Feature point matching algorithm based on metric learning

ChangJiang Jiang; Tong Lin; YuHang Zhang; ChangHao Zhao

doi:10.1117/12.2671321

28 April 2023 Feature point matching algorithm based on metric learning

ChangJiang Jiang, Tong Lin, YuHang Zhang, ChangHao Zhao

Author Affiliations +

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105A (2023) https://doi.org/10.1117/12.2671321
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

In order to solve the problem that the quality of feature point matching and the computational efficiency cannot be achieved simultaneously, this paper proposes twin network feature point matching algorithm based on metric learning. Features and feature descriptors of image blocks is extracted through twin networks, and similarity measure loss function is used to complete feature matching in this paper. The results of network training and testing on HPatches dataset show that the algorithm is helpful to improve the accuracy and matching efficiency of feature matching point pairs.

Citation Download Citation

ChangJiang Jiang, Tong Lin, YuHang Zhang, and ChangHao Zhao "Feature point matching algorithm based on metric learning", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105A (28 April 2023); https://doi.org/10.1117/12.2671321

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KEYWORDS

Feature extraction

Education and training

Neural networks

Image processing

Distance measurement

Network architectures

Quantitative analysis

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