Expert Systems With Applications
Expert Systems With Applications
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DOI：
10.1016/j.eswa.2017.04.021
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
Lei Zhang;D. Zhang;Ming-ming Sun;Fangmei Chen
中科院分区：
文献类型：
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作者：
Lei Zhang;D. Zhang;Ming-ming Sun;Fangmei Chen
人脸美容分析已经成为多媒体和生物识别领域的一个新兴学科。本文旨在从几何特征的角度探索面部美的本质，并将其应用于交互式吸引力评估(IAA)。在此基础上，提出了一种基于机器学习的几何人脸美感分析方法。由于美容标注的繁琐和主观性，造成准确标注的数据稀缺，导致标注的数据非常少。此外，面部美与几个典型的特征有关，如质地、颜色等，然而，这些特征很容易因化妆而变形。针对这些问题，提出了一种将几何特征引入到智能吸引力评价系统中的半监督人脸美容分析框架。为了进行实验研究，我们建立了一个包含亚洲男性和女性人脸的几何面部美容(GFB)数据集。此外，现有的包括西方和东方女性面孔的多模式美容(M2B)数据库也进行了测试。实验证明了该方法的有效性。揭示了对美的本质和面部审美主题的一些新的观点。这项工作的影响在于，它将吸引更多相关领域的研究人员通过使用智能算法进行美丽探索。此外，其意义在于，它应该很好地促进专家和智能系统的多样性，以解决这种具有挑战性的面部美感和评级问题。
Facial beauty analysis has been an emerging subject of multimedia and biometrics. This paper aims at exploring the essence of facial beauty from the viewpoint of geometric characteristic toward an interactive attractiveness assessment (IAA) application. As a result, a geometric facial beauty analysis method is proposed from the perspective of machine learning. Due to the troublesome and subjective beauty labeling, the accurately labeled data scarcity is caused, and result in very few labeled data. Additionally, facial beauty is related to several typical features such as texture, color, etc., which, however, can be easily deformed bymake-up. For addressing these issues, a semi-supervisedfacial beauty analysisframework that is characterized by feeding geometric feature into the intelligent attractiveness assessment system is proposed. For experimental study, we have established a geometric facial beauty (GFB) dataset including Asian male and female faces. Moreover, an existing multi-modal beauty (M2B) database including western and eastern female faces is also tested. Experiments demonstrate the effectiveness of the proposed method. Some new perspectives on the essence of beauty and the topic of facial aesthetic are revealed. The impact of this work lies in that it will attract more researchers in related areas for beauty exploration by using intelligent algorithms. Also, the significance lies in that it should well promote the diversity of expert and intelligent systems in addressing such challenging facial aesthetic perception and rating issue.