Recovering Dense Stereo Depth Maps Using a Single Gaussian Blurred Structured Light Pattern

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 corresponde...

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Bibliographic Details
Published in:2013 International Conference on Computer and Robot Vision (CRV) pp. 295 - 302
Main Authors: Xida Chen, Yee-Hong Yang
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2013
Subjects:
Accuracy
De Bruijn
Dense Correspondence
Encoding
Image coding
Image color analysis
Image edge detection
Kernel
Stereo vision
Structured Light
ISBN:1467364096, 9781467364096
Online Access:Get full text
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Summary: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.
ISBN:1467364096
9781467364096
DOI:10.1109/CRV.2013.22