Clothing Recommendation System based on Visual Information Analytics

Due to the short fashion style life circle, much more different clothing designs show up. It is hard for consumers to find the suitable clothes effectively. To solve this problem, an automatic and reliable recommendation system is in great demand. In this paper, the clothing attributes recognition, gender recognition, and body height are considered to design the recommendation system. Based on the clothing style, gender and body height, the system can recommend the proper clothes with suitable size. On-line texture modeling is proposed to produce the variation of the clothing texture so that the recommendation system can give reasonable and diversified choices for the consumers. Besides, the data of consumers' wearing style is also useful to make the better marketing strategy. According to the reasons above, the clothing recognition and recommendation system can create a win-win situation between the consumers and the fashion industry.