Performance Analysis of Feature Extraction Methods towards Underwater vSLAM-Reference-Cited by-同舟云学术

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Performance Analysis of Feature Extraction Methods towards Underwater vSLAM

Published:2022-06-27 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 17th International Conference on Control & Automation (ICCA)
language:
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Author:

Wu Di¹,Wang Yue²,Hou Dongdong³,Hao Lichao¹,Zhang Liukun¹,Wang Di¹

Affiliation:

1. Harbin Engineering University,College of Intelligent Systems Science and Engineering,Harbin,China,150001

2. Harbin Engineering University,Qingdao Innovation and Development Center,Qingdao,China,266404

3. The 713 Research Institute of CSSC,Zhengzhou,China,450015

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9831427/9831807/09831964.pdf?arnumber=9831964

Reference20 articles.

1. Experimental comparison of open source vision-based state estimation algorithms;li;International Symposium on Experimental Robotics,2016

2. Object recognition from local scale-invariant features

3. Evaluation of Several Feature Detectors/Extractors on Underwater Images towards vSLAM

4. Distinctive Image Features from Scale-Invariant Keypoints

5. SURF: Speeded Up Robust Features

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Mismatch Correction Method Based on Two-Way Strategies of Spatial Vector Feature;2024 IEEE 18th International Conference on Control & Automation (ICCA);2024-06-18

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