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Remote Sensing for Land ＆ Resources. 2020, (02) Core

Point cloud simplification method combining K-means++ clustering with UAV LiDAR point cloud normal vectorsChinese Full TextEnglish Full Text (MT)

LI Peiting;ZHAO Qingzhan;TIAN Wenzhong;MA Yongjian;College of Information Science and Technology,Shihezi University;Division of National Remote Sensing Center,Xinjiang Production and Construction Corps;Geospatial Information Engineering Research Center,Xinjiang Production and Construction Corps;College of Mechanical and Electrical Engineering,Shihezi University;

Abstract: It is important to reduce the amount of unmanned aerial vehicle（UAV） light detection and ranging（Li DAR） data effectively based on point cloud simplification method,and this is of great significance for later point cloud storage and fast processing. The authors used K-means + + method to cluster point cloud normal vectors so as to achieve point cloud simplification. Firstly,the echo point cloud was removed by using the echo number. After that,the zero-mean normalization method was used to normal... More
Keywords：

point cloud K neighborhood; point cloud normal vector; K-means++ clustering method; Delaunay triangle;

  • Series：

    (A) Mathematics/ Physics/ Mechanics/ Astronomy; (I) Electronic Technology ＆ Information Science

  • Subject：

    Telecom Technology

  • Classification Code：

    TN958.98

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