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    Person Identification and Gender Recognition from Footstep Sound using Modulation Analysis

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    No. of downloads: 4123

    Date
    2008-08-08
    Author
    DeLoney, Chasity
    Advisor
    Mesgarani, Nima
    Fritz, Jonathan
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    Abstract
    We describe a person identification system that is based on classifying the sound of the footstep. The classification is done on the spectrotemporal modulations of sound that are estimated using a model of auditory processing. We describe how different footsteps form a unique footprint in the spectrotemporal modulation domain and how this representation captures the user specific signatures. Using this representation, we achieved higher than 60% accuracy in identifying 9 people with three different shoes and two floors. The study demonstrates the efficacy of the spectrotemporal features in the tasks examined.
    Notes
    This report is the final project of a student in ISR's 2008 Research Experiences for Undergraduates program.
    URI
    http://hdl.handle.net/1903/8379
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