MilliSonic: Pushing the Limits of Acoustic Motion Tracking

Hand Gesture RecognitionSocial & Collaborative VRContext-Aware ComputingSoftware Engineers & DevelopersUI/UX DesignersAI/ML Researchers & Engineers

Recent years have seen interest in device tracking and localization using acoustic signals. State-of-the-art acoustic motion tracking systems however do not achieve millimeter accuracy and require large separation between microphones and speakers, and as a result, do not meet the requirements for many VR/AR applications. Further, tracking multiple concurrent acoustic transmissions from VR devices today requires sacrificing accuracy or frame rate. We present MilliSonic, a novel system that pushes the limits of acoustic based motion tracking. Our core contribution is a novel localization algorithm that can provably achieve sub-millimeter 1D tracking accuracy in the presence of multipath, while using only a single beacon with a small 4-microphone array.Further, MilliSonic enables concurrent tracking of up to four smartphones without reducing frame rate or accuracy. Our evaluation shows that MilliSonic achieves 0.7mm median 1D accuracy and a 2.6mm median 3D accuracy for smartphones, which is 5x more accurate than state-of-the-art systems. MilliSonic enables two previously infeasible interaction applications: a) 3D tracking of VR headsets using the smartphone as a beacon and b) fine-grained 3D tracking for the Google Cardboard VR system using a small microphone array.

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https://hci.top/en/papers/chi/5092/2019

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Source
CHI
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Year
2019
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2 authors
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Subtopics
Hand Gesture Recognition, Social & Collaborative VR, Context-Aware Computing
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Software Engineers & Developers, UI/UX Designers, AI/ML Researchers & Engineers
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Abstract only
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