AXIOM Face Database

The main purpose of building the AXIOM Face Database was to gather challenging pictures for fine-tuning object recognition algorithms for facial analysis based on state-of-the-art machine learning techniques. Additionally, the database was also developed with the aim of enriching with supplementary human-annotated pictures existing datasets that are used for training demographic face estimation algorithms. By taking into account these initial requirements, a team in the University of Siena collected pictures of faces of people who previously provided their written consent to participate in the experiment. The AXIOM Face Database includes both frontal and non-frontal images captured in multiple poses using different illumination conditions. More particularly, the database features 123 multiethnic individuals for whom 25 pictures were captured showing partially occluded faces coming from wearing glasses, sunglasses, caps, hats or scarves.构建AXIOM人脸数据库（AXIOM Face Database）的核心目标，是收集具有挑战性的人脸图像，用于微调基于最先进机器学习技术的面部分析目标识别算法。此外，该数据库的研发还旨在为现有用于训练人口统计学人脸估计算法的数据集补充人工标注人脸图像，以充实其数据资源。 基于上述初始研发需求，锡耶纳大学（University of Siena）的一支研究团队收集了此前已签署书面知情同意书参与本实验的志愿者的人脸图像。AXIOM人脸数据库包含不同姿态、不同光照条件下拍摄的正面与非正面人脸图像。更具体而言，该数据库涵盖123名多种族志愿者，每位志愿者均采集了25张人脸图像，其中部分人脸存在因佩戴眼镜、太阳镜、帽子或围巾导致的遮挡情况。