颅面复原是根据给定的未知颅骨数据来估算对应的面貌, 在法医学、人类学、公安刑侦等领域都有重要的应用价值。针对颅面复原中手工提取特征点费时费力的问题, 本文依据颅面几何结构, 在三维颅面模型上自动提取以鼻尖点为起点的均匀分布于人脸的径向曲线作为颅面的特征表示, 并以颅骨和人脸面皮上提取的径向曲线作为训练样本数据, 构建了一种基于径向曲线的颅面统计复原模型, 通过由这种模型得到的先验知识联合待复原颅骨数据, 来求得面皮数据。实验结果表明: 与基于主成分分析( PCA)进行的颅面复原方法相比, 本文提出的基于径向曲线的颅面统计复原方法的复原精度提高了 2. 95倍, 速度提高了 4. 01倍, 因此本文方法降低了模型中样本数据的维度, 提高了颅面复原的精度和速度, 颅面复原的效果得到进一步的改善。

Craniofacial reconstruction is used to estimate facial data for a given unknown skull data, and it has been widely applied in various fields such as forensic science, anthropology, and criminal investiga. tion. It is time-consuming and laborious to extract feature points manually during craniofacial reconstruc. tion. In this study, radial curves uniformly distributed on the face were automatically extracted starting from the nose tip as a feature representation of the three-dimensional craniofacial model based on its geome. try structure. The extracted radial curves and skull data were used as training sample data to establish a sta. tistical model for craniofacial reconstruction. Previous knowledge obtained using the statistical model and skull data were used to estimate the data for the face. The experimental results showed that when the craniofacial statistical method based on the radial curves was applied, the craniofacial reconstruction accuracy improved by 2. 95 times;moreover, the reconstructed speed was 4. 01 times faster than that of the cranio. facial reconstruction method based on principal component analysis. Therefore, our method reduces the di. mension of craniofacial data and improves the accuracy and speed of the reconstruction results.