基于服装风格的款式相似度算法

Style similarity algorithm based on clothing style

为准确计算服装图像之间的相似度,从而满足更多用户通过搜索服装搭配图像来购买相似服装的跨场景需求,研究了服装风格的影响因素,并以服装风格的量化标准为基础,构建了服装款式的风格特征模型,进一步分析了现有服装属性识别算法的不足,实现了基于深度学习的款式风格特征识别,通过构建融合迁移学习的残差网络模型,刻画出服装在款式上的风格特征。实验结果表明:模型在服装款式风格特征上的精确度接近90%,准确度达到了80%;相对于传统的图像相似度计算方法,基于服装款式风格的图像相似度计算,准确率和可解释性更高,也为服装个性化推荐提供了新的思路。

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.