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Fast Learning-based Gesture Recognition for Child-robot Interactions Host Publication: Proceedings of ECAI㤔 workshop on Machine Learning for Interactive Systems: Bridging the Gap between Language, Motor Control and Vision Authors: W. Wang, V. Enescu and H. Sahli Publication Date: Aug. 2012 Number of Pages: 43
Abstract: In this paper we propose a reliable gesture recognition system that could be run on low-level machines in real-time, which is practical in human-robot interaction scenarios. The system is based on a Random Forest classifier fed with Motion History Images(MHI) as classi?cation features. To detect fast continuous gestures as well as to improve the robustness, we introduce a feedback mechanism for parameter tuning. We applied the system as a component in the child-robot imitation game of ALIZ-E project.
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