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Gait recognition using linear time normalization

Research output: Contribution to journalArticlepeer-review

N V Boulgouris, K N Plataniotis, D Hatzinakos

Original languageEnglish
Pages (from-to)969 - 979
Number of pages11
Issue number5
PublishedMay 2006

King's Authors


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. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved

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