Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features-Reference-Cited by-同舟云学术

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Laser point cloud registration method based on iterative closest point improved by Gaussian mixture model considering corner features

Published:2022-02-01 Issue:3 Volume:43 Page:932-960
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wang Yongzhi¹^ORCID,Zhou Tao¹,Li Hui¹,Tu Wenlong¹,Xi Jing¹,Liao Lixia²

Affiliation:

1. School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, People’s Republic of China

2. Department of Surveying and EngineeringZhejiang Land Surveying and Planning Co. Ltd, Hangzhou, People’s Republic of China

Funder

National Natural Science Foundation of China

Program of Qingjiang Excellent Young Talents, Jiangxi University of Science and Technology

Youth Jinggang Scholars Program in Jiangxi Province

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2021.2022242

Reference41 articles.

1. A method for registration of 3-D shapes

2. Keypoint design and evaluation for place recognition in 2D lidar maps

3. A Survey Of Free-Form Object Representation and Recognition Techniques

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