3D hand pose estimation with neural networks

Angelopoulou, A, Serra, JA, Garcia-Rodriguez, J, Orts-Escolano, S, Garcia-Chamizo, JM, Psarrou, A, Mentzelopoulos, M, Montoyo-Bojo, J and Domínguez, E (2013) 3D hand pose estimation with neural networks. In: 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, 12 Jun 2013, Puerto de la Cruz, Tenerife, Spain.

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Official URL: https://dx.doi.org/10.1007/978-3-642-38682-4_54


We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using 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 provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Growing Neural Gas, 3D Sensor, Hand Pose Estimation, Hand Motion, Trajectories Description
Subjects: University of Westminster > Science and Technology
SWORD Depositor: repository@westminster.ac.uk
Depositing User: repository@westminster.ac.uk
Date Deposited: 18 Nov 2015 15:22
Last Modified: 06 Jan 2016 16:46
URI: http://westminsterresearch.wmin.ac.uk/id/eprint/16024

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