Selection of Three-Dimensional Garment Image Style Based on Three-Dimensional Body Shape Image Classification of Young Women

Autor:	Hidehiko Okabe, Mikako Nishi, Kaori Murakami, Tomoe Masuda
Rok vydání:	2007
Předmět:	Scale (ratio) Contextual image classification Computer science business.industry Principal component analysis Pattern recognition General Medicine Artificial intelligence business Young female Selection (genetic algorithm) Image (mathematics)
Zdroj:	Sen'i Gakkaishi. 63:277-286
ISSN:	1884-2259 0037-9875
DOI:	10.2115/fiber.63.277
Popis:	Useful information for garment selection support of young women's 3 Dimensional body (hereafter 3Dbody) rotating shape images and well-suited garment designs according to these 3D-body shapes were investigated using image evaluations (scale 1 to 5) on the same base. The full-length 3D-body shape images presented as the rotating simulations of thirteen young female models were categorized into five types (Groups by cluster analysis) using their three principal component scores calculated by means of six body image key words (As : A1 to A6). We extracted the de-emphasis or emphasis evaluations (Cs : C1 to C18) of the partial 3D-body shape images (Bs : B1 to B18) using the garments on the five full-length 3D-body types and the suitability of the twelve 3D-garment design images (Ds :D1 to D5) on the rotating body shape of each of the As.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c03b4e475f2f5ca6c550ddfecc8230bc https://doi.org/10.2115/fiber.63.277 Zobrazit plný text záznamu