An SVM/GA hybrid framework for qualitative knowledge aided 3D scene synthesis

dc.contributor.author	Μακρής, Δημήτριος Γ.	el
dc.contributor.author	Μπάρδης, Γεώργιος	el
dc.contributor.author	Μιαούλης, Γεώργιος	el
dc.contributor.author	Πλεμενός, Δημήτρης	el
dc.date.accessioned	2015-06-07T07:38:03Z
dc.date.available	2015-06-07T07:38:03Z
dc.date.issued	2015-06-07
dc.identifier.uri	http://hdl.handle.net/11400/15392
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://link.springer.com/book/10.1007/978-3-642-03452-7	en
dc.subject	Computational intelligence
dc.subject	Conceptual design
dc.subject	Declarative modeling
dc.subject	Evolutionary search
dc.subject	Machine learning
dc.subject	Qualitative aspects
dc.subject	Style
dc.subject	Υπολογιστική νοημοσύνη
dc.subject	Εννοιλογικός σχεδιασμός
dc.subject	Δηλωτική μοντελοποίηση
dc.subject	Εξελικτική αναζήτηση
dc.subject	Μάθηση μηχανής
dc.subject	Ποιοτικές πτυχές
dc.subject	Ύφος
dc.title	An SVM/GA hybrid framework for qualitative knowledge aided 3D scene synthesis	en
heal.type	conferenceItem
heal.classification	Computer science
heal.classification	Artificial intelligence
heal.classification	Πληροφορική
heal.classification	Τεχνητή νοημοσύνη
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://skos.um.es/unescothes/C00261
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Τεχνητή νοημοσύνη
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh94004659
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85079324
heal.identifier.secondary	DOI: 10.1007/978-3-642-03452-7_9
heal.language	en
heal.access	campus
heal.recordProvider	Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2009
heal.bibliographicCitation	Makris, D., Bardis, G., Miaoulis, G. and Plemenos, D. (2009) An SVM/GA hybrid framework for qualitative knowledge aided 3D scene synthesis. In "Intelligent Computer Graphics 2009". [n.p.]: [n.n.]. Available from: http://link.springer.com/chapter/10.1007%2F978-3-642-03452-7_9 [Accessed: 07/06/2015].	en
heal.abstract	One of the major issues related to the conceptual phase of 3D scene synthesis is the acquisition and incorporation of qualitative aspects into the design process. Our motivation is to alleviate the task of synthesizing a scene conforming to the particularities of certain morphological or other intuitive demands. We address the feasibility of such a framework, through the study and integration of methods for the acquisition of qualitative knowledge as well as for the guided generation of scenes. The proposed framework comprises a knowledge obtainment stage, where the machine learning mechanism acquires the qualitative implications of a series of examples and a scene generation stage, where the evolutionary mechanism conducts a partial exploration of the solution space of scenes, compliant with a given set of quantitative requirements as well as to the acquired qualitative knowledge. The paradigm domain is that of architectural design with the aid of declarative modeling by hierarchical decomposition.	en
heal.fullTextAvailability	true
heal.conferenceName	Intelligent Computer Graphics 2009	en
heal.conferenceItemType	full paper