面向个性化服装推荐的判断优化模型

针对已有服装推荐算法中服装色调与用户颜色特征不协调的问题，将服装搭配的四季色彩理论与计算机视觉领域的推荐方法相结合，提出一种面向个性化服装推荐的判断优化模型。提出四季色彩判断模型，对根据输入的人脸图像提取得到的用户颜色特征集进行分类；建立优化处理模型，根据四季色彩判断模型结果和用户所需风格进行优化处理并获得服装预推荐结果；通过用户评分及反馈机制，提高优化结果，得到最终推荐结果。实验表明，该方法能实现与用户颜色特征相协调的个性化的服装推荐，并且在实际应用中具有较高的准确率。

Judgement and optimization model for personalized clothing recommendation

Judgement and optimization model for personalized clothing recommendation is proposed, which aims to solve the problem of clothing recommendation algorithm inconsistent with the color characteristics of the user color by combination of four seasons color theory and computer vision. Firstly, the four seasons color judgment model is applied to classify the user color feature based on the input face image. Secondly, the optimization processing model is established, according to the results of the four seasons color judgment model and user’s required style to optimize the processing and get the clothing pre-recommendation results. Finally, the user scoring and feedback mechanism are used to improve the optimization result and get the final recommendation result. Experiments show that this method can realize personalized clothing recommendation which is compatible with user color characteristics with high accuracy in practical application.