论文标题
面部识别是否在近红外光谱上也有偏见吗？
Is Facial Recognition Biased at Near-Infrared Spectrum As Well?
论文作者
论文摘要
发表的学术研究和媒体文章表明，面部识别在人群之间存在偏见。具体而言，女性，黑皮肤的人和老年人获得了不平等的表现。但是，这些已发表的研究检查了可见光谱中面部识别的偏见（VIS）。面部妆容，面部毛发，肤色和照明变化等因素归因于VIS中该技术的偏见。近红外（NIR）频谱在鲁棒性方面对诸如照明变化，面部妆容和肤色等因素具有优势。因此，值得研究近红外光谱（NIR）面部识别的偏见。这项第一项研究调查了NIR光谱上面部识别系统的偏差。为此，分别使用两个受欢迎的NIR面部图像数据集，即Casia-Face-Africa和Notre-Dame-Nivl，分别由非洲和高加索主题组成，用于研究在性别和种族中面部识别技术的偏见。有趣的是，实验结果表明在NIR谱系中性别和种族之间的公平面部识别表现。
Published academic research and media articles suggest face recognition is biased across demographics. Specifically, unequal performance is obtained for women, dark-skinned people, and older adults. However, these published studies have examined the bias of facial recognition in the visible spectrum (VIS). Factors such as facial makeup, facial hair, skin color, and illumination variation have been attributed to the bias of this technology at the VIS. The near-infrared (NIR) spectrum offers an advantage over the VIS in terms of robustness to factors such as illumination changes, facial makeup, and skin color. Therefore, it is worthwhile to investigate the bias of facial recognition at the near-infrared spectrum (NIR). This first study investigates the bias of the face recognition systems at the NIR spectrum. To this aim, two popular NIR facial image datasets namely, CASIA-Face-Africa and Notre-Dame-NIVL consisting of African and Caucasian subjects, respectively, are used to investigate the bias of facial recognition technology across gender and race. Interestingly, experimental results suggest equitable face recognition performance across gender and race at the NIR spectrum.
