Gait recognition using linear time normalization

Authors:
Nikolaos V. Boulgouris;Konstantinos N. Plataniotis;Dimitrios Hatzinakos
Affiliations:
Department of Electronic Engineering, Division of Engineering, King's College London, Strand, London WC2R 2LS, UK;The Edward Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Canada;The Edward Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Canada
Venue:
Pattern Recognition
Year:
2006

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Abstract

We present a novel system for gait recognition. Identity recognition and verification are based on the matching of linearly time-normalized gait walking cycles. A novel feature extraction process is also proposed for the transformation of human silhouettes into low-dimensional feature vectors consisting of average pixel distances from the center of the silhouette. By using the best-performing of the proposed methodologies, improvements of 8-20% in recognition and verification performance are seen in comparison to other known methodologies on the ''Gait Challenge'' database.