A Decision Making Framework for Dressing Consultant

Abstract

The project, Dressing Consultant, aims to provide a system which functions as a personal wearing advisor to help general users choose a correct clothing for occasions. ALCOVE (attention learning covering network) neural network model is used to train the matchmaker as a fashion editor. In addition, image processing techniques are employed at pre-processing stage to obtain the essential data of garments and to build a digital wardrobe for individuals. On the occasions when user has trouble finding an outfit for a special event, what user could do is to make a decision of the style of apparel to the system and let the system go through piece of garments in the digital wardrobe, and the matchmaker will then find several matched pairs. Eventually, the most similarly suitable and matched garments pair is shown in 3D show room. This paper focuses on making decision of correct clothing according to those classifying and matching rules extracted from fashion industry