research-article

Polaris: getting accurate indoor orientations for mobile devices using ubiquitous visual patterns on ceilings

Authors:

Pei ZhangAuthors Info & Claims

HotMobile '12: Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications

Article No.: 14, Pages 1 - 6

https://doi.org/10.1145/2162081.2162101

Published: 28 February 2012 Publication History

Abstract

Ubiquitous computing applications commonly use digital compass sensors to obtain orientation of a device relative to the magnetic north of the earth. However, these compass readings are always prone to significant errors in indoor environments due to presence of metallic objects in close proximity. Such errors can adversely affect the performance and quality of user experience of the applications utilizing digital compass sensors.

In this paper, we propose Polaris, a novel approach to provide reliable orientation information for mobile devices in indoor environments. Polaris achieves this by aggregating pictures of the ceiling of an indoor environment and applies computer vision based pattern matching techniques to utilize them as orientation references for correcting digital compass readings. To show the feasibility of the Polaris system, we implemented the Polaris system on mobile devices, and field tested the system in multiple office buildings. Our results show that Polaris achieves 4.5° average orientation accuracy, which is about 3.5 times better than what can be achieved through sole use of raw digital compass readings.

References

[1]

M. Azizyan, I. Constandache, and R. Roy Choudhury. SurroundSense: Mobile Phone Localization via Ambience Fingerprinting. In Proceedings of the 15th Annual International Conference on Mobile Computing and Networking, pages 261--272. ACM, 2009.

Digital Library

[2]

D. Ballard. Generalizing the Hough Transform to Detect Arbitrary Shapes. Pattern Recognition, 13(2):111--122, 1981.

[3]

J. Canny. A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6):679--698, Nov. 1986.

Digital Library

[4]

T. Choudhury, G. Borriello, and S. Consolvo. The Mobile Sensing Platform: An Embedded Activity Recognition System. IEEE Pervasive, pages 32--41, 2008.

Digital Library

[5]

G. Essl and M. Rohs. SHAMUS: A Sensor-Based Integrated Mobile Phone Instrument. In Proceedings of the International Computer Music Conference ICMC (2007), volume 40, page 50. Citeseer, 2007.

[6]

D. Gusenbauer, C. Isert, and J. Krosche. Self-Contained Indoor Positioning on Off-The-Shelf Mobile Devices. In Proceedings of the 2010 International Conference on Indoor Positioning and Indoor Navigation, number September, pages 1--9. IEEE, 2010.

[7]

B. Hoff and R. Azuma. Autocalibration of An Electronic Compass In An Outdoor Augmented Reality System. Proceedings IEEE and ACM International Symposium on Augmented Reality (ISAR 2000), 2000(October):159--164, 2000.

[8]

M. Hoshino, Y. Gunji, S. Oho, and K. Takano. A Kalman Filter to Estimate Direction for Automotive Navigation. In Proceedings of the 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems, pages 145--150. IEEE, 1996.

[9]

X. Jin and C. H. Davis. Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information. EURASIP Journal on Advances in Signal Processing, 2005(14):2196--2206, Jan. 2005.

Digital Library

[10]

T. King, S. Kopf, T. Haenselmann, C. Lubberger, and W. Effelsberg. Compass: A Probabilistic Indoor Positioning System Based on 802.11 And Digital Compasses. In Proceedings of the 1st International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization, number September, pages 34--40. ACM, 2006.

Digital Library

[11]

W. Piekarski and B. Thomas. ARQuake: The Outdoor Augmented Reality Gaming System. Communications of the ACM, 45(1):36--38, 2002.

Digital Library

[12]

D. Spinellis. Position-Annotated Photographs: A Geotemporal Web. IEEE Pervasive Computing, 2(2):72--79, Apr. 2003.

Digital Library

[13]

P. Steadman. Why Are Most Buildings Rectangular? Architectural Research Quarterly, 10(02):119--130, June 2006.

[14]

M. Youssef, M. Yosef, and M. El-Derini. GAC: Energy-Efficient Hybrid GPS-accelerometer-compass GSM Localization. In Proceedings of the IEEE Globecom 2010, 2010.

[15]

Y.T.Kim. Contrast Enhancement Using Brightness Preserving Bi-histogram Equalization. IEEE Transactions on Consumer Electronics, 43(1):1--8, 1997.

Digital Library

Cited By

Sathya GGayathiri ASumitra PSathiya MSabitha SGhinea G(2024)A Bright Future for AR and VR on MobileUbiquitous Computing and Technological Innovation for Universal Healthcare10.4018/979-8-3693-2268-0.ch017(388-406)Online publication date: 6-Aug-2024
https://doi.org/10.4018/979-8-3693-2268-0.ch017
Hashem OAlkiek KYoussef MHarras K(2021)Leveraging Earables for Natural Calibration-Free Multi-Device Identification in Smart EnvironmentsProceedings of the 22nd International Workshop on Mobile Computing Systems and Applications10.1145/3446382.3448653(92-98)Online publication date: 24-Feb-2021
https://dl.acm.org/doi/10.1145/3446382.3448653
Chen XRuiz CZeng SGao LPurohit ACarpin SZhang P(2020)H-DrunkWalkACM Transactions on Sensor Networks10.1145/338209416:2(1-27)Online publication date: 17-Apr-2020
https://dl.acm.org/doi/10.1145/3382094
Show More Cited By

