A data-driven personnel detection scheme for indoor surveillance using seismic sensors

Arun Subramanian; Satish G. Iyengar; Kishan G. Mehrotra; Chilukuri K. Mohan; Pramod K. Varshney; Thyagaraju Damarla

doi:10.1117/12.820237

5 May 2009 A data-driven personnel detection scheme for indoor surveillance using seismic sensors

Arun Subramanian, Satish G. Iyengar, Kishan G. Mehrotra, Chilukuri K. Mohan, Pramod K. Varshney, Thyagaraju Damarla

Proceedings Volume 7333, Unattended Ground, Sea, and Air Sensor Technologies and Applications XI; 733315 (2009) https://doi.org/10.1117/12.820237
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

This paper describes experiments and analysis of seismic signals in addressing the problem of personnel detection for indoor surveillance. Data was collected using geophones to detect footsteps from walking and running in indoor environments such as hallways. Our analysis of the data shows the significant presence of nonlinearity, when tested using the surrogate data method. This necessitates the need for novel detector designs that are not based on linearity assumptions. We present one such method based on empirical mode decomposition (EMD) and functional data analysis (FDA) and evaluate its applicability on our collected dataset.

Citation Download Citation

Arun Subramanian, Satish G. Iyengar, Kishan G. Mehrotra, Chilukuri K. Mohan, Pramod K. Varshney, and Thyagaraju Damarla "A data-driven personnel detection scheme for indoor surveillance using seismic sensors", Proc. SPIE 7333, Unattended Ground, Sea, and Air Sensor Technologies and Applications XI, 733315 (5 May 2009); https://doi.org/10.1117/12.820237

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available