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

  • Authors:

  • Zheng Sun;Aveek Purohit;Shijia Pan;Frank Mokaya;Raja Bose;Pei Zhang

  • Affiliations:

  • Carnegie Mellon University;Carnegie Mellon University;University of Science and Technology of China;Carnegie Mellon University;Nokia Research Center, Palo Alto;Carnegie Mellon University

  • Venue:
  • Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
  • Year:
  • 2012

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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.