首页|Impact of cross-section centers estimation on the accuracy of the point cloud spatial expansion using robust M-estimation and Monte Carlo simulation
Impact of cross-section centers estimation on the accuracy of the point cloud spatial expansion using robust M-estimation and Monte Carlo simulation
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NSTL
Elsevier
The point cloud spatial expansion (PCSE) method creates an alternative form of representing the shape of symmetrical objects and introduces additional descriptive geometric parameters. An important element of the procedure is determining the course of the axis of symmetry of cylindrical objects based on cross-sections of point clouds. Outliers occurring in laser measurements are of great importance in this case. In this study, six robust estimation methods were used to determine the coordinates of the section centers. Accuracy analysis was performed both for data simulated with the Monte Carlo method and the real data. The study showed the advantage of robust methods for the PCSE method over the classical method of least squares estimation.
PCSESpatial expansionPoint cloudMonte Carlo simulationRobust estimationCYLINDERSCANNER
NSTL
Elsevier
