法医学杂志

法医学杂志 ›› 2018, Vol. 34 ›› Issue (4): 363-369，374.DOI: 10.12116/j.issn.1004-5619.2018.04.004

• 论著 • 上一篇    下一篇

新疆维吾尔族男性三维人脸图像的年龄估计与年龄面貌重构

潘思宇1，2，陈诗婷3，唐  鲲3，李彩霞2，刘  京2，叶  健1，2，赵雯婷2   

  1. 1. 中国人民公安大学，北京 100038； 2. 公安部物证鉴定中心 北京市现场物证检验工程技术研究中心 现场物证溯源技术国家工程实验室，北京 100038； 3. 中国科学院上海生命科学研究院，上海 200031
  • 发布日期:2018-08-25 出版日期:2018-08-28
  • 通讯作者: 叶健，女，博士，主任法医师，主要从事法医遗传学研究；E-mail：yejian77@126.com 赵雯婷，女，博士，副主任法医师，主要从事法医遗传学研究；E-mail：wtzhao@sibs.ac.cn
  • 作者简介:潘思宇（1990—），男，硕士研究生，主要从事法医遗传学研究；E-mail：276951867@qq.com
  • 基金资助:
    “十三五”国家重点研发计划资助项目（2017YFC0803501）；国家科技资源共享服务平台计划资助项目（YCZYPT[2017]01-3）；基本科研业务费资助项目（2016JB001，2017JB025，2018JB046）

Age Estimation and Age-related Facial Reconstruction of Xinjiang Uygur Males by Three-dimensional Human Facial Images

PAN Si-yu1,2, CHEN Shi-ting3, TANG Kun3, LI Cai-xia2, LIU Jing2, YE Jian1,2, ZHAO Wen-ting2   

  1. 1. People’s Public Security University of China, Beijing 100038, China; 2. National Engineering Laboratory for Crime Scene Evidence Investigation and Examination, Beijing Engineering Research Center of Crime Scene Evidence Examination, Institute of Forensic Science, Ministry of Public Security, Beijing 100038, China; 3. Shanghai Institutes for Biological Sciences, Shanghai 200031, China
  • Online:2018-08-25 Published:2018-08-28
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摘要： 目的 基于新疆维吾尔族男性三维脸部图像寻找与年龄相关的脸部特征，构建年龄估计模型，重塑个体衰老及年轻时的脸部图像。 方法 使用Artec Studio软件对采集的105例17~57岁新疆维吾尔族男性人脸三维图像预处理。用FaceAnalysis软件将人脸图像转为高密度三维点阵数据，使每张图像可用32 251个点所表示。利用广义普鲁克分析法对人脸图像进行中心化校正并统一至同一坐标系。采用偏最小二乘回归法建立年龄估计模型。将年龄相关脸部形态特征的变化展现在平均脸的热图上，并基于该模型进行不同年龄的脸部图像重构。 结果 随着年龄的增长，平均脸会发生鼻唇沟加深、脸颊凹陷、颧骨突出、眼角下垂等变化。估计年龄和真实年龄之间的Pearson相关系数为0.71，估计年龄的平均绝对偏差（mean absolute deviation，MAD）为6.37岁，>30~40岁组的年龄估计结果最准确（MAD值为4.27岁），40岁以后偏差随年龄上升。合成的脸部图像随年龄增长脸部形态变化和衰老效果明显。 结论 本研究在维吾尔族人群中揭示了年龄相关的脸部特征和衰老标记，建立了可靠的年龄估计模型。

 

关键词: 法医人类学；成像, 三维；面部；年龄测定；年龄面貌合成；新疆；维吾尔族

Abstract: Objective To search age-correlated facial features and construct an age estimation model based on the three-dimensional （3D） facial images of Xinjiang Uygur males, and to structure individual face images of old age and young age. Methods Pretreatment was performed to collect 105 3D facial images of Xingjiang Uygur males aged between 17-57 years by Artec Studio software. The facial images were transferred to high-density 3D dot matrix data by FaceAnalysis software, and each image could be represented with 32 251 vertexes. Central correction of the facial images was done and all the data were aligned to a standard coordinate frame by generalized Procrustes analysis （GPA）. The age estimation model was established by partial least square regression （PLSR）. Furthermore, the changes of age-correlated facial features were presented on the heat map of average face, and the reconstruction of facial images at different ages was performed based on this model. Results With age, the average faces showed a series of changes including the nasolabial sulcus deepening, cheek sinking, cheekbone protruding and eye corner drooping. The Pearson correlation coefficient （r） between estimated age and chronological age was 0.71. The mean absolute deviation （MAD） of age estimation was 6.37 years. The results of age estimation in >30-40 years group showed a best accuracy （MAD=4.27 years）, and the deviations increased with age after 40 years. The composite facial images represented a significant result with age on facial morphological features and aging. Conclusion The results of this study reveal the age-correlated facial features and aging markers in Uygur population, which help to construct a reliable age estimation model.

Key words: forensic anthropology, imaging, three-dimensional, face, age determination, face reconstruction, Xinjiang, Uygur

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