The Plane Feature Recognition Method for Modern Building Point Cloud
[Purposes]According to the patch characteristics of modern building point cloud data,a plane segmentation recognition method based on random sampling consistent algorithm is proposed in this pa-per.[Methods]In this method,the spatial grid element is established by three-dimensional grid divi-sion,and then the local grid element is determined according to the random sampling points,the plane model is fitted by random mechanism,and the candidate model set is determined by local scoring.Nor-mal constraints and coplanar segmentation are used to solve the problems of over-segmentation and in-sufficient segmentation.[Findings]Finally,the current optimal model and consistent set are obtained,and the point cloud segmentation can be completed.[Conclusions]The experimental results show that this method can segment the buildings with plane features effectively.
point cloudsegmentationlocal samplingconsistent set
NETL
NSTL
万方数据
