2D sketch based recognition of 3D freeform shape by using the RBF neural network

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2568

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DC Field	Value	Language
dc.contributor.author	Qin, SF	-
dc.contributor.author	Sun, GM	-
dc.contributor.author	Wright, DK	-
dc.contributor.author	Lim, S	-
dc.contributor.author	Khan, U	-
dc.contributor.author	Mao, C	-
dc.coverage.spatial	8	en
dc.date.accessioned	2008-08-01T15:39:10Z	-
dc.date.available	2008-08-01T15:39:10Z	-
dc.date.issued	2005	-
dc.identifier.citation	Proceedings of Eurographics Workshop on Sketch Based Interfaces and Modeling. Dublin, 2005.	en
dc.identifier.issn	1812-3503	-
dc.identifier.uri	http://www.eg.org/DOI/10.2312/SBM/SBM05/119-126	en
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/2568	-
dc.description.abstract	This paper presents a novel free-form surface recognition method from 2D freehand sketching. The approach is based on the Radial basis function (RBF), an artificial intelligence technique. A simple three-layered network has been designed and constructed. After training and testing with two types of surfaces (four sided boundary surfaces and four close section surfaces), it has been shown that the method is useful in freeform surface recognition. The testing results are very satisfactory.	en
dc.format.extent	270677 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	Eurographics	en
dc.title	2D sketch based recognition of 3D freeform shape by using the RBF neural network	en
dc.type	Conference Paper	en
Appears in Collections:	Design Brunel Design School Research Papers

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