Development of Three-Dimension computer graphic system for reconstruction of the face features from the skull.

首先，我们分析了形成面部特征的器官的大小，如咬肌和腮腺，与每个受试者的特征，如性别、年龄、头骨大小、身高、体重、身体质量指数和残余臼齿数量之间的关系。使用CT图像测量每个器官的大小。我们使用多元回归分析来评估这些关系。并建立了面部各器官的预测值函数。多元相关系数为0.71 ~ 0.74。我们评估了人脸重建的等级，人们可以识别每个被试，使用特征脸方法重建每个被试的裁剪的脸，这是基于一种称为主成分分析的方法。在此基础上，利用聚类分析对人脸图像进行分类。结果表明，个体人脸至少有7个特征面，即重构等级为0.88相关系数，认为个体人脸被识别为裁剪后的人脸。通过聚类分析，将人脸图像分为5类。我们分析了人们识别个体的面部因素。结果表明，最重要的因素是双眼之间的距离。其次，嘴唇的宽度。如上所述，我们获得了有关面部与个体特征（头骨大小、性别、年龄、体重、咀嚼功能）之间关系的有用结果，以及用于识别个体面部的面部重建等级。然而，目前我们正在开发用于人脸特征重建的计算机图形软件。

At first We analyzed the relationships between the size of organs that formed face features such as the masseter muscle and the parotid gland, and characteristic of each subject such as sex, age, the size of the skull, height, weight, body mass index and number of residual molar teeth. The size of each organs were measured using CT images. We evaluated the relationships using multiple regression analysis. And the function for predict value of each organ in face was made. Their multiple correlation coefficients were 0.71 to 0.74.We evaluated the grade of reconstruction of face that persons could identify each subject using cropped faces of each subject which were reconstructed using the eigen-face methods, which is based on a methods known as the principal component analysis. Furthermore, the facial images was classified by cluster analysis. As a results, It was consider that individual face was identified to cropped face with at least 7 eigen-faces, that is, the grade of reconstruction was 0.88 of correlation coefficients. Furthermore, face images were classified into 5 groups by cluster analysis.We analyzed the factors in face by which persons identify individuals. As results, The most important factor was the distance between both eyes. Secondly, the width of the lips.As above mentioned, we obtained useful results concerning with the relationships between face and the individual features (skull size, sex, age, body mass, masticator function), and the grade of reconstruction of face for identifying the individual face. However, we are developing the computer graphic software for reconstruction of the face features now.