Angular features analysis for gait recognition


Wan Noorshahida Mohd Isa, and Rubita Sudirman, and Sheikh Hussain Sh-Salleh, (2005) Angular features analysis for gait recognition. In: 1st International Conference on Computers, Communications, & Signal Processing with Special Track on Biomedical Engineering, 2005. CCSP 2005. IEEE Xplore, 236 -238. ISBN 978-1-4244-0011-9

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Automatic gait recognition is an emergent biometrics identification system for recognizing humans by the way they walk. Its system is non-invasive because it operates from a distance via video cameras. The videos cum image frames are manually labeled to extract angular displacements of thigh's and lower leg's rotation, and foot flexion. The angular displacements data is analyzed using standard approach of Principal Component Analysis (PCA) and Canonical Analysis (CA). A cycle extraction procedure consisting of cubic-spline interpolation in SVR (Support Vector machine for Regression) and resampling within zero crossings is performed beforehand for an invariant analysis due to difference in walking speed of subjects. Combined dataset, is proposed for analyzing features that provide the most variations in gait recognition. Results have shown that the hip accounts for most variations among the three limbs' displacements data. Also, difference in temporal information of gait's signal does affect the recognition performance.

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 02 Dec 2013 03:28
Last Modified: 02 Dec 2013 03:28


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