@inproceedings{f2766712cb9b4f1d8d8f59efdbc1c340,
title = "A Brief Survey of Feature Based Image Matching",
abstract = "The image matching task, which aims to find the correspondence between elements across images, is a fundamental component for many computer vision applications. In visual simultaneous localization and mapping algorithms, the pose can be estimated on the basis of correspondences between multiple measurements obtained by on-board cameras. Feature-based image matching methods have rapidly developed and been widely utilized in the past few decades due to their robustness and accuracy. In this paper, feature-based image matching task is reviewed according to its process, including feature detection, feature description, and feature matching.",
keywords = "computer vision, deep learning, feature matching, image matching",
author = "Xingming Wu and Kuiyuan Fu and Zhong Liu and Weihai Chen",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022 ; Conference date: 16-12-2022 Through 19-12-2022",
year = "2022",
doi = "10.1109/ICIEA54703.2022.10006226",
language = "英语",
series = "ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1634--1639",
editor = "Wenxiang Xie and Shibin Gao and Xiaoqiong He and Xing Zhu and Jingjing Huang and Weirong Chen and Lei Ma and Haiyan Shu and Wenping Cao and Lijun Jiang and Zeliang Shu",
booktitle = "ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications",
address = "美国",
}