IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Robust Gait-Based Person Identification against Walking Speed Variations
Muhammad Rasyid AQMARKoichi SHINODASadaoki FURUI
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2012 Volume E95.D Issue 2 Pages 668-676


Variations in walking speed have a strong impact on gait-based person identification. We propose a method that is robust against walking-speed variations. It is based on a combination of cubic higher-order local auto-correlation (CHLAC), gait silhouette-based principal component analysis (GSP), and a statistical framework using hidden Markov models (HMMs). The CHLAC features capture the within-phase spatio-temporal characteristics of each individual, the GSP features retain more shape/phase information for better gait sequence alignment, and the HMMs classify the ID of each gait even when walking speed changes nonlinearly. We compared the performance of our method with other conventional methods using five different databases, SOTON, USF-NIST, CMU-MoBo, TokyoTech A and TokyoTech B. The proposed method was equal to or better than the others when the speed did not change greatly, and it was significantly better when the speed varied across and within a gait sequence.

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© 2012 The Institute of Electronics, Information and Communication Engineers
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