Person Identification and Gender Recognition from Footstep Sound using Modulation Analysis

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2008-08-08

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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.

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This report is the final project of a student in ISR's 2008 Research Experiences for Undergraduates program.

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