Cited by 1,542Advanced Vision and ImagingOptical measurement and interference techniquesSatellite Image Processing and Photogrammetry

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High-accuracy stereo depth maps using structured light

Scharstein, D., Szeliski, R.·2003·2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.

DOI 10.1109/cvpr.2003.1211354

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Abstract

Progress in stereo algorithm performance is quickly outpacing the ability of existing stereo data sets to discriminate among the best-performing algorithms, motivating the need for more challenging scenes with accurate ground truth information. This paper describes a method for acquiring high-complexity stereo image pairs with pixel-accurate correspondence information using structured light. Unlike traditional range-sensing approaches, our method does not require the calibration of the light sources and yields registered disparity maps between all pairs of cameras and illumination projectors. We present new stereo data sets acquired with our method and demonstrate their suitability for stereo algorithm evaluation. Our results are available at http://www.middlebury.edu/stereo/.

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Authors: Scharstein, D., & Szeliski, R.
Affiliations: Middlebury College (US)
Microsoft (United States) (US)
Venue: 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.
Publisher: IEEE Comput. Soc
Published: 2003-11-04
Pages: I-195-I-202
ISSN: 1063-6919 (ISSN-L)
DOI: 10.1109/cvpr.2003.1211354
OpenAlex: W2155479981
Cited by: 1,542
References: 28
Citations by year: 2026: 10 · 2025: 29 · 2024: 31 · 2023: 51 · 2022: 58 · 2021: 80 · 2020: 88 · 2019: 93 · 2018: 93 · 2017: 88 · 2016: 103 · 2015: 110 · 2014: 98 · 2013: 95 · 2012: 105
FWCI: 21.66
Type: conference paper
Language: en
Open access: closed
Locations: IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Satellite Image Processing and Photogrammetry
Keywords: stereo vision, structured light, ground truth, disparity map, range sensing

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High-accuracy stereo depth maps using structured light

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