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Point cloud precision determination method, electronic equipment and computer storage medium

A determination method, point cloud technology, applied in computer parts, calculation, electromagnetic wave re-radiation, etc., can solve problems such as difficulty in adapting to large-scale map data production and low efficiency, and achieve the effect of improving determination efficiency

Pending Publication Date: 2022-07-08
AUTONAVI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing massive point cloud data processing process not only has strict requirements on computer performance, but also requires a large number of manual inspections, manual point selection and other operations, resulting in extremely low efficiency and it is difficult to adapt to the production of large-scale map data.

Method used

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  • Point cloud precision determination method, electronic equipment and computer storage medium
  • Point cloud precision determination method, electronic equipment and computer storage medium
  • Point cloud precision determination method, electronic equipment and computer storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0020] For ease of understanding, before the detailed description of the implementation process of the method of the present application, a usage scenario of the method is exemplarily described, but the method of the present application is not limited to this usage scenario, and can also be applied to other suitable scenarios. in the scene.

[0021] In this usage scenario, it is used to determine the point cloud accuracy of the point cloud collected by the vehicle-mounted mobile measurement system in the same geographic space (the geographic space can be a scanned road or a cell, etc.) in different times. The point cloud accuracy is used to indicate the same The difference value between the point clouds collected in different times in the geographic space or a certain area in the geographic space, and the point cloud that needs to be aligned according to the accuracy of the point cloud, so as to avoid the need for point cloud alignment for a large number of point clouds. The p...

Embodiment 2

[0102] refer to figure 2 , showing a schematic flowchart of the steps of the point cloud processing method according to the second embodiment of the present application.

[0103] The method includes:

[0104] Step S202: Acquire the point cloud accuracy between the first point cloud and the second point cloud.

[0105] The point cloud precision is the point cloud precision obtained by the method in the foregoing embodiment. It should be noted that, if the geographic space corresponding to the first point cloud and the second point cloud is divided into multiple regions, the point cloud accuracy of each region can be obtained respectively. If the geographic space is not divided into multiple regions, the point cloud accuracy of the geographic space can be directly obtained.

[0106] By dividing the geographic space into multiple regions, the number of points involved in subsequent calculations can be reduced, thereby reducing the computational load.

[0107] The following t...

Embodiment 3

[0121] refer to image 3 , showing a structural block diagram of the device for determining the accuracy of a point cloud according to Embodiment 3 of the present application.

[0122] In this embodiment, the device includes:

[0123] The first determination module 302 is configured to perform semantic feature extraction on the target point cloud, so as to determine the point cloud of the marker from the target point cloud, and the target point cloud includes a first point cloud and a second point cloud, wherein, The first point cloud and the second point cloud are any two point clouds in the plurality of point clouds;

[0124] The second determination module 304 is configured to determine the key feature points corresponding to the marker according to the point cloud of the marker;

[0125] A third determining module 306, configured to determine the key feature points of the identifier of the first point cloud and the corresponding key feature points in the same marker in t...

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Abstract

The embodiment of the invention provides a point cloud precision determination method, electronic equipment and a computer storage medium. The method comprises the steps that semantic feature extraction is carried out on target point clouds to determine point clouds of markers from the target point clouds, the target point clouds comprise a first point cloud and a second point cloud, and the first point cloud and the second point cloud are any two point clouds in multiple point clouds; determining key feature points corresponding to the marker according to the point cloud of the marker; determining key feature points of the marker of the first point cloud and corresponding key feature points in the same marker in the second point cloud as homonymy point pairs; and determining the point cloud precision between the first point cloud and the second point cloud according to a difference value between the two key feature points in the homonymy point pair. According to the method, the point cloud precision of the point clouds collected at different times can be quickly and accurately obtained.

Description

technical field [0001] The embodiments of the present application relate to the technical field of map making, and in particular, to a method for determining the accuracy of a point cloud, an electronic device, and a computer storage medium. Background technique [0002] In the process of collecting point cloud data by the vehicle-mounted mobile measurement system, due to the interference (occlusion) of the external environment and changes in weather (wind, rain, snow, etc.), and the performance limitations of the lidar sensor itself, the same geographic location collected multiple times is caused. Objects in the space have inconsistencies in point cloud data, and sometimes there are meters-level deviations, which cannot meet the needs of high-precision maps. Therefore, in the process of subsequent processing of point cloud data, it is necessary to improve the accuracy. However, the existing massive point cloud data processing process not only has strict requirements on com...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06V10/46G06V10/75G01S17/931G01S17/89
CPCG01S17/89G01S17/931
Inventor 马朝帅万斌
Owner AUTONAVI
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