TriModal Face Detection Dataset

TMFD Dataset addresses the lack of available depth and thermal face detection benchmarks. The corresponding depth and thermal data frames accompany each RGB image in the dataset. The dataset encompasses a wide range of variations. The samples include different numbers of people in the scene, different individuals, various types of backgrounds, varying distances of measurement, and wearable accessories worn by the individuals, such as hoodies, headphones, hats, glasses, and face masks. Additionally, the dataset includes different types of illumination in the scene. The dataset is categorized into three separate groups based on the complexity and difficulty level of face detection. The first subset represents the easiest detection conditions, with images containing a single person against a simple background. The sensor is positioned close to the target. This subset consists of 781 images for each modality. The second group represents medium detection conditions. The sensor placement remains the same as in the first subset, but additional variety is introduced. Individuals are captured wearing accessories that serve as obstacles to make detection more challenging. These accessories include hoodies, headphones, hats, and glasses. The second group also includes images with multiple persons in the scene to test the performance of multiple face detection. There are 965 images for each modality in this group. The last group represents the most challenging images for detection. In this case, the sensor is placed further away from the target. The scenes feature various obstacles, such as computer screens, plants, desks, and chairs, with individuals interacting with them. The presence of singular and plural individuals is also included. A distinct subset within this collection consists of images from a previous, easier scene, but with the addition of face mask usage to increase the difficulty of the prediction task. This particular group contains 1062 images for each modality. This database may be used for non-commercial research purpose only. If you publish material based on this database, we request you to include a reference to: Mucha W., Kampel M. (2022) “Depth and Thermal Images in Face Detection – A Detailed Comparison Between Image Modalities”, The 5th International Conference on Machine Vision and Applications (ICMVA 2022), February 18-20, 2022, Singapore https://doi.org/10.1145/3523111.3523114TMFD数据集（TMFD Dataset）针对当前深度与热成像人脸检测基准数据集匮乏的痛点而构建。数据集中每一张RGB图像均配套提供对应的深度数据帧与热成像数据帧。该数据集涵盖丰富多样的场景变化维度：样本包含场景中不同的人数、各异的个体、多样的背景类型、不同的测量距离，以及个体佩戴的可穿戴配饰，例如连帽衫、耳机、帽子、眼镜与口罩。此外，数据集还覆盖了场景中不同类型的光照条件。 数据集依据人脸检测的复杂度与难度等级，划分为三个独立组别。第一子集对应最简易的检测场景：图像仅包含单一个体，背景简洁，传感器贴近目标采集。该子集的每一种模态（modality）均包含781张图像。第二组别对应中等难度的检测场景：传感器部署位置与第一子集一致，但新增了更多样化的干扰因素——个体佩戴会对检测构成阻碍的配饰，包括连帽衫、耳机、帽子与眼镜；同时该组别还包含场景中存在多个人体的图像，用于测试多人脸检测算法的性能。该组别每一种模态均包含965张图像。第三组别对应难度最高的检测场景：此时传感器远离目标采集，场景中存在各类干扰物，例如电脑屏幕、绿植、书桌与座椅，且个体可与这些物品进行交互；该场景同时包含单个人体与多个人体的情况。该集合中还设有一个独立子场景：沿用此前的简易采集场景，但新增了佩戴口罩的设置，以此提升检测任务的难度。该特定组别每一种模态均包含1062张图像。 本数据库仅可用于非商业性研究用途。若您基于该数据库发表研究成果，请务必引用如下文献：Mucha W., Kampel M. (2022) "Depth and Thermal Images in Face Detection – A Detailed Comparison Between Image Modalities", 第5届国际机器视觉与应用会议（ICMVA 2022），2022年2月18-20日，新加坡 https://doi.org/10.1145/3523111.3523114