Analysis of spatial domain information for footstep recognition
Entity
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesPublisher
The Institution of Engineering and TechnologyDate
2011-11-01Citation
10.1049/iet-cvi.2010.0189
IET Computer Vision 5.6 (2011): 380–388
ISSN
1751-9632 (print); 1751-9640 (online)DOI
10.1049/iet-cvi.2010.0189Funded by
Ruben Vera-Rodriguez, Julian Fierrez and Javier Ortega Garcia are supported by projects Contexts (S2009/TIC-1485), Bio-Challenge (TEC2009-11186), TeraSense (CSD2008-00068) and ‘Catedra UAM-Telefonica’.Project
Comunidad de Madrid. S2009/TIC-1485/CONTEXTSEditor's Version
http://dx.doi.org/10.1049/iet-cvi.2010.0189Subjects
Biometrics; Equal error rate; Footstep database; Footstep recognition; Footstep signals; High heels; Support vector machines; Signal processing; Sensors; Principal component analysis; Informática; TelecomunicacionesNote
This paper is a postprint of a paper submitted to and accepted for publication in Computer Vision, IET and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital LibraryRights
© The Institution of Engineering and Technology 2011Abstract
This study reports an experimental analysis of footsteps as a biometric. The focus here is on information extracted from the spatial domain of signals collected from an array of piezoelectric sensors. Results are related to the largest footstep database collected to date, with almost 20 000 valid footstep signals and more than 120 persons. A novel feature approach is proposed, obtaining three-dimensional images of the distribution of the footstep pressure along the spatial course. Experimental work is based on a verification mode with a holistic approach based on principal component analysis and support vector machines, achieving results in the range of 6-10% equal error rate (EER) depending on the experimental conditions of quantity of data used in the client models (200 and 40 signals per model, respectively). Also, this study includes the analysis of two interesting factors affecting footstep signals and especially spatial domain features, namely, sensor density and the special case of high heels.
Files in this item
Google Scholar:Vera Rodríguez, Rubén
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Mason, John S. D.
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Fiérrez Aguilar, Julián
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Ortega García, Javier
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