@inproceedings{70bed5278ebd4b5daebc100353f23157,
title = "3DVPS: A 3D point cloud-based visual positioning system",
abstract = "Visual positioning is a critical function in applications such as navigation and extended reality experiences. Recently, deep learning technologies, especially classification, had been implemented on the positioning task. However, to acquire a comprehensive positioning dataset and produce a high-performance neural network model is challenging. In this article, we propose to solve the issue by projecting training images from auto-generated 3D point cloud maps. By utilizing branch convolutional neural network (B-CNN) model, the 'zoom-in' equivalent property results in favorable positioning accuracy and successful real-time implementation.",
author = "Chen, {Yu Hsiu} and Chen, {Yen Yu} and Chen, {Ming Chien} and Huang, {Chih Wei}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Consumer Electronics, ICCE 2020 ; Conference date: 04-01-2020 Through 06-01-2020",
year = "2020",
month = jan,
doi = "10.1109/ICCE46568.2020.9043071",
language = "???core.languages.en_GB???",
series = "Digest of Technical Papers - IEEE International Conference on Consumer Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Consumer Electronics, ICCE 2020",
}