3DVPS: A 3D point cloud-based visual positioning system

Yu Hsiu Chen, Yen Yu Chen, Ming Chien Chen, Chih Wei Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics, ICCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728151861
DOIs
StatePublished - Jan 2020
Event2020 IEEE International Conference on Consumer Electronics, ICCE 2020 - Las Vegas, United States
Duration: 4 Jan 20206 Jan 2020

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2020-January
ISSN (Print)0747-668X

Conference

Conference2020 IEEE International Conference on Consumer Electronics, ICCE 2020
Country/TerritoryUnited States
CityLas Vegas
Period4/01/206/01/20

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