Laboratory for Human Craniofacial and Skeletal Identification (HuCS-ID Lab), School of Biomedical Sciences, The University of Queensland, Brisbane, 4072, Australia.
School of Biomedical Sciences, The University of Queensland, Brisbane, 4072, Australia.
Int J Legal Med. 2022 Nov;136(6):1697-1716. doi: 10.1007/s00414-022-02871-5. Epub 2022 Aug 24.
Craniofacial superimposition concerns the photographic overlay of skulls and faces, for skeletal identification. As a phased method that depends on photographic optics first and anatomical comparisons second, superimposition is strongly underpinned by the physics of light travel through glass lenses. So that the downstream (and dependent) anatomical evaluations are not thwarted or erroneous identification decisions risked, it is critical that the optical prerequisites for valid image comparisons are met. As focus distance sets the perspective, the focus distance used for skull photography must be matched to that used at face photography, so that anatomically comparable 1:1 images are obtained. In this paper, we review the pertinent camera optics that set these nonnegotiable fundamentals and review a recently proposed method for focus distance estimation. We go beyond the original method descriptions to explain the mathematical justification for the PerspectiveX algorithm and provide an extension to profile images. This enables the first scientifically grounded use of profile view (or partial profile view) photographs in craniofacial superimposition. Proof of concept is provided by multiple worked examples of the focus distance estimation for frontal and profile view images of three of the authors at known focus distances. This innovation (1) removes longstanding trial-and-error components of present-day superimposition methods, (2) provides the first systematic and complete optical basis for image comparison in craniofacial superimposition, and (3) will enable anatomical comparison standards to be established from a valid grassroots basis where complexities of camera vantage point are removed as interfering factors.
颅面叠合涉及颅骨和面部的照相叠加,用于骨骼识别。作为一种分阶段的方法,它首先依赖于照相光学,其次依赖于解剖比较,因此叠合得到了通过玻璃透镜传播光的物理原理的有力支持。为了不阻碍下游(和依赖的)解剖评估或冒险做出错误的识别决策,至关重要的是要满足有效图像比较的光学前提条件。由于焦点距离确定了视角,因此颅骨摄影使用的焦点距离必须与面部摄影使用的焦点距离相匹配,以获得可进行解剖比较的 1:1 图像。在本文中,我们回顾了确定这些不可协商的基本原理的相关相机光学,并回顾了最近提出的焦点距离估计方法。我们超越了原始方法描述,解释了 PerspectiveX 算法的数学依据,并为轮廓图像提供了扩展。这使得首次可以在颅面叠合中科学地使用轮廓视图(或部分轮廓视图)照片。通过对已知焦点距离的三位作者的正面和轮廓视图图像的焦点距离估计的多个实例进行演示,证明了该概念的可行性。这项创新(1)消除了当前叠合方法中长期存在的反复试验成分,(2)为颅面叠合中的图像比较提供了首个系统和完整的光学基础,(3)将能够从有效的基层基础上建立解剖比较标准,去除了相机视角的复杂性作为干扰因素。