A matching method for three dimensional laser point cloud data and unmanned aerial vehicle point cloud data

Abstract

The invention relates to a matching method for three dimensional laser point cloud data and unmanned aerial vehicle point cloud data. The method includes the following steps: step S1: the unmanned aerial vehicle point cloud data of the target is obtained by the unmanned aerial vehicle; step S2: the three dimensional laser point cloud data of the target is obtained through a three dimensional laserscanner; step S3: the three dimensional laser point cloud data and the unmanned aerial vehicle point cloud data are converted to the same format; step S4: the unmanned aerial vehicle point cloud datais used as a reference system, the three dimensional laser point cloud data is used as a mobile system, multiple same points are selected based on the RGB color types of the three dimensional point cloud data, and the correlation matching is established according to the unmanned aerial vehicle point cloud data and the three dimensional point cloud data by utilizing a global matching mode. The method has effects that: ground-air integration is realized through the obtaining process of the point cloud data, the existence of data missing of the point cloud data unidirectionally obtained by the three dimensional laser or the unmanned aerial vehicle is reduced, and the more comprehensive data information of the target is provided for the research personnel.

Description

technical field [0001] The invention relates to a method for matching three-dimensional laser point cloud data and unmanned aerial vehicle point cloud data. Background technique [0002] At present, 3D laser and UAV point cloud data are developing rapidly in the field of forestry. Due to the needs of research, it is often necessary to accurately obtain the 3D structure information of the forest canopy. How to quickly and effectively obtain comprehensive point cloud data is particularly important. Although the use of drones and 3D laser scanners to obtain point cloud data is more common, the one-way ground point cloud data or aerial point cloud data often lacks point cloud data, which cannot fully reflect the characteristic information of the target. . SUMMARY OF THE INVENTION [0003] The present invention improves the above problems, that is, the technical problem to be solved by the present invention is to realize the matching of ground and empty point cloud data and ob...

AI Technical Summary

Problems solved by technology

Although the use of UAVs and 3D laser scanners to obtain point cloud data is more common, one-way ground point cloud data or aerial point cloud data often have missing point cloud data, which cannot fully reflect the characteristic information of the target object.

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