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Proceedings Paper

Time-domain classification of humans using seismic sensors
Author(s): Sean Schumer
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Paper Abstract

Methods of human classification and direction of travel are developed for the purpose of being embedded in low-power, low-cost microprocessors. Techniques are explored for classifying an impulsive set of events in a seismic field as being either human or non-human based on information extrapolated from time-domain data of geophones. Additionally, a method of time domain direction of travel determination is explored. As a target is traversing the field of detection, simple impulse detection techniques determine seismic activities that are of interest. By recreating the time-domain signal as an average energy over time, the frequency of footstep of the target can be determined after a human has left the field by using post processing techniques, even when multiple targets are present. An autocorrelation of the energy averaged signal will yield an output that can be used to easily determine the most dominant frequency of the observed series of impulsive events. This method is capable of classifying humans under certain conditions at a rate of up to 98% with a varying rate of rejection for different types of animals and environmental factors. The technique can be easily integrated to work in conjunction with other modalities for an increase in classifier confidence.

Paper Details

Date Published: 7 May 2010
PDF: 11 pages
Proc. SPIE 7693, Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 769311 (7 May 2010); doi: 10.1117/12.850092
Show Author Affiliations
Sean Schumer, U.S. Army Research, Development and Engineering Command (United States)


Published in SPIE Proceedings Vol. 7693:
Unattended Ground, Sea, and Air Sensor Technologies and Applications XII
Edward M. Carapezza, Editor(s)

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