research-article

Image-based indoor positioning system: fast image matching using omnidirectional panoramic images

Authors:

Toshihiko Yamasaki,

Kiyoharu AizawaAuthors Info & Claims

MPVA '10: Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis

Pages 1 - 4

https://doi.org/10.1145/1878039.1878041

Published: 29 October 2010 Publication History

Abstract

In this paper, we developed an image-based indoor localization system using omnidirectional panoramic images to which location information is added. By the combination of the robust image matching by PCA-SIFT and fast nearest neighbor search algorithm based on Locality Sensitive Hashing (LSH), our system can estimate users' positions with high accuracy and in a short time. To improve the precision, we introduced the "confidence" of the image matching results. We conducted experiments at the Railway Museum and we obtained 426 omnidirectional panoramic reference images and 1067 supplemental images for image matching. Experimental results using 126 test images demonstrated that the location detection accuracy is above 90% with about 2.2s of processing time.

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Cited By

Yu ZYe SLiu CJin RXia PYan K(2024)Globally Optimal Relative Pose and Scale Estimation from Only Image Correspondences with Known Vertical DirectionISPRS International Journal of Geo-Information10.3390/ijgi1307024613:7(246)Online publication date: 9-Jul-2024
https://doi.org/10.3390/ijgi13070246
Li YKambhamettu RHu YZhang R(2022)ImPos: An Image-Based Indoor Positioning System2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49033.2022.9700699(144-150)Online publication date: 8-Jan-2022
https://doi.org/10.1109/CCNC49033.2022.9700699
Ssekidde PSteven Eyobu OHan DOyana T(2021)Augmented CWT Features for Deep Learning-Based Indoor Localization Using WiFi RSSI DataApplied Sciences10.3390/app1104180611:4(1806)Online publication date: 18-Feb-2021
https://doi.org/10.3390/app11041806
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Index Terms

Image-based indoor positioning system: fast image matching using omnidirectional panoramic images
1. Information systems
  1. Information systems applications
    1. Multimedia information systems

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cover image ACM Conferences

MPVA '10: Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis

October 2010

68 pages

ISBN:9781450301671

DOI:10.1145/1878039

General Chairs:
Hamid Aghajan
University of Stanford, USA
,
Marco Cristani
University of Verona, Italy
,
Vittorio Murino
University of Verona, Italy
,
Nicu Manuel Sebe
University of Trento, Italy

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2010

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MM '10: ACM Multimedia Conference

October 29, 2010

Firenze, Italy

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Cited By

Yu ZYe SLiu CJin RXia PYan K(2024)Globally Optimal Relative Pose and Scale Estimation from Only Image Correspondences with Known Vertical DirectionISPRS International Journal of Geo-Information10.3390/ijgi1307024613:7(246)Online publication date: 9-Jul-2024
https://doi.org/10.3390/ijgi13070246
Li YKambhamettu RHu YZhang R(2022)ImPos: An Image-Based Indoor Positioning System2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49033.2022.9700699(144-150)Online publication date: 8-Jan-2022
https://doi.org/10.1109/CCNC49033.2022.9700699
Ssekidde PSteven Eyobu OHan DOyana T(2021)Augmented CWT Features for Deep Learning-Based Indoor Localization Using WiFi RSSI DataApplied Sciences10.3390/app1104180611:4(1806)Online publication date: 18-Feb-2021
https://doi.org/10.3390/app11041806
Karkar AAl-Maadeed SKunhoth JBouridane A(2021)CamNav: a computer-vision indoor navigation systemThe Journal of Supercomputing10.1007/s11227-020-03568-5Online publication date: 8-Jan-2021
https://doi.org/10.1007/s11227-020-03568-5
Shahid EArain Q(2021)Indoor positioning: “an image-based crowdsource machine learning approach”Multimedia Tools and Applications10.1007/s11042-021-10906-zOnline publication date: 29-Apr-2021
https://doi.org/10.1007/s11042-021-10906-z
Kubíčková HJedlička KFiala RBeran D(2020)Indoor Positioning Using PnP Problem on Mobile Phone ImagesISPRS International Journal of Geo-Information10.3390/ijgi90603689:6(368)Online publication date: 2-Jun-2020
https://doi.org/10.3390/ijgi9060368
Kunhoth JKarkar AAl-Maadeed SAl-Ali A(2020)Indoor positioning and wayfinding systems: a surveyHuman-centric Computing and Information Sciences10.1186/s13673-020-00222-010:1Online publication date: 2-May-2020
https://doi.org/10.1186/s13673-020-00222-0
YASHIRO THIRAYAMA HSAKAMURA K(2020)An Indoor Localization Service using 360 Degree Spherical Camera2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)10.1109/LifeTech48969.2020.1570617174(17-18)Online publication date: Mar-2020
https://doi.org/10.1109/LifeTech48969.2020.1570617174
Yang SMa LJia SQin D(2020)An Improved Vision-Based Indoor Positioning MethodIEEE Access10.1109/ACCESS.2020.29689588(26941-26949)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2968958
Alhomayani FMahoor M(2020)Deep learning methods for fingerprint-based indoor positioning: a reviewJournal of Location Based Services10.1080/17489725.2020.1817582(1-72)Online publication date: 14-Sep-2020
https://doi.org/10.1080/17489725.2020.1817582
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