RGB-D cameras and depth sensors have made possible the development of an uncountable number of applications in the field of human-computer interactions. Such applications, varying from gaming to medical, have made possible because of the capability of such sensors of elaborating depth maps of the placed ambient. In this context, aiming to realize a sound basis for future applications relevant to the movement and to the pose of hands, we propose a new approach to recognize fingertips and to identify their position by means of the Microsoft Kinect technology. The experimental results exhibit a really good identification rate, an execution speed faster than the frame rate with no meaningful latencies, thus allowing the use of the proposed system in real time applications. Furthermore, the scored identification accuracy confirms the excellent capability of following also little movements of the hand and it encourages the real possibility of successive implementations in more complex gesture recognition systems. © 2011 IEEE.

An accurate algorithm for the identification of fingertips using an RGB-D camera / Marco, Maisto; Panella, Massimo; Liparulo, Luca; Proietti, Andrea. - In: IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS. - ISSN 2156-3357. - STAMPA. - 3:2(2013), pp. 272-283. [10.1109/jetcas.2013.2256830]

An accurate algorithm for the identification of fingertips using an RGB-D camera

PANELLA, Massimo;LIPARULO, LUCA;PROIETTI, ANDREA
2013

Abstract

RGB-D cameras and depth sensors have made possible the development of an uncountable number of applications in the field of human-computer interactions. Such applications, varying from gaming to medical, have made possible because of the capability of such sensors of elaborating depth maps of the placed ambient. In this context, aiming to realize a sound basis for future applications relevant to the movement and to the pose of hands, we propose a new approach to recognize fingertips and to identify their position by means of the Microsoft Kinect technology. The experimental results exhibit a really good identification rate, an execution speed faster than the frame rate with no meaningful latencies, thus allowing the use of the proposed system in real time applications. Furthermore, the scored identification accuracy confirms the excellent capability of following also little movements of the hand and it encourages the real possibility of successive implementations in more complex gesture recognition systems. © 2011 IEEE.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/513422
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