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Title: Gait recognition using sub-vector quantisation technique

Authors: Neel K. Pandey; Waleed H. Abdulla; Zoran Salcic

Addresses: Department of Electrical Engineering and Trades, Faculty of Engineering and Trades, Manukau Institute of Technology, Private Bag 94006, Manukau 2241, Auckland, New Zealand ' Department of Electrical and Computer Engineering, The University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand ' Department of Electrical and Computer Engineering, The University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand

Abstract: Recognising people from their gait is a challenging problem in biometric research. In this paper, we address the problem of gait identification based on a novel approach of sub-vector quantisation (SVQ) technique. A silhouette-based algorithm is utilised to capture the spatial-temporal information of the gait. A sequence of temporally ordered outer contour widths of binarised silhouettes of a walking person represents the feature vectors set. The feature vectors are segmented into sub vectors and vector quantised independently to represent the gait signatures using low dimensional vectors. Dynamic time warping (DTW) technique is used for gait feature sequence matching. The proposed method is validated on several well known benchmarked databases as well as on our own database. The experimental results confirm the validity and robustness of the proposed SVQ method for gait recognition.

Keywords: gait recognition; vector quantisation; feature extraction; image sequence analysis; biometrics; gait identification; sub-vector quantisation; SVQ; silhouettes; walking persons; dynamic time warping; DTW; gait features; feature sequence matching.

DOI: 10.1504/IJMISSP.2013.052880

International Journal of Machine Intelligence and Sensory Signal Processing, 2013 Vol.1 No.1, pp.68 - 90

Available online: 19 Mar 2013 *

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