An Efficient Class-Constrained DBSCAN Approach for Large-Scale Point Cloud Clustering-Reference-Cited by-同舟云学术

An Efficient Class-Constrained DBSCAN Approach for Large-Scale Point Cloud Clustering

Published:2022 Issue: Volume:15 Page:7323-7332
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Zhang Hua¹^ORCID,Duan Zhenwei¹^ORCID,Zheng Nanshan¹^ORCID,Li Yong²,Zeng Yu³,Shi Wenzhong⁴^ORCID

Affiliation:

1. School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China

2. Sichuan Institute of Coal Field Geological Engineering Exploration and Designing, Chengdu, China

3. Sichuan Institute of Coal Field Surveying and Mapping Engineering, Chengdu, China

4. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference31 articles.

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4. Non-parametric segmentation of ALS point clouds using mean shift;thomas;J Appl Geophys,2007

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