Classification method and device for objects in road point cloud, electronic equipment and storage medium

Abstract

The invention provides a classification method and device for objects in road point cloud, electronic equipment and a storage medium. The classification method comprises: collecting initial point cloud data; dividing the initial point cloud data according to a first preset division interval to obtain a point cloud profile; determining a target two-dimensional image corresponding to the point cloud profile according to the number of point clouds in each pixel included in the point cloud profile and a mapping relation between the point clouds and the gray values; slicing the target two-dimensional image along a preset direction according to a second division preset interval, and determining a pavement layer according to the number of point clouds included in each slice layer; and denoising and classifying the target two-dimensional image according to the pavement layer and the preset height distance, and determining classification information of the pavement object in the vehicle driving process. By adopting the technical scheme provided by the invention, the two-dimensional point cloud profile with a certain width is taken as a processing unit, and under the condition that the vehicle-mounted point cloud data volume is huge, the operation space is ensured, and the processing efficiency is improved.

Description

technical field [0001] The present application relates to the field of point cloud data processing, in particular to a method, device, electronic equipment and storage medium for classifying objects in road point clouds. Background technique [0002] The vehicle-mounted mobile measurement system is a new type of measurement equipment composed of a variety of high-performance sensors such as laser scanners, inertial navigation, and panoramic cameras, which can be directly mounted on mobile carriers such as automobiles. Using the non-contact measurement method, you can directly obtain the 3D coordinates and attribute information of a large number of points in a large range during the driving process. The acquisition speed is fast and the measurement accuracy is high. The output point cloud results are combined with the panorama taken by the panoramic camera. The matching and fusion of pictures can restore the appearance of urban street scenes to the greatest extent. However, ...

AI Technical Summary

Problems solved by technology

[0003] Wide scanning range and dense point cloud data are one of the advantages of the vehicle-mounted mobile measurement system. However, the point cloud data collected by the vehicle-mounted mobile measurement system is large, and it is difficult to perform unified processing; and the collected point cloud also includes The noise that affects the subsequent processing needs to be removed. The existing point cloud denoising technology is mostly used in 3D scenes. The method of directly processing point clouds in 3D scenes must first compare within the range of 360 degrees and select a suitable observation direction. At the same time, in the 3D scene, the composition of the point cloud data is relatively complex, and the amount of data to be processed is relatively large, so the collection and processing of the point cloud data in the 3D scene are relatively complicated, resulting in the processing of the point cloud. The speed is slow, which affects the efficiency of point cloud data processing

Images