Recently, different researchers have found that the gallery composition of a face database can induce performance differentials to facial identification systems in which a probe image is compared against up to all stored reference images to reach a biometric decision. This negative effect is referred to as "watchlist imbalance effect". In this work, we present a method to theoretically estimate said effect for a biometric identification system given its verification performance across demographic groups and the composition of the used gallery. Further, we report results for identification experiments on differently composed demographic subsets, i.e. females and males, of the public academic MORPH database using the open-source ArcFace face recognition system. It is shown that the database composition has a huge impact on performance differentials in biometric identification systems, even if performance differentials are less pronounced in the verification scenario. This study represents the first detailed analysis of the watchlist imbalance effect which is expected to be of high interest for future research in the field of facial recognition.

中文翻译：

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人脸识别中的人口公平性：观察名单失衡效应

最近，不同的研究人员发现，人脸数据库的图库组成会导致人脸识别系统的性能差异，其中将探测图像与所有存储的参考图像进行比较，以做出生物识别决策。这种负面影响被称为“观察名单不平衡效应”。在这项工作中，我们提出了一种方法，从理论上估计生物特征识别系统的上述影响，因为它在人口群体中的验证性能和所用图库的组成。此外，我们报告了使用开源 ArcFace 人脸识别系统对公共学术 MORPH 数据库的不同组成的人口子集（即女性和男性）进行识别实验的结果。结果表明，数据库组成对生物识别系统中的性能差异有巨大影响，即使在验证场景中性能差异不那么明显。这项研究代表了对观察名单不平衡效应的首次详细分析，预计这对面部识别领域的未来研究具有重要意义。