Chapter title | 3D hand pose estimation with neural networks |
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Authors | Serra, J.A., Garcia-Rodriguez, J., Orts Escolano, S., Garcia-Chamizo, J.M., Angelopoulou, A., Psarrou, A., Mentzelopoulos, M., Montoyo-Bojo, J. and Domínguez, E. |
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Abstract | 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. |
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Keywords | Growing Neural Gas, 3D Sensor, Hand Pose Estimation, Hand Motion, Trajectories Description |
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Book title | Advances in Computational Intelligence: 12th International Work-Conference on Artificial Neural Networks, IWANN 2013 |
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Year | 2013 |
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Publisher | Springer |
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Publication dates |
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Published | 2013 |
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ISBN | 9783642386817 |
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Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-642-38682-4_54 |
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Web address (URL) | http://www.scopus.com/inward/record.url?eid=2-s2.0-84880047937&partnerID=MN8TOARS |
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Event | 12th International Work-Conference on Artificial Neural Networks, IWANN 2013 |
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Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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