Towards a mean body for apparel design
Impacto
Scholar |
Otros documentos de la autoría: Domingo Esteve, Juan de Mata; Simó, Amelia; Ibáñez Gual, Maria Victoria; Dura, Esther; Ayala Gallego, Guillermo; Alemany Mut, Sandra
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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http://dx.doi.org/10.1016/j.imavis.2016.04.016 |
Metadatos
Título
Towards a mean body for apparel designAutoría
Fecha de publicación
2016-08Editor
ElsevierCita bibliográfica
DOMINGO ESTEVE, Juan de Mata; SIMÓ VIDAL, Amelia; IBÁÑEZ GUAL, María Victoria; DURA, Esther; AYALA GALLEGO, Guillermo; ALEMANY MUT, Sandra. Towards a mean body for apparel design. Image and vision computing (2016), v. 52, pp. 88-96Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0262885616300944Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
This paper focuses on shape average with applications to the apparel industry. Apparel industry uses a
consensus sizing system; its major concern is to fit most of the population into it. Since anthropometric
measures ... [+]
This paper focuses on shape average with applications to the apparel industry. Apparel industry uses a
consensus sizing system; its major concern is to fit most of the population into it. Since anthropometric
measures do not grow linearly, it is important to find prototypes to accurately represent each size. This is
done using random compact mean sets, obtained from a cloud of 3D points given by a scanner and applying
to the sample a previous definition of mean set. Additionally, two approaches to define confidence sets are
introduced. The methodology is applied to data obtained from a real anthropometric survey. [-]
Publicado en
Image and vision computing (2016), v. 52Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/restrictedAccess
info:eu-repo/semantics/restrictedAccess
Aparece en las colecciones
- MAT_Articles [770]