DocumentCode :
2426553
Title :
Discovering Dressing Knowledge for an Intelligent Dressing Advising System
Author :
Cheng, Ching-i ; Liu, Damon Shing-Min
Author_Institution :
Nat. Chung Cheng Univ., Chiayi
Volume :
4
fYear :
2007
fDate :
24-27 Aug. 2007
Firstpage :
339
Lastpage :
343
Abstract :
Our research aims to develop a system to help women choose correct attire for attending a specific occasion using all of what have already been in their closets. Many different computer theories and techniques are gathered in the project. Category learning with supervised neural networking is applied to cluster garments into different impression groups. Fuzzy theories are applied for gathering fashion match rules. In addition, modeling and virtual dressing techniques are used for representing matched garments pair in digital show room. User can simply submit her queries to the system on the occasions when the user has trouble finding an outfit for a special event. After enquiries are received, the core is following fuzzy logic rules to search good matches in the garment database and showing the matched results in the show room. This paper focuses on how garment classification and matching rules retrieved from fashion stylists.
Keywords :
clothing; data mining; fuzzy set theory; humanities; neural nets; virtual reality; category learning; digital show room; discovering dressing knowledge; fashion match rules; fuzzy logic rules; fuzzy theories; garment database; intelligent dressing advising system; supervised neural networking; virtual dressing techniques; Clothing; Computer applications; Databases; Digital images; Fuzzy logic; Fuzzy systems; Intelligent systems; Neural networks; Pipelines; Psychology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
Type :
conf
DOI :
10.1109/FSKD.2007.256
Filename :
4406408
Link To Document :
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