BRISK: Binary Robust invariant scalable keypoints

Authors:
Stefan Leutenegger;Margarita Chli;Roland Y. Siegwart
Affiliations:
Autonomous Systems Lab, ETH Zürich, Switzerland;Autonomous Systems Lab, ETH Zürich, Switzerland;Autonomous Systems Lab, ETH Zürich, Switzerland
Venue:
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Year:
2011

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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