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demonstration

Demo: iMoon: Using Smartphones for Image-based Indoor Navigation

Published: 01 November 2015 Publication History

Abstract

The indoor location market is growing rapidly. However, fine-grained and up-to-date indoor maps are rarely available, and the existing indoor localization and navigation services mostly require extra infrastructures to provide accurate locations. In this demonstration we show iMoon, an indoor navigation system that provides indoor mapping, localization and navigation services using photos and sensor data collected from widely available mobile devices. The demonstration leverages a cohesive suite of computer vision, mobile sensing, and wireless networking techniques.

References

[1]
J. Dong, Y. Xiao, M. Noreikis, Z. Ou, and A. Yla-Jaaski. imoon: Using smartphones for image-based indoor navigation. In Proceedings of SenSys '15, Seoul, Korea.
[2]
J.-M. Frahm, P. Fite-Georgel, D. Gallup, T. Johnson, R. Raguram, C. Wu, Y.-H. Jen, E. Dunn, B. Clipp, S. Lazebnik, and M. Pollefeys. Building rome on a cloudless day. In Proc. of ECCV'10, pages 368--381, Berlin, Heidelberg.
[3]
N. Snavely, I. Simon, M. Goesele, R. Szeliski, and S. Seitz. Scene reconstruction and visualization from community photo collections. Proc. of the IEEE, 98(8):1370--1390, 2010.

Cited By

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  • (2018)Fusion of wifi and vision based on smart devices for indoor localizationProceedings of the 16th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry10.1145/3284398.3284401(1-8)Online publication date: 2-Dec-2018

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Published In

cover image ACM Conferences
SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
November 2015
526 pages
ISBN:9781450336314
DOI:10.1145/2809695
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2015

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Author Tags

  1. 3D modelling
  2. indoor mapping
  3. indoor navigation
  4. mobile crowdsensing

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  • Demonstration

Funding Sources

  • Academy of Finland

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Acceptance Rates

SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;
Overall Acceptance Rate 174 of 867 submissions, 20%

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SenSys '24

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View all
  • (2018)Fusion of wifi and vision based on smart devices for indoor localizationProceedings of the 16th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry10.1145/3284398.3284401(1-8)Online publication date: 2-Dec-2018

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