A datum feature extraction and deformation analysis method based on normal vector of point cloud

doi:10.13474/j.cnki.11-2246.2019.0100

Abstract

Abstract: In order to solve the problems of the existing difficulty of datum feature extraction and the lack of applicable analysis method of point cloud data in the application of three-dimensional laser scanning technology to the field of deformation monitoring,an efficient method for datum feature extraction and deformation analysis is proposed in this paper based on normal vector of point cloud.Firstly,owing to the local surface fitting obtains directly the geometric features by applying the point cloud model with low time complexity,this paper uses the local planar normal vector determined by the nearest neighbours of meet certain condition and follow the normal vector of the point cloud to detect the datum points.Then,the cubic B-spline curve fitting is performed on the datum points.To this end,elevation of the datum and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information is analyzed.The proposed approach is verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant.The results show that the method could obtain the entire information of the monitor object quickly and comprehensively,and reflect the datum deformation accurately.

Key words: deformation analysis, point cloud, normal vector, datum feature, cubic B-spline curve fitting

CLC Number:

P258

SUN Wenxiao, WANG Jian, JIN Fengxiang, LIANG Zhouyan. A datum feature extraction and deformation analysis method based on normal vector of point cloud[J]. 测绘通报, 2019, 0(3): 155-158,162.

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