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Mobiceil: cost-free indoor localizer for office buildings

Published: 03 September 2018 Publication History

Abstract

Location awareness of people inside commercial establishments can help with occupancy-based dynamic energy management and indoor navigation. In this paper, we propose MobiCeil, a novel phone-based indoor localization technique. The proposed technique is offline, automated, and uses image captured from phone's camera to identify the unique ceiling structure of any particular location in the office building. The proposed method is based on these assumptions: (a) in office, employees tend to keep their phones lying on the table, and (b) the layout of ceiling landmarks in a portion of the ceiling structure (as captured by the phone's camera on the table) is unique. We validated these assumptions by checking the phone placement of 47 employees randomly at their cubicle or meeting room, and collecting ceiling layout data from 18 meeting rooms and 6 cubicles in an IT office building. To evaluate the performance of MobiCeil, we collected images of the ceiling as seen by the phone (front and back) camera in three different rotations of the phone placed on the table, to capture a total of 960 ceiling images. Our approach achieved an accuracy of 88.2% for identifying locations, with a low computation time of 2.8s per image.

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Cited By

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  • (2023)Depth Estimation Using Homographic Transformation2023 2nd International Conference on Smart Cities 4.010.1109/SmartCities4.056956.2023.10525722(391-395)Online publication date: 22-Oct-2023
  • (2020)A Comprehensive Survey of Indoor Localization Methods Based on Computer VisionSensors10.3390/s2009264120:9(2641)Online publication date: 6-May-2020

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cover image ACM Conferences
MobileHCI '18: Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services
September 2018
552 pages
ISBN:9781450358989
DOI:10.1145/3229434
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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Published: 03 September 2018

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Author Tags

  1. camera
  2. ceiling tracking
  3. computer vision
  4. indoor localization
  5. indoor navigation
  6. occupancy-based energy management
  7. office buildings
  8. smartphones
  9. workplaces

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Cited By

View all
  • (2023)Depth Estimation Using Homographic Transformation2023 2nd International Conference on Smart Cities 4.010.1109/SmartCities4.056956.2023.10525722(391-395)Online publication date: 22-Oct-2023
  • (2020)A Comprehensive Survey of Indoor Localization Methods Based on Computer VisionSensors10.3390/s2009264120:9(2641)Online publication date: 6-May-2020

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