http://www.cnr.it/ontology/cnr/individuo/prodotto/ID31232
A Framework for the Automatic Annotation of Car Aesthetics (Articolo in rivista)
- Type
- Label
- A Framework for the Automatic Annotation of Car Aesthetics (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1017/S0890060407070151 (literal)
- Alternative label
Chiara E. Catalano; Franca Giannini; Marina Monti; Giuliana Ucelli (2007)
A Framework for the Automatic Annotation of Car Aesthetics
in Artificial intelligence for engineering design, analysis and manufacturing; Cambridge University Press, Cambridge (Regno Unito)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Chiara E. Catalano; Franca Giannini; Marina Monti; Giuliana Ucelli (literal)
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- Scopu (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Chiara E. Catalano,Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Genova, Italy
Franca Giannini,Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Genova, Italy
Marina Monti, Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Genova, Italy
Giuliana Ucelli, Fondazione Graphitech, Trento, Italy (literal)
- Titolo
- A Framework for the Automatic Annotation of Car Aesthetics (literal)
- Abstract
- The design of a new car is guided by a set of directives indicating the target market, specific engineering, and aesthetic
constraints, which may also include the preservation of the company brand identity or the restyling of products already
on the market. When creating a new product, designers usually evaluate other existing products to find sources of
inspiration or to possibly reuse successful solutions. In the perspective of an optimized styling workflow, great benefit
could be derived from the possibility of easily retrieving the related documentation and existing digital models both
from internal and external repositories. In fact, the rapid growth of resources on the Web and the widespread adoption
of computer-assisted design tools have made available huge amounts of data, the utilization of which could be improved
by using more selective retrieval methods. In particular, the retrieval of aesthetic elements may help designers to create
digital models conforming to specific styling properties more efficiently. The aim of our research is the definition of a
framework that supports ~semi!automatic extraction of semantic data from three-dimensional models and other multimedia
data to allow car designers to reuse knowledge and design solutions within the styling department. The first
objective is then to capture and structure the explicit and implicit elements contributing to the definition of car
aesthetics, which can be realistically tackled through computational models and methods. The second step is the
definition of a system architecture that is able to transfer such semantic evaluation through the automatic annotation of
car models.I (literal)
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