Vezzetti Enrico, Marcolin Federica
Department of Management and Production Engineering, Politecnico di Torino, Torino, Italy.
Aesthetic Plast Surg. 2014 Aug;38(4):796-811. doi: 10.1007/s00266-014-0334-2. Epub 2014 May 30.
The application of three-dimensional (3D) facial analysis and landmarking algorithms in the field of maxillofacial surgery and other medical applications, such as diagnosis of diseases by facial anomalies and dysmorphism, has gained a lot of attention. In a previous work, we used a geometric approach to automatically extract some 3D facial key points, called landmarks, working in the differential geometry domain, through the coefficients of fundamental forms, principal curvatures, mean and Gaussian curvatures, derivatives, shape and curvedness indexes, and tangent map. In this article we describe the extension of our previous landmarking algorithm, which is now able to extract eyebrows and mouth landmarks using both old and new meshes. The algorithm has been tested on our face database and on the public Bosphorus 3D database. We chose to work on the mouth and eyebrows as a separate study because of the role that these parts play in facial expressions. In fact, since the mouth is the part of the face that moves the most and affects mainly facial expressions, extracting mouth landmarks from various facial poses means that the newly developed algorithm is pose-independent.
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三维(3D)面部分析和地标定位算法在颌面外科及其他医学应用领域中的应用,如通过面部异常和畸形来诊断疾病,已引起了广泛关注。在之前的一项工作中,我们采用了一种几何方法,通过基本形式系数、主曲率、平均曲率和高斯曲率、导数、形状和曲率指数以及切映射,在微分几何领域自动提取一些3D面部关键点,即地标。在本文中,我们描述了之前地标定位算法的扩展,该算法现在能够使用新旧网格提取眉毛和嘴巴地标。该算法已在我们的面部数据库和公共的博斯普鲁斯3D数据库上进行了测试。由于嘴巴和眉毛在面部表情中所起的作用,我们选择将它们作为单独的研究对象。事实上,由于嘴巴是面部运动最多且主要影响面部表情的部分,从各种面部姿势中提取嘴巴地标意味着新开发的算法与姿势无关。
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