Vision-based Context and Height Estimation for 3D Indoor Location

B. Kazemipur, Z. Syed, J. Georgy, N. El-Sheimy

Abstract: Today’s smartphones are powerful devices whose continually increasing processing power and wide array of sensors make them well suited for use as personal navigation devices. In the absence of information from the Global Navigation Satellite System (GNSS), the onboard inertial sensors can be used to provide a relative navigation solution. However, these onboard inertial sensors suffer from the effects of different sensor errors which cause the inertial-only solution to deteriorate rapidly. As such, there is a need to constrain the inertial positioning solution when long term navigation is needed. GNSS positions and velocities, and WiFi positions are the most important forms of updates available for the inertial solution. However, updates from these two sources depend on external signals and may not always be available. A rich source of information about the outside world can be obtained using the device’s camera. Nearly all devices have at least one camera which has thus far been largely neglected as a navigation aid for these mobile devices. There are many indoor scenarios that require accurate height estimates. Traditionally, barometers have been used to provide height information. However, not all mobile devices that are equipped with inertial sensors are also equipped with a barometer. As nearly all devices are equipped with at least one camera, it is our aim to use information from the camera to aid the inertial-only solution with appropriate height estimates. Different pattern analysis techniques are used to identify the different scenarios. The results are presented for the following common use cases: (1) single floor texting mode, (2) stairs texting mode, (3) single floor calling mode, (4) stairs calling mode, and (5) fidgeting the phone while standing still on a single floor (i.e. “fidgeting”). For each of these use cases, first the context will be determined and then the relevant information will be used to calculate the height accordingly. This work is patent pending.
Published in: Proceedings of IEEE/ION PLANS 2014
May 5 - 8, 2014
Hyatt Regency Hotel
Monterey, CA
Pages: 1336 - 1342
Cite this article: Kazemipur, B., Syed, Z., Georgy, J., El-Sheimy, N., "Vision-based Context and Height Estimation for 3D Indoor Location," Proceedings of IEEE/ION PLANS 2014, Monterey, CA, May 2014, pp. 1336-1342.
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