Název:	Kinect-based gait recognition using sequences of the most relevant joint relative angles
Autoři:	Ahmed, Faisal Polash Paul, Padma Gavrilova, Marina L.
Citace zdrojového dokumentu:	Journal of WSCG. 2015, vol. 23, no. 1, p. 147-156.
Datum vydání:	2015
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	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)
Klíčová slova:	rozpoznávání chůze;Kinect v2;JRA;DTW-kernel;analýza pohybu
Klíčová slova v dalším jazyce:	gait recognition;Kinect v2;JRA;DTW-kernel;motion analysis
Abstrakt v dalším jazyce:	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.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	Volume 23, Number 2 (2015)

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