Title:
VISUAL POINT CLOUD-BASED SEMANTIC VECTOR MAP BUILDING METHOD, DEVICE, AND ELECTRONIC APPARATUS
Document Type and Number:
WIPO Patent Application WO/2020/098316
Kind Code:
A1
Abstract:
The present application discloses a visual point cloud-based semantic vector map building method, a visual point cloud-based semantic vector map building device, and an electronic apparatus. According to one embodiment, the visual point cloud-based semantic vector map building method comprises: performing object detection on an image acquired by an image acquisition apparatus, and acquiring pixel targets in the image and attribute information thereof; determining position information of each pixel target in the image; combining the attribute information and the position information of each pixel target, and generating a semantic point cloud; and building a semantic vector map on the basis of the semantic point cloud. The visual point cloud-based semantic vector map building method completes high-resolution map building at an extremely low cost simply by using images and a small amount of priori information of an external sensor.
Inventors:
YAN QINRUI (CN)
YANG SHUAI (CN)
YANG SHUAI (CN)
Application Number:
PCT/CN2019/099205
Publication Date:
May 22, 2020
Filing Date:
August 05, 2019
Export Citation:
Assignee:
NANJING INST OF ADVANCED ARTIFICIAL INTELLIGENCE LTD (CN)
International Classes:
G06T19/00
Foreign References:
| CN109461211A | 2019-03-12 | |||
| CN108416808A | 2018-08-17 | |||
| CN108124489A | 2018-06-05 | |||
| US20180275277A1 | 2018-09-27 |
Other References:
QI, XUXIANG: "Deep Learning Based Semantic Labelling of 3D Point Cloud in Visual SLAM", IOP CONFERENCE SERIES: MATERIALS SCIENCE AND ENGINEERING, vol. 428, no. 012023, 1 September 2018 (2018-09-01) - 1 October 2018 (2018-10-01), pages 1 - 10, XP055707458, ISSN: 1757-899X
Attorney, Agent or Firm:
NANJING XINHUIHENGCHENG INTELLECTUAL PROPERTY AGENCY CO., LTD (CN)
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