AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (20 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

A Vision-aided Localization and Geo-registration Method for Urban ARGIS Based on 2D Maps

Chen DENG1Xiong YOU1 ( )Weiwei ZHANG1Meixia ZHI2Diao LIN1Wang XU1
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450052, China
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Show Author Information

Abstract

Augmented Reality Geographic Information System (ARGIS) applications can only provide users accurate content services with a highly precise geo-registration. However, the absolute 6DOF (Degree of Freedom) pose provided by the portable sensors is usually inaccurate in urban outdoors, resulting in poorly geo-registration accuracy for ARGIS applications. Aiming at this issue, an automatic vision-aided localization method based on the 2D map is proposed to improve the initial localization accuracy of the portable sensors, and an overall geo-registration optimization framework for outdoor ARGIS is proposed. Based on the initial pose provided by the sensors, the basic principles of the vision-aided localization method are expounded in detail. The experimental results show that the proposed method can effectively correct the initial pose obtained by the pose sensors, and improve the geo-registration accuracy of outdoor ARGIS applications ultimately.

References

【1】
【1】
 
 
Journal of Geodesy and Geoinformation Science
Pages 93-110

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
DENG C, YOU X, ZHANG W, et al. A Vision-aided Localization and Geo-registration Method for Urban ARGIS Based on 2D Maps. Journal of Geodesy and Geoinformation Science, 2022, 5(3): 93-110. https://doi.org/10.11947/j.JGGS.2022.0310

702

Views

42

Downloads

0

Crossref

1

Scopus

1

CSCD

Received: 10 January 2022
Accepted: 25 July 2022
Published: 20 September 2022
© 2022 Journal of Geodesy and Geoinformation Science