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ANMS-Codes

version 1.0.0 (6.11 MB) by Alex Bailo
Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution

18 Downloads

Updated 22 Aug 2021

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Keypoint detection usually results in a large number of keypoints which are mostly clustered, redundant, and noisy. These keypoints often require special processing like Adaptive Non-Maximal Suppression (ANMS) to retain the most relevant ones. In this paper, we present three new efficient ANMS approaches which ensure a fast and homogeneous repartition of the keypoints in the image. For this purpose, a square approximation of the search range to suppress irrelevant points is proposed to reduce the computational complexity of the ANMS. To further speed up the proposed approaches, we also introduce a novel strategy to initialize the search range based on image dimension which leads to a faster convergence. An exhaustive survey and comparisons with already existing methods are provided to highlight the effectiveness and scalability of our methods and the initialization strategy.

Cite As

Alex Bailo (2021). ANMS-Codes (https://github.com/BAILOOL/ANMS-Codes), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2015a
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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.