Style similarity algorithm based on clothing style

In order to calculate accurately the similarity between clothing images so as to meet the cross-scene needs of more users searching for clothing matching images for purchasing similar clothing, the influencing factors of clothing styles were investigated based on clothing styles constructed according to quantitative standards. The feature model of styles was established to further analyze the shortcomings of existing clothing attribute recognition algorithms, and was used to identify styles based on deep learning. The features of clothing styles were depicted through constructing a residual network model that integrates transfer learning. The experimental results show that the precision of the model on clothing style features is close to 90%, and the overall accuracy reaches 80%. Compared with the traditional image similarity methods, the accuracy of the image similarity calculation based on clothing styler is higher.This research also provides new ideas for personalized clothing recommendation. © 2021, Periodical Agency of Journal of Textile Research. All right reserved.