Discovering Dressing Knowledge for an Intelligent Dressing Advising System

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.