Real-time sensor-fusion based indoor localization for mobile Augmented Reality

Jinki Jung, Suwon Lee, Hyeopwoo Lee, Hyun S. Yang, Luis Weruaga, Jamal Zemerly

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

1 Scopus citations

Abstract

In this paper we propose a sensor fusion based indoor localization method for mobile Augmented Reality (MAR). The aim of this research is to provide fine-tuning of the line feature based localization to accuracy of centimeter-level by exploring multi-modality of a mobile device. In order to match with line features from the captured scene and the given floor map, a line-based indoor scene analysis is proposed with Manhattan world assumption. An efficient pairwise line matching method using corresponding compass sensor data is presented to yield accurate localization and registration for MAR. Experimental results demonstrated that the proposed method is able to provide real-time performance and robustness in indoor environment.

Original languageBritish English
Title of host publicationProceedings of the 2014 International Conference on Virtual Systems and Multimedia, VSMM 2014
EditorsSarah Kenderdine, Harold Thwaites, Jeffrey Shaw
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages184-191
Number of pages8
ISBN (Electronic)9781479972272
DOIs
StatePublished - 2014
Event20th International Conference on Virtual Systems and Multimedia, VSMM 2014 - Hong Kong, Hong Kong
Duration: 9 Dec 201412 Dec 2014

Publication series

NameProceedings of the 2014 International Conference on Virtual Systems and Multimedia, VSMM 2014

Conference

Conference20th International Conference on Virtual Systems and Multimedia, VSMM 2014
Country/TerritoryHong Kong
CityHong Kong
Period9/12/1412/12/14

Keywords

  • indoor localization
  • mobile Augmented Reality
  • scene analysis
  • sensor-fusion method

Fingerprint

Dive into the research topics of 'Real-time sensor-fusion based indoor localization for mobile Augmented Reality'. Together they form a unique fingerprint.

Cite this