Title:	Kinect-based gait recognition using sequences of the most relevant joint relative angles
Authors:	Ahmed, Faisal Polash Paul, Padma Gavrilova, Marina L.
Citation:	Journal of WSCG. 2015, vol. 23, no. 1, p. 147-156.
Issue Date:	2015
Publisher:	Václav Skala - UNION Agency
Document type:	článek article
URI:	http://wscg.zcu.cz/WSCG2015/!_2015_Journal_WSCG-No-2.pdf http://hdl.handle.net/11025/17149
ISSN:	1213–6972 (hardcopy) 1213–6980 (CD-ROM) 1213–6964 (online)
Keywords:	rozpoznávání chůze;Kinect v2;JRA;DTW-kernel;analýza pohybu
Keywords in different language:	gait recognition;Kinect v2;JRA;DTW-kernel;motion analysis
Abstract in different language:	This paper introduces a new 3D skeleton-based gait recognition method for motion captured by a low-cost consumer level camera, namely the Kinect. We propose a new representation of human gait signature based on the spatio-temporal changes in relative angles among different skeletal joints with respect to a reference point. A sequence of joint relative angles (JRA) between two skeletal joints, computed over a complete gait cycle, comprises an intuitive representation of the relative motion patterns of the involved joints. JRA sequences originated from different joint pairs are then evaluated to find the most relevant JRAs for gait description. We also introduce a new dynamic time warping (DTW)-based kernel that takes the collection of the most relevant JRA sequences from the train and test samples and computes a dissimilarity measure. The use of DTW in the proposed kernel makes it robust in respect to variable walking speed and thus eliminates the need of resampling to obtain equal-length feature vectors. The performance of the proposed method was evaluated using a Kinect skeletal gait database. Experimental results show that the proposed method can more effectively represent and recognize human gait, as compared against some other Kinect-based gait recognition methods.
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	Volume 23, Number 2 (2015)

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