@article{DENG2022, 
author = {Chen DENG and Xiong YOU and Weiwei ZHANG and Meixia ZHI and Diao LIN and Wang XU},
title = {A Vision-aided Localization and Geo-registration Method for Urban ARGIS Based on 2D Maps},
year = {2022},
journal = {Journal of Geodesy and Geoinformation Science},
volume = {5},
number = {3},
pages = {93-110},
keywords = {augmented reality, ARGIS, geo-registration, vision-aided localization, hybrid localization, portable sensors},
url = {https://www.sciopen.com/article/10.11947/j.JGGS.2022.0310},
doi = {10.11947/j.JGGS.2022.0310},
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.}
}