot Vision (CRV), 2013 International Conference on
Conference_Location
Regina, SK
Print_ISBN
978-1-4673-6409-6
Type
conf
DOI
10.1109/CRV.2013.22
Filename
6569216
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