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Exploiting the Similarity of Top 100 Beauties for Hairstyle Recommendation via Perceptual Hash

Abstract : In recent years, with the fast development of the fashion industry, the definition of beauty is constantly changing and the diversity of women’s hairstyles always gives us a dazzling feeling. Most young female would like to pursue the varying fashion trend and change a hairstyle to meet the fashion requirements. How to choose an appropriate fashion hairstyle has become a critical issue for modern fashion women. In this paper, we design and implement a C++ based female hairstyle recommendation system. At first, the selected top 100 beauties per year in the world are collected for building the beauty standard. Then, considering the changing female status (e.g., age, weight), perceptual hash algorithm (pHash) is used to calculate the global similarity between the user and 100 beauties for selecting the appropriate hairstyle. Finally, the comprehensive rank results from more than 350 demonstrate the recommended hairstyle is preferred.
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Chentong Zhang, Jiajia Jiao. Exploiting the Similarity of Top 100 Beauties for Hairstyle Recommendation via Perceptual Hash. 2nd International Conference on Intelligence Science (ICIS), Nov 2018, Beijing, China. pp.49-59, ⟨10.1007/978-3-030-01313-4_6⟩. ⟨hal-02118820⟩



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