Map data labeling method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a map data labeling method and device, equipment and a storage medium. The method comprises the steps of obtaining point cloud data of a target scene; Fittingthe ground based on the point cloud data, and generating a two-dimensional map of the target scene; Based on a first position of a surface element in a two-dimensional map, determining a second position of the surface element on the ground, the surface element being a road identifier drawn on a road surface; And acquiring three-dimensional data of the surface element on the second position based on the point cloud data, and marking the three-dimensional data of the surface element into a three-dimensional map. According to the technical scheme provided by the embodiment of the invention, the labeling speed of the map data, especially the three-dimensional map data, can be increased.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technology, and in particular, to a method, device, device, and storage medium for labeling map data. Background technique [0002] Autonomous driving technology needs to rely on high-precision maps. Vehicles can drive based on road information in high-precision maps. Therefore, the road information in high-precision maps needs to be very comprehensive and accurate. This leads to a very high complexity of high-precision maps, including a lot of data on various road elements (such as traffic lights, road lines, etc.), making the production of high-precision maps very difficult and very low in production efficiency. [0003] At present, in the process of generating high-precision maps, road elements are usually directly identified and extracted from the point cloud, and then the three-dimensional data of the road elements in the point cloud are marked on the high-precision map. In...

AI Technical Summary

Problems solved by technology

This leads to a very high complexity of high-precision maps, including a lot of data on various road elements (such as traffic lights, road lines, etc.), which makes it very difficult to produce high-precision maps, and the production efficiency is very low

[0003] At present, in the process of generating high-precision maps, road elements are usually directly identified and extracted from the point cloud, and then the three-dimensional data of the road elements in the point cloud are marked on the high-precision map. In this way, based on point Cloud identification processing is more complex, time-consuming and less efficient

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