NDLI: Abnormal gait detection with RGB-D devices using joint motion history features

Content Provider	IEEE Xplore Digital Library
Author	Chaaraoui, A.A. Padilla-Lopez, J.R. Florez-Revuelta, F.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Technol., Univ. of Alicante, Alicante, Spain (Chaaraoui, A.A.; Padilla-Lopez, J.R.) \|\| Fac. of Sci., Eng. & Comput., Kingston Univ., Kingston upon Thames, UK (Florez-Revuelta, F.)
Abstract	Human gait has become of special interest to health professionals and researchers in recent years, not only due to its relation to a person's quality of life and personal autonomy, but also due to the involved cognitive process, since deviation from normal gait patterns can also be associated to neurological diseases. Vision-based abnormal gait detection can provide support to current human gait analysis procedures providing quantitative and objective metrics that can assist the evaluation of the geriatrician, while at the same time providing technical advantages, such as low intrusiveness and simplified setups. Furthermore, recent advances in RGB-D devices allow to provide low-cost solutions for 3D human body motion analysis. In this sense, this work presents a method for abnormal gait detection relying on skeletal pose representation based on depth data. A novel spatio-temporal feature is presented that provides a representation of a set of consecutive skeletons based on the 3D location of the skeletal joints and the motion's age. The corresponding feature sequences are learned using a machine learning method, namely BagOfKeyPoses. Experimentation with different datasets and evaluation methods shows that reliable detection of abnormal gait is obtained and, at the same time, an outstandingly high temporal performance is provided.
Starting Page	1
Ending Page	6
File Size	579569
Page Count	6
File Format	PDF
ISBN	9781479960262
DOI	10.1109/FG.2015.7284881
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-04
Publisher Place	Slovenia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Joints Feature extraction Three-dimensional displays History Estimation Cameras
Content Type	Text
Resource Type	Article

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