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Mapping method and system based on visual semantic point cloud

A point cloud, semantic technology, applied in machine vision and map construction, deep learning field, can solve problems such as difficulty in map reuse

Pending Publication Date: 2021-02-09
SAIC MOTOR
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with the sensor solution of laser point cloud map, the sensor solution of visual point cloud map has a huge cost advantage, but it is limited by the accuracy and difficulty in map reuse. At present, visual point cloud map has not obtained large-scale scale like laser point cloud map application

Method used

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  • Mapping method and system based on visual semantic point cloud
  • Mapping method and system based on visual semantic point cloud
  • Mapping method and system based on visual semantic point cloud

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Embodiment Construction

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0053] Such as figure 1 As shown, it is a method flowchart of an embodiment of a mapping method based on visual semantic point cloud disclosed in the present invention, and the method may include the following steps:

[0054] S101. Collect image data during the running of the vehicle, wherein the image data includes: four-way surround-view images and motion parameters of the vehicle;

[0055] When it is necessary to construct a point cloud map, firstly, the i...

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Abstract

The invention discloses a mapping method and system based on visual semantic point cloud, which can extract semantic information through deep learning frameworks such as semantic segmentation, targetdetection and the like, can add point cloud registration constraints into an SLAM system and perform post-processing on a point cloud map in combination with an octree map, effectively improves the mapping accuracy; According to the method and device, after the octree is used for filtering the original point cloud, the central coordinates of the occupied voxel and the semantic information of the voxel of the octree map are converted into the semantic point cloud map again, so that redundant points in the original map are greatly reduced, the storage space is saved, and subsequent computing resource consumption is reduced; meanwhile, the problem that the map is difficult to use after being converted into the octree structure is also solved.

Description

technical field [0001] The present invention relates to the technical fields of deep learning, machine vision and map construction, and in particular to a mapping method and system based on visual semantic point cloud. Background technique [0002] Point cloud maps are widely used in simultaneous localization and mapping (SLAM) technology, and play an important role in specific functions such as real-time tracking of robot positions and local mapping. According to the sensor scheme adopted, the point cloud map can be mainly divided into the laser point cloud map directly collected by the lidar, and the visual point cloud map obtained by converting the image collected by the camera. Compared with the sensor solution of laser point cloud map, the sensor solution of visual point cloud map has a huge cost advantage, but it is limited by the accuracy and difficulty in map reuse. At present, visual point cloud map has not obtained large-scale scale like laser point cloud map appl...

Claims

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Application Information

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IPC IPC(8): G06T11/20G06K9/34G06T3/40G06T17/00
CPCG06T11/206G06T3/4038G06T17/00G06V10/267G06V2201/07
Inventor 梁帅乔延琦陈祝金忠孝
Owner SAIC MOTOR
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