Fast dense stereo correspondences by binary locality sensitive hashing

Philipp Heise; Brian Jensen; Sebastian Klose; Alois Knoll

doi:10.1109/ICRA.2015.7138987

Fast dense stereo correspondences by binary locality sensitive hashing

Philipp Heise, Brian Jensen, Sebastian Klose, Alois Knoll

nformatics 6 - Chair of IRobotics, Artificial Intelligence and Real-time Systems

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

The stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive hashing and is well suited to implementation on the GPU. Our proposed method is capable of processing very high-resolution stereo images at near real-time rates. An evaluation on the new Middlebury and Disney high-resolution stereo benchmarks demonstrates that our proposed method performs well compared to existing state of the art algorithms.

Original language	English
Title of host publication	2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	105-110
Number of pages	6
Edition	June
ISBN (Electronic)	9781479969234
DOIs	https://doi.org/10.1109/ICRA.2015.7138987
State	Published - 29 Jun 2015
Event	2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: 26 May 2015 → 30 May 2015

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
Number	June
Volume	2015-June
ISSN (Print)	1050-4729

Conference

Conference	2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Country/Territory	United States
City	Seattle
Period	26/05/15 → 30/05/15

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10.1109/ICRA.2015.7138987

Cite this

Heise, P., Jensen, B., Klose, S., & Knoll, A. (2015). Fast dense stereo correspondences by binary locality sensitive hashing. In 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 (June ed., pp. 105-110). Article 7138987 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2015-June, No. June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2015.7138987

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title = "Fast dense stereo correspondences by binary locality sensitive hashing",

abstract = "The stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive hashing and is well suited to implementation on the GPU. Our proposed method is capable of processing very high-resolution stereo images at near real-time rates. An evaluation on the new Middlebury and Disney high-resolution stereo benchmarks demonstrates that our proposed method performs well compared to existing state of the art algorithms.",

author = "Philipp Heise and Brian Jensen and Sebastian Klose and Alois Knoll",

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doi = "10.1109/ICRA.2015.7138987",

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Heise, P, Jensen, B, Klose, S & Knoll, A 2015, Fast dense stereo correspondences by binary locality sensitive hashing. in 2015 IEEE International Conference on Robotics and Automation, ICRA 2015. June edn, 7138987, Proceedings - IEEE International Conference on Robotics and Automation, no. June, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 105-110, 2015 IEEE International Conference on Robotics and Automation, ICRA 2015, Seattle, United States, 26/05/15. https://doi.org/10.1109/ICRA.2015.7138987

Fast dense stereo correspondences by binary locality sensitive hashing. / Heise, Philipp; Jensen, Brian; Klose, Sebastian et al.
2015 IEEE International Conference on Robotics and Automation, ICRA 2015. June. ed. Institute of Electrical and Electronics Engineers Inc., 2015. p. 105-110 7138987 (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2015-June, No. June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive hashing and is well suited to implementation on the GPU. Our proposed method is capable of processing very high-resolution stereo images at near real-time rates. An evaluation on the new Middlebury and Disney high-resolution stereo benchmarks demonstrates that our proposed method performs well compared to existing state of the art algorithms.

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Heise P, Jensen B, Klose S, Knoll A. Fast dense stereo correspondences by binary locality sensitive hashing. In 2015 IEEE International Conference on Robotics and Automation, ICRA 2015. June ed. Institute of Electrical and Electronics Engineers Inc. 2015. p. 105-110. 7138987. (Proceedings - IEEE International Conference on Robotics and Automation; June). doi: 10.1109/ICRA.2015.7138987

Fast dense stereo correspondences by binary locality sensitive hashing

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