Full metadata record
DC poleHodnotaJazyk
dc.contributor.authorLangerak, T. R.
dc.contributor.authorVergeest, J. S. M.
dc.contributor.authorWang, H.
dc.contributor.authorSong, Y.
dc.contributor.editorRossignac, Jarek
dc.contributor.editorSkala, Václav
dc.date.accessioned2014-04-08T10:41:24Z
dc.date.available2014-04-08T10:41:24Z
dc.date.issued2007
dc.identifier.citationWSCG '2007: Full Papers Proceedings: The 15th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2007 in co-operation with EUROGRAPHICS: University of West Bohemia Plzen Czech Republic, January 29 – February 1, 2007, p. 145-152.en
dc.identifier.isbn978-80-86943-98-5
dc.identifier.urihttp://wscg.zcu.cz/wscg2007/Papers_2007/full/!WSCG2007_Full_Proceedings_Final-1.zip
dc.identifier.urihttp://hdl.handle.net/11025/10995
dc.description.abstractNowadays, most 3D CAD systems support the use of form features. The main advantage of form features is that they provide parametric, high-level support for shape manipulation. When the parametric information of a shape is not available, it can be retrieved using a feature recognition procedure. In this procedure, a target shape is recognized as an instance of one or more features in a pre-defined feature library. The speed and accuracy of the feature recognition procedure significantly improve when the target feature type is known. This information can be provided by a user, but we propose a new method that identifies the feature type automatically. This method uses an evolutionary algorithm to find the optimal feature type. The algorithm randomly generates a population of instances of every type of feature available in the feature library. From this initial population of feature instances, successive populations are generated using the principle of natural selection. The algorithm was tested for different settings and was found to correctly identify features in between one and three minutes.en
dc.format8 s., 1 prezentacecs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG '2007: Full Papers Proceedingsen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectrozpoznávání znakůcs
dc.subjectevoluční algoritmycs
dc.subjectznaková knihovnacs
dc.titleAn Evolutionary Strategy for Free Form Feature Identification in 3D CAD Modelsen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedfeature recognitionen
dc.subject.translatedevolutionary algorithmsen
dc.subject.translatedfeature libraryen
dc.type.statusPeer-revieweden
dc.type.driverinfo:eu-repo/semantics/conferenceObjecten
dc.type.driverinfo:eu-repo/semantics/publishedVersionen
Vyskytuje se v kolekcích:WSCG '2007: Full Papers Proceedings

Soubory připojené k záznamu:
Soubor Popis VelikostFormát 
Langerak.pdfPlný text430,39 kBAdobe PDFZobrazit/otevřít
Langerak_prezentace.pptPrezentace663,5 kBMicrosoft PowerpointZobrazit/otevřít


Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/10995

Všechny záznamy v DSpace jsou chráněny autorskými právy, všechna práva vyhrazena.