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Real-Time Arm Gesture Recognition Using 3D Skeleton Joint Data

School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9, 157 73 Zografou, Greece
Institute of Informatics and Telecommunications, NCSR Demokritos, Neapoleos 10, 153 41 Ag. Paraskevi, Greece
Department of Computer Science and Telecommunications, University of Thessaly, 3rd km Old National Rd. Lamia-Athens, 351 00 Lamia, Greece
Department of Informatics, Ionian University, Platia Tsirigoti 7, 491 00 Corfu, Greece
Author to whom correspondence should be addressed.
Algorithms 2019, 12(5), 108;
Received: 29 March 2019 / Revised: 9 May 2019 / Accepted: 15 May 2019 / Published: 20 May 2019
(This article belongs to the Special Issue Mining Humanistic Data 2019)
PDF [1210 KB, uploaded 20 May 2019]


In this paper we present an approach towards real-time hand gesture recognition using the Kinect sensor, investigating several machine learning techniques. We propose a novel approach for feature extraction, using measurements on joints of the extracted skeletons. The proposed features extract angles and displacements of skeleton joints, as the latter move into a 3D space. We define a set of gestures and construct a real-life data set. We train gesture classifiers under the assumptions that they shall be applied and evaluated to both known and unknown users. Experimental results with 11 classification approaches prove the effectiveness and the potential of our approach both with the proposed dataset and also compared to state-of-the-art research works. View Full-Text
Keywords: gesture recognition; Kinect; skeleton joints; machine learning gesture recognition; Kinect; skeleton joints; machine learning

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Paraskevopoulos, G.; Spyrou, E.; Sgouropoulos, D.; Giannakopoulos, T.; Mylonas, P. Real-Time Arm Gesture Recognition Using 3D Skeleton Joint Data. Algorithms 2019, 12, 108.

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