Context dependent recognition and parametrization of shape features (Contributo in atti di convegno)

Type
Label
  • Context dependent recognition and parametrization of shape features (Contributo in atti di convegno) (literal)
Anno
  • 1997-01-01T00:00:00+01:00 (literal)
Alternative label
  • F. Giannini, T. De Martino, B. Falcidieno (1997)
    Context dependent recognition and parametrization of shape features
    in TC5/WG5.1 International Workshop on Geometric Modeling in Computer Aided Design, Airlie, VA, USA, 19-23 Maggio 1996
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • F. Giannini, T. De Martino, B. Falcidieno (literal)
Pagina inizio
  • 191 (literal)
Pagina fine
  • 202 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Product Modeling for Computer Integrated Design and Manufacture (literal)
Note
  • Google Scholar (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto per la Matematica Applicata - C.N.R. Fraunhofer Institut fuer Graphische (literal)
Titolo
  • Context dependent recognition and parametrization of shape features (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-412-80980-X (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • M.J. Pratt, R.D. Sriram, M.J. Wozny (literal)
Abstract
  • Feature technology is now becoming popular in most advanced CAD systems. However, feature recognition processes are still necessary both to derive design feature-based description from traditional geometric representations for re-design purposes and to create feature-based description for driving downstream applications. One of the main limitations in existing automatic feature recognition systems is the inability of identifying simple features when feature faces and edges have been split or destroyed as a consequence of the interaction with other features. In this paper, a method for identifying such situations by means of geometric reasoning is presented. The proposed system is able to recognize not only generic features but also specific instances of application features with their defining parameter relations and values. (literal)
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