Counterterrorism and Forensic Science Research Unit, Visiting Scientist Program, FBI Laboratory Division, 2501 Investigation Parkway, Quantico, VA 22135, United States.
Counterterrorism and Forensic Science Research Unit, FBI Laboratory Division, 2501 Investigation Parkway, Quantico, VA 22135, United States.
Forensic Sci Int. 2018 Oct;291:272-278. doi: 10.1016/j.forsciint.2018.07.024. Epub 2018 Jul 27.
Currently in the United States, the remains of thousands of unidentified human decedents are housed in medical, law enforcement, and forensic facilities throughout the country. A number of digital data repositories have been established to curate and disseminate the details of these unidentified decedent cases; some repositories also maintain records of missing persons. Although a cross-reference for textual data similarity occurs between the missing persons and unidentified decedent records in some repositories, no repository is currently known to employ an image analysis technology for cross-referencing image data. Results suggest that the computer-generated facial approximations used in this research were consistently included in prioritized candidate lists when used in an automated facial recognition context. Two concurrent studies exploring the specific use-case discussed here were executed. The first employed an optimally-conditioned facial image gallery (g=6159) (i.e., a gallery comprised of highly consistent facial images), a research design intended to establish the ceiling performance of the combined use of the two software programs employed. The second employed a gallery (g=1816) compiled from a real-world dataset of missing persons' facial images, a research design intended to inform potential operational performance when using the highly varied facial images typically comprising public databases. Multiple types of facial approximations (reconstructions) with varying degrees of weight adjustments, age adjustments, or the presence (or absence) of visible eyes, and combinations of these variables, were evaluated. Overall, in the larger, optimally modeled study, 53% of the facial approximations for the t=159 test subjects examined were matched to his or her corresponding life photo within the top 50 images of a candidate list generated from a blind (unrestricted) search of the highly consistent gallery (g=6159). In the operationally modeled study, 31% of the test subjects' (t=16) facial approximations were matched to their corresponding life photos within the top 50 images of a candidate list generated from a blind search of the gallery populated with images from an operational dataset (g=1816). As anticipated, candidate list inclusion rates improved with the use of demographic filters. No significantly different inclusion rates were observed between the sex or age cohorts examined. Significant differences were, however, observed across population cohorts. Entities curating missing and unidentified decedent records may benefit from a paired implementation of facial recognition technology and computer-generated approximations as part of a comprehensive investigative strategy for the specific envisioned use-case discussed in this research.
目前在美国，数千具身份不明的死者遗体存放在全国各地的医疗、执法和法医机构中。已经建立了许多数字数据库来管理和传播这些身份不明的死者案例的详细信息；一些数据库还保存失踪人员的记录。尽管一些数据库中失踪人员和身份不明的死者记录之间存在文本数据相似性的交叉引用，但目前还没有一个数据库使用图像分析技术进行图像数据的交叉引用。研究结果表明，在自动面部识别环境中使用时，本研究中生成的计算机面部近似值始终包含在优先候选列表中。执行了两项同时探索这里讨论的特定用例的研究。第一项研究使用了经过最佳条件处理的面部图像库（g=6159）（即由高度一致的面部图像组成的图库），这一研究设计旨在确定两个所使用的软件程序组合使用的上限性能。第二项研究使用了一个由真实世界失踪人员面部图像数据集编制的图库（g=1816），该研究设计旨在告知使用通常由公共数据库组成的高度多样化面部图像时的潜在操作性能。评估了多种类型的面部近似值（重建），具有不同程度的权重调整、年龄调整或是否存在（或不存在）可见眼睛，以及这些变量的组合。总体而言，在规模更大、建模更完善的研究中，在对 159 名测试对象进行的 t=159 测试中，有 53%的测试对象的面部近似值在对高度一致的图库（g=6159）进行盲（无限制）搜索生成的候选名单的前 50 张图像中与他们的对应生活照片相匹配。在操作模型研究中，在对由操作数据集的图像填充的图库进行盲搜索生成的候选名单的前 50 张图像中，有 31%的测试对象（t=16）的面部近似值与他们的对应生活照片相匹配。正如预期的那样，候选名单的包含率随着使用人口统计过滤器而提高。在检查的性别或年龄组之间没有观察到明显不同的包含率。然而，在不同的人群中观察到了显著的差异。管理失踪和身份不明的死者记录的实体可能受益于面部识别技术和计算机生成的近似值的配对实施，作为本研究中讨论的特定设想用例的综合调查策略的一部分。
