Paper
2 June 2011 Classification of people walking and jogging/running using multimodal sensor signatures
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Abstract
In this paper, we address the issues involved in detecting and classifying people walking and jogging/running. When the people are walking, sensors observe the signals for a longer period compared to the case in which people are jogging. To identify fast-moving people, one must make the decision based on the few telltale signals generated by a person jogging: a higher impact of a foot on the ground, which can be monitored by seismic sensors; the panting noise observed through an acoustic sensor; or a higher Doppler from an ultrasonic sensor, to name few. First, we investigate the phenomenology associated with seismic signals generated by a person walking and jogging. Then, we analyze ultrasonic signatures to distinguish the characteristics associated with them. Finally, we develop the algorithms to detect and classify people walking and jogging. These algorithms are tested on data collected in an outdoor environment.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thyagaraju Damarla and James Sabatier "Classification of people walking and jogging/running using multimodal sensor signatures", Proc. SPIE 8019, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense X, 80190N (2 June 2011); https://doi.org/10.1117/12.883246
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Ultrasonics

Doppler effect

Acoustics

Algorithm development

Signal detection

Electric field sensors

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