Emotion analysis of students plays an important role in teaching effect evaluation. To develop robust algorithms for emotion analysis of students, a database from real classrooms is required. However, most existing databases were collected from adults and constructed in laboratory settings. In this article, we present a manually-annotated facial action unit database from juveniles in real classrooms. Our database has three main characteristics: (1) it provides numerous education-related action units data from primary and high schools, complementing the vacancy of the publicly available educational action unit databases; (2) it contains 256,220 manually-annotated facial images of 1,796 juveniles, frame-by-frame annotated with 12 action units and 6-level intensities for each action unit; (3) it covers many challenges in the wild, including various head poses, low facial resolution, illuminations, and occlusions, supplementing action unit databases in the wild for research. The baselines for action unit detection and action unit intensity estimation are provided for future references. Especially, we apply the weighted balance loss to solve imbalances within and between labels. Our database will be available to the research community: http://www.dlc.sjtu.edu.cn/rfau .

中文翻译：

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RFAU：真实教室中面部动作单元分析的数据库

学生情绪分析在教学效果评价中起着重要作用。为了开发强大的学生情绪分析算法，需要一个来自真实教室的数据库。然而，大多数现有数据库都是从成年人那里收集的，并在实验室环境中构建。在本文中，我们展示了一个手动注释的真实教室中青少年的面部动作单元数据库。我们的数据库具有三个主要特点：（1）它提供了来自小学和高中的大量与教育相关的行动单元数据，补充了公开可用的教育行动单元数据库的空缺；(2) 包含1796名青少年的256220张人工标注的面部图像，逐帧标注12个动作单元，每个动作单元6级强度；(3) 它涵盖了野外的许多挑战，包括各种头部姿势、低面部分辨率、照明和遮挡，补充野外的动作单元数据库以供研究。提供了动作单元检测和动作单元强度估计的基线以供将来参考。特别是，我们应用加权平衡损失来解决不平衡内和标签之间。我们的数据库将提供给研究界：http://www.dlc.sjtu.edu.cn/rfau .