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  • Motion_Coupling_of_Earable_Devices_in_Camera_View___MUM2020_Note

    Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MUM 2020: 19th International Conference on Mobile and Ubiquitous Multimedia 2020 https://dl.acm.org/doi/proceedings/10.1145/3428361

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Motion Coupling of Earable Devices in Camera View

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Abstract

Earables, earphones augmented with inertial sensors and real-time data accessibility, provide the opportunity for private audio channels in public settings. One of the main challenges of achieving this goal is to correctly associate which device belongs to which user without prior information. In this paper, we explore how motion of an earable, as measured by the on-board accelerometer, can be correlated against detected faces from a webcam to accurately match which user is wearing the device. We conduct a data collection and explore which type of user movement can be accurately detected using this approach, and investigate how varying the speed of the movement affects detection rates. Our results show that the approach achieves greater detection results for faster movements, and that it can differentiate the same movement across different participants with a detection rate of 86%, increasing to 92% when differentiating a movement against others.

Bibliographic note

© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MUM 2020: 19th International Conference on Mobile and Ubiquitous Multimedia 2020 https://dl.acm.org/doi/proceedings/10.1145/3428361