Matthews Harold, Penington Anthony, Clement John, Kilpatrick Nicola, Fan Yi, Claes Peter
Murdoch Children's Research Institute, Melbourne, Australia; Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia.
Murdoch Children's Research Institute, Melbourne, Australia; Royal Children's Hospital, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia.
Forensic Sci Int. 2018 May;286:61-69. doi: 10.1016/j.forsciint.2018.02.024. Epub 2018 Mar 6.
3D facial images are becoming increasingly common. They provide more information about facial form than their 2D counterparts and will be useful in future forensic applications. These include age estimation and predicting changes in appearance of missing persons (synthetic growth). We present a framework for both age estimation and synthetic growth of children and adolescents from 3D photographs. Age estimation accuracy was substantially better than for existing approaches (mean absolute error=1.19 years). Our synthetically 'grown' images were compared to actual longitudinal images of the same cases. On average 75% of the head overall and 85% of the face were predicted correctly to within three millimetres. We find that our approach is most suitable for ageing children from late childhood into adolescence. The work can be improved in the future by modelling skin colouring and taking account of other factors that influence face shape such as BMI.
三维面部图像正变得越来越普遍。与二维面部图像相比，它们能提供更多关于面部形态的信息，并且在未来的法医应用中会很有用。这些应用包括年龄估计以及预测失踪人员外貌的变化（合成生长）。我们提出了一个从三维照片中对儿童和青少年进行年龄估计和合成生长的框架。年龄估计的准确性比现有方法有显著提高（平均绝对误差 = 1.19岁）。我们将合成“生长”的图像与相同案例的实际纵向图像进行了比较。平均而言，头部整体的75%和面部的85%被正确预测到误差在三毫米以内。我们发现我们的方法最适合对从儿童晚期到青春期的儿童进行年龄增长模拟。未来可以通过对面部肤色进行建模以及考虑其他影响面部形状的因素（如身体质量指数）来改进这项工作。
