3D gesture recognition with growing neural gas

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Author(s)
Sérra-Perez, JA
García-Rodríguez, J
Orts-Escolano, S
García-Chamizo, JM
Montoyo-Bojo, J
Angelopoulou, A
Psarrou, A
Mentzeopoulos, M
Lewis, A
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Bruno Apolloni

Date
2013
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Dallas, Texas

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Abstract

We propose the design of a real-time system to recognize and interpret hand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose segmentation, characterization and tracking will be implemented using the growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provided with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirror writing system and a module to estimate hand pose have been designed to demonstrate the validity of the system.

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Proceedings of the International Joint Conference on Neural Networks

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Computer vision

Image processing

Virtual and mixed reality

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