Feature point matching algorithm based on metric learning

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.