3 June 2014 New generation of human machine interfaces for controlling UAV through depth-based gesture recognition
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Abstract
New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.
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Tomás Mantecón, Tomás Mantecón, Carlos Roberto del Blanco, Carlos Roberto del Blanco, Fernando Jaureguizar, Fernando Jaureguizar, Narciso García, Narciso García, } "New generation of human machine interfaces for controlling UAV through depth-based gesture recognition", Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840C (3 June 2014); doi: 10.1117/12.2053244; https://doi.org/10.1117/12.2053244
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