Every form of human gesture has been recognized in the literature as a means of providing natural and intuitive ways to interact with computers across many computer application domains. In this paper we propose a real time gesture recognition approach which uses a depth sensor to extract the initial human skeleton. Then, robust and significant features have been compared and the most unrelated and representative features have been selected and fed to a set of supervised classifiers trained to recognize different gestures. Different problems concerning the gesture initialization, segmentation, and normalization have been considered. Several experiments have demonstrated that the proposed approach works effectively in real time applications.

A real time gesture recognition system for Human Computer Interaction / Attolico, C; Cicirelli, G; Guaragnella, Cataldo; D’Orazio, T.. - 8869:(2015), pp. 92-101. (Intervento presentato al convegno Third IAPR Workshop on Multimodal Pattern Recognition of Social Signals in  Human Computer Interaction (MPRSS 2014), in conjuction with ICPR 2014 tenutosi a Stockholm, Sweden nel August 24, 2014) [10.1007/978-3-319-14899-1_9].

A real time gesture recognition system for Human Computer Interaction

GUARAGNELLA, Cataldo;
2015-01-01

Abstract

Every form of human gesture has been recognized in the literature as a means of providing natural and intuitive ways to interact with computers across many computer application domains. In this paper we propose a real time gesture recognition approach which uses a depth sensor to extract the initial human skeleton. Then, robust and significant features have been compared and the most unrelated and representative features have been selected and fed to a set of supervised classifiers trained to recognize different gestures. Different problems concerning the gesture initialization, segmentation, and normalization have been considered. Several experiments have demonstrated that the proposed approach works effectively in real time applications.
2015
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction: Third IAPR TC3 Workshop, MPRSS 2014, Stockholm, Sweden, August 24, 2014, Revised Selected Papers
978-3-319-14898-4
978-3-319-14899-1
Springer
A real time gesture recognition system for Human Computer Interaction / Attolico, C; Cicirelli, G; Guaragnella, Cataldo; D’Orazio, T.. - 8869:(2015), pp. 92-101. (Intervento presentato al convegno Third IAPR Workshop on Multimodal Pattern Recognition of Social Signals in  Human Computer Interaction (MPRSS 2014), in conjuction with ICPR 2014 tenutosi a Stockholm, Sweden nel August 24, 2014) [10.1007/978-3-319-14899-1_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/13316
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