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
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;
Conference_Titel :
Computer and Robot Vision (CRV), 2013 International Conference on
Conference_Location :
Regina, SK
Print_ISBN :
978-1-4673-6409-6
DOI :
10.1109/CRV.2013.22