Hand gesture interfaces provide an intuitive and natural way for interacting with a wide range of applications. Nowadays, the development of these interfaces is supported by an increasing number of sensing devices which are able to track hand and finger movements. Despite this, the physical and technical features of many of these devices make them unsuitable for the implementation of interfaces oriented to the everyday desktop applications. Conversely, the LEAP motion controller has been specifically designed to interact with these applications. Moreover, this latter device has been equipped with a hand skeletal model that provides tracking data with a high level of accuracy.This paper describes a novel approach to define and recognize hand gestures. The proposed method adopts freehand drawing recognition algorithms to interpret the tracking data of the hand and finger movements. Although our approach is applicable to any hand skeletal model, the overall features of that provided by the LEAP motion controller have driven us to use it as a reference model. Extensive preliminary tests have demonstrated the usefulness and the accuracy of the proposed method

Markerless hand gesture interface based on LEAP motion controller

Avola, Danilo;Petracca, Andrea;Placidi, Giuseppe;Spezialetti, Matteo;Cinque, Luigi;
2014-01-01

Abstract

Hand gesture interfaces provide an intuitive and natural way for interacting with a wide range of applications. Nowadays, the development of these interfaces is supported by an increasing number of sensing devices which are able to track hand and finger movements. Despite this, the physical and technical features of many of these devices make them unsuitable for the implementation of interfaces oriented to the everyday desktop applications. Conversely, the LEAP motion controller has been specifically designed to interact with these applications. Moreover, this latter device has been equipped with a hand skeletal model that provides tracking data with a high level of accuracy.This paper describes a novel approach to define and recognize hand gestures. The proposed method adopts freehand drawing recognition algorithms to interpret the tracking data of the hand and finger movements. Although our approach is applicable to any hand skeletal model, the overall features of that provided by the LEAP motion controller have driven us to use it as a reference model. Extensive preliminary tests have demonstrated the usefulness and the accuracy of the proposed method
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/124010
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