Point Cloud Simplification Method Based on k-Means Clustering

Yibo He; Ranli Chen; Kan Wu; Zhixin Duan

doi:10.3788/LOP56.091002

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 9 >Page 091002 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 9, 091002 (2019)

Point Cloud Simplification Method Based on k-Means Clustering

Yibo He^1、*, Ranli Chen², Kan Wu³, and Zhixin Duan³

Author Affiliations

¹ Department of Architecture and Civil Engineering, Datong Vocational and Technical College of Coal, Datong, Shanxi 0 37003, China

² Department of Surveying Engineering, Shijiazhuang Institute of Railway Technology, Shijiazhuang, Hebei 0 50041, China

³ School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China

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DOI: 10.3788/LOP56.091002 Cite this Article Set citation alerts

Yibo He, Ranli Chen, Kan Wu, Zhixin Duan. Point Cloud Simplification Method Based on k-Means Clustering[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091002 Copy Citation Text

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Fig. 1. Compression rates and standard deviations for different numbers of clusters

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Fig. 2. Standard deviations and modeling results for two methods

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Fig. 3. Point cloud data after projection by section method

Yibo He, Ranli Chen, Kan Wu, Zhixin Duan. Point Cloud Simplification Method Based on k-Means Clustering[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091002

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