Person Identification and Gender Recognition from Footstep Sound using Modulation Analysis

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