A Depth-based approach for 3D dynamic gesture recognition

Hajar Hiyadi 1, 2 Fakhr-Eddine Ababsa 1 Christophe Montagne 1 El Houssine Bouyakhf 2 Fakhita Regragui 2
1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 LIMIARF - Laboratoire d'Informatique, Mathématiques appliquées, Intelligence Artificielle et Reconnaissance de Formes
Abstract : In this paper we propose a recognition technique of 3D dynamic gesture for human robot interaction (HRI) based on depth information provided by Kinect sensor. The body is tracked using the skeleton algorithm provided by the Kinect SDK. The main idea of this work is to compute the angles of the upper body joints which are active when executing gesture. The variation of these angles are used as inputs of Hidden Markov Models (HMM) in order to recognize the dynamic gestures. Results demonstrate the robustness of our method against environmental conditions such as illumination changes and scene complexity due to using depth information only
Keywords : Hidden Markov Models Depth image 3D gesture recognition Gesture tracking
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Conference papers
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  • HAL Id : hal-01177438, version 1

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UNIV-EVRY | IBISC | IBISC-IRA2 | UNIV-PARIS-SACLAY

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Hajar Hiyadi, Fakhr-Eddine Ababsa, Christophe Montagne, El Houssine Bouyakhf, Fakhita Regragui. A Depth-based approach for 3D dynamic gesture recognition. 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2015), Jul 2015, Colmar, France. pp.103--110. ⟨hal-01177438⟩

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