School of Information, University of California, Berkeley, CA, USA.
Electrical Engineering & Computer Sciences, University of California, Berkeley, CA, USA.
J Vis. 2021 Mar 1;21(3):4. doi: 10.1167/jov.21.3.4.
A relatively new type of identity theft uses morphed facial images in identification documents in which images of two individuals are digitally blended to create an image that maintains a likeness to each of the original identities. We created a set of high-quality digital morphs from passport-style photos for a diverse set of people across gender, race, and age. We then examine people's ability to detect facial morphing both in terms of determining if two side-by-side faces are of the same individual or not and in terms of identifying if a face is the result of digital morphing. We show that human participants struggle at both tasks. Even modern machine-learning-based facial recognition struggles to distinguish between an individual and their morphed version. We conclude with a hopeful note, describing a computational technique that holds some promise in recognizing that one facial image is a morphed version of another.
一种相对较新的身份盗窃形式是在身份证件中使用变形的面部图像，即将两个人的图像进行数字融合，创建一个保持与每个原始身份相似的图像。我们从护照照片中创建了一组高质量的数字变形，涵盖了不同性别、种族和年龄的人群。然后，我们研究了人们在确定并排的两张脸是否来自同一个人以及识别脸是否是数字变形的结果这两个方面检测面部变形的能力。我们发现人类参与者在这两个任务上都很吃力。即使是基于现代机器学习的面部识别技术也难以区分个体与其变形版本。最后，我们以一个有希望的说明结束，描述了一种计算技术，该技术在识别一个面部图像是另一个面部图像的变形版本方面具有一定的前景。
