A Neural Network Model for a View Independent Extraction of Reach-to-Grasp Action Features

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Abstract. The aim of this paper is to introduce a novel, biologically inspired approach to extract visual features relevant for controlling and understanding reachto-grasp actions. One of the most relevant of such features has been found to be the grip-size defined as the index finger-tip - thumb-tip distance. For this reason, in this paper we focus on this feature. The human visual system is naturally able to recognize many hand configurations

Roberto Prevete, Matteo Santoro, Ezio Catanzariti,

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Artificial Intelligence | BVAI 2007 | Computational Models | MNS Model | Visual Features |

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Added	12 Aug 2010
Updated	12 Aug 2010
Type	Conference
Year	2007
Where	BVAI
Authors	Roberto Prevete, Matteo Santoro, Ezio Catanzariti, Giovanni Tessitore

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A Neural Network Model for a View Independent Extraction of Reach-to-Grasp Action Features

Artificial Intelligence | BVAI 2007 | Computational Models | MNS Model | Visual Features |

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