Index Terms

Polaris: getting accurate indoor orientations for mobile devices using ubiquitous visual patterns on ceilings
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems

Recommendations

Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing
UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

Heading information becomes widely used in ubiquitous computing applications for mobile devices. Digital magnetometers, also known as geomagnetic field sensors, provide absolute device headings relative to the earth's magnetic north. However, ...
Shuriken: User Grouping and Data Transfer for Collaborative Shopping and Offline Meetings Based on Inter-Device Relative Positioning
CSCW'15 Companion: Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing

We present Shuriken, a method for user grouping and data transfer based on relative position estimates of smart devices that are in close proximity. The relative positions are then used for identifying the recipient of transferred data by performing a ...
FM radio for indoor localization with spontaneous recalibration

The position of mobile users has become highly important information in pervasive computing environments. Indoor localization systems based on Wi-Fi signal strength fingerprinting techniques are widely used in office buildings with an existing Wi-Fi ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

HotMobile '12: Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications

February 2012

92 pages

ISBN:9781450312073

DOI:10.1145/2162081

General Chair:
Gaetano Borriello
University of Washington
,
Program Chair:
Rajesh Krishna Balan
Singapore Management University, SG

Copyright © 2012 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]

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 February 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

HotMobile '12

Sponsor:

SIGMOBILE

HotMobile '12: 13th Workshop on Mobile Computing Systems and Applications

February 28 - 29, 2012

California, San Diego

Acceptance Rates

HotMobile '12 Paper Acceptance Rate 14 of 68 submissions, 21%;

Overall Acceptance Rate 96 of 345 submissions, 28%

Upcoming Conference

HOTMOBILE '25

Sponsor:
sigmobile

The 26th International Workshop on Mobile Computing Systems and Applications

February 26 - 27, 2025

La Quinta , CA , USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

19
Total Citations
View Citations
219
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 13 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Sathya GGayathiri ASumitra PSathiya MSabitha SGhinea G(2024)A Bright Future for AR and VR on MobileUbiquitous Computing and Technological Innovation for Universal Healthcare10.4018/979-8-3693-2268-0.ch017(388-406)Online publication date: 6-Aug-2024
https://doi.org/10.4018/979-8-3693-2268-0.ch017
Hashem OAlkiek KYoussef MHarras K(2021)Leveraging Earables for Natural Calibration-Free Multi-Device Identification in Smart EnvironmentsProceedings of the 22nd International Workshop on Mobile Computing Systems and Applications10.1145/3446382.3448653(92-98)Online publication date: 24-Feb-2021
https://dl.acm.org/doi/10.1145/3446382.3448653
Chen XRuiz CZeng SGao LPurohit ACarpin SZhang P(2020)H-DrunkWalkACM Transactions on Sensor Networks10.1145/338209416:2(1-27)Online publication date: 17-Apr-2020
https://dl.acm.org/doi/10.1145/3382094
Liu SHe T(2017)SmartLightProceedings of the 15th ACM Conference on Embedded Network Sensor Systems10.1145/3131672.3131677(1-14)Online publication date: 6-Nov-2017
https://dl.acm.org/doi/10.1145/3131672.3131677
Chatzopoulos DBermejo CHuang ZHui P(2017)Mobile Augmented Reality Survey: From Where We Are to Where We GoIEEE Access10.1109/ACCESS.2017.26981645(6917-6950)Online publication date: 2017
https://doi.org/10.1109/ACCESS.2017.2698164
Mohssen NMomtaz RAly HYoussef M(2017)HumaineGeoinformatica10.1007/s10707-017-0300-721:3(519-548)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s10707-017-0300-7
Shen ZZheng XXie H(2016)Near Field Service Initiation via Vibration Channel2016 12th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN)10.1109/MSN.2016.083(450-453)Online publication date: Dec-2016
https://doi.org/10.1109/MSN.2016.083
Jiang ZHan JXi WZhao J(2016)NFV: Near Field Vibration Based Group Device PairingCollaborative Computing: Networking, Applications, and Worksharing10.1007/978-3-319-28910-6_12(129-140)Online publication date: 29-Jan-2016
https://doi.org/10.1007/978-3-319-28910-6_12
Chen XPurohit ADominguez CCarpin SZhang PSong JAbdelzaher TMascolo C(2015)DrunkWalkProceedings of the 13th ACM Conference on Embedded Networked Sensor Systems10.1145/2809695.2809724(295-308)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1145/2809695.2809724
Sharma PChakraborty DBanerjee NBanerjee DAgarwal SMittal S(2014)KARMA: Improving WiFi-based indoor localization with dynamic causality calibration2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SAHCN.2014.6990331(90-98)Online publication date: Jun-2014
https://doi.org/10.1109/SAHCN.2014.6990331
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents