计算机工程2024，Vol.50Issue(10)：16-34,19.DOI:10.19678/j.issn.1000-3428.0068580
基于深度学习特征的二维图像匹配算法综述
Review of 2D Image Matching Algorithms Based on Deep Learning Features
摘要
Abstract
The objective of image matching is to establish correspondences between similar structures across two or more images.This task is fundamental to computer vision,with applications in robotics,remote sensing,and autonomous driving.With the advancements in deep learning in recent years,Two-Dimensional(2D)image matching algorithms based on deep learning have seen regular improvements in feature extraction,description,and matching.The performance of these algorithms in terms of matching accuracy and robustness has surpassed that of traditional algorithms,leading to significant advancements.First,this study summarizes 2D image matching algorithms based on deep learning features from the past ten years and categorizes them into three types:two-stage image matching based on local features,image matching of joint detection and description,and image matching without feature detection.Second,the study details the development processes,classification methods,and performance evaluation metrics of these three categories and summarizes their advantages and limitations.Typical application scenarios of 2D image matching algorithms are then introduced,and the effects of research progress in 2D image matching on its application domains are analyzed.Finally,the study summarizes the development trends of 2D image matching algorithms and discusses future prospects.关键词
图像匹配/局部特征/深度学习/特征检测/特征描述Key words
image matching/local feature/deep learning/feature detection/feature description分类
信息技术与安全科学引用本文复制引用
黄开基,杨华..基于深度学习特征的二维图像匹配算法综述[J].计算机工程,2024,50(10):16-34,19.基金项目
国家自然科学基金联合基金项目(U22A20208). （U22A20208）
