Article

BRISK: Binary Robust invariant scalable keypoints

Authors:

Stefan Leutenegger,

Margarita Chli,

Roland Y. SiegwartAuthors Info & Claims

ICCV '11: Proceedings of the 2011 International Conference on Computer Vision

Pages 2548 - 2555

https://doi.org/10.1109/ICCV.2011.6126542

Published: 06 November 2011 Publication History

Abstract

Effective and efficient generation of keypoints from an image is a well-studied problem in the literature and forms the basis of numerous Computer Vision applications. Established leaders in the field are the SIFT and SURF algorithms which exhibit great performance under a variety of image transformations, with SURF in particular considered as the most computationally efficient amongst the high-performance methods to date. In this paper we propose BRISK

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BRISK: Binary Robust invariant scalable keypoints
1. General and reference
  1. Cross-computing tools and techniques

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Published In

ICCV '11: Proceedings of the 2011 International Conference on Computer Vision

November 2011

2669 pages

ISBN:9781457711015

Publisher

IEEE Computer Society

United States

Publication History

Published: 06 November 2011

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Zeng ZSun SLi TYin JShen YHuang Q(2024)Exploring the topic evolution of Dunhuang murals through image classificationJournal of Information Science10.1177/0165551522107433650:1(35-52)Online publication date: 1-Feb-2024
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Hu TScargill TYang FChen YLan GGorlatova MShu YLiu JTan RHe YChen J(2024)SEESys: Online Pose Error Estimation System for Visual SLAMProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699341(322-335)Online publication date: 4-Nov-2024
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Venugopalan HDin ZCarpenter TLowe-Power JKing SShafiq Z(2024)AragornProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314067:4(1-31)Online publication date: 12-Jan-2024
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Image feature point matching method based on improved BRISK

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