Laser-point cloud marking method, device and readable storage medium

Abstract

The embodiment of the invention provides a laser-point cloud marking method, a device and a readable storage medium, and belongs to the technical field of identification. The method includes steps ofacquiring laser-point cloud data, wherein the laser-point cloud data comprises laser-point cloud data corresponding to at least one target object; every laser point corresponding to the laser-point cloud data is displayed in a three-dimensional scene; dyeing every laser point; marking the laser point after being dyed. Through the method, every laser point can be dyed firstly, and then the laser point corresponding to every target object after being dyed is marked, thus a marker is not easy to feel tired during the marking process, and is easier to exactly finger out tiny target object, not easy to miss and wrongly mark the tiny target object; therefore, the marking speed and efficiency of the laser point are further improved.

Description

technical field [0001] The present invention relates to the field of recognition technology, in particular to a laser point cloud marking method, device and readable storage medium. Background technique [0002] At present, with the development of automatic driving technology, it is particularly important to identify target objects around the vehicle (such as vehicles, pedestrians, tricycles, bicycles, etc.). line or 64-line laser radar) to detect target objects around the vehicle, the laser radar emits laser beams around, and when the laser beam encounters an object, it returns a laser point cloud, and identifies the surrounding target objects and the size of the target object through the laser point cloud , position, speed, etc. [0003] At present, the main way to identify the target object through the laser point cloud is: manually mark the received laser point cloud point by point in advance to obtain the laser point cloud sample data corresponding to the target object...

AI Technical Summary

Problems solved by technology

[0004] At present, the received laser point cloud is manually marked point by point, and the laser point cloud contains a huge amount of laser point data. Points, so the labelers still need to spend a lot of time and energy to label some tiny target objects when distinguishing, which leads to the problem of low labeling efficiency

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