dc.contributor.author | Qin, S. F. | en_US |
dc.contributor.author | Sun, Guangmin | en_US |
dc.contributor.author | Wright, D. K. | en_US |
dc.contributor.author | Lim, S. | en_US |
dc.contributor.author | Khan, U. | en_US |
dc.contributor.author | Mao, C. | en_US |
dc.contributor.editor | Joaquim Armando Pires Jorge and Takeo Igarashi | en_US |
dc.date.accessioned | 2014-01-27T18:26:20Z | |
dc.date.available | 2014-01-27T18:26:20Z | |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 3-905673-30-4 | en_US |
dc.identifier.issn | 1812-3503 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/SBM/SBM05/119-126 | en_US |
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_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Categories and Subject Descriptors (according to ACM CSS): H.5.2 [Information Interfaces and Presentation]: Graphical user interfaces (GUI); I.2.10 [Artificial Intelligence]: surface modelling. | en_US |
dc.title | 2D Sketch Based Recognition of 3D freeform Shape by Using the RBF Neural Network | en_US |
dc.description.seriesinformation | Eurographics Workshop on Sketch-Based Interfaces and Modeling | en_US |