2014 · 25 citations · 27 references
ComputingAutonomous SystemsMobile ComputingMovement AnalysisSensor FusionMobile Human-computer InteractionMobile SensingMotion AnalysisMotion EstimationOutdoor LocalizationTracking SystemsFramesLocation TrackingMobility TrackingMulti-user InteractionReal-time TrackingReal-time Tracking SystemsSmartphonesUser Activity Recognition
In this work we design and develop Montage for real-time multi-user formation tracking and localization by off-the-shelf smartphones. Montage achieves submeter-level tracking accuracy by integrating temporal and spatial constraints from user movement vector estimation and distance measuring. In Montage we designed a suite of novel techniques to surmount a variety of challenges in real-time tracking, without infrastructure and fingerprints, and without any a priori user-specific (e.g., stride-length and phone-placement) or site-specific (e.g., digitalized map) knowledge. We implemented, deployed and evaluated Montage in both outdoor and indoor environment. Our experimental results (847 traces from 15 users) show that the stride-length estimated by Montage over all users has error within 9cm, and the moving-direction estimated by Montage is within 20 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> . For realtime tracking, Montage provides meter-second-level formation tracking accuracy with off-the-shelf mobile phones.
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