论文标题
一个新颖的完全注释的热红外面部数据集：记录在各种环境条件下和镜头距离的距离
A Novel Fully Annotated Thermal Infrared Face Dataset: Recorded in Various Environment Conditions and Distances From The Camera
论文作者
论文摘要
面部热量成像是红外热成像中最受欢迎的研究领域之一，在医疗，监视和环境监测中采用了不同的应用。但是，与视觉范围中的面部图像相反，面部热图像缺乏公共数据集是该领域研究改进的障碍。热面图像仍然是一个相对较新的研究领域，要在不同的域中进行评估和研究。当前的热面数据集在受试者与摄像机的距离，环境温度变化和面部地标的本地化方面受到限制。我们通过呈现一个新的面部热力计数据集来解决这些空白。本文为知识体体做出了两个主要贡献。首先，它对面部热量成像中当前的公共数据集进行了全面的审查和比较。其次，它介绍并研究了一个关于面部热量成像的新型公共数据集，我们称其为夏洛特 - 地表。 Charlotte-Thermalface在不同的热条件下包含10000多个红外热图像，距相机几个距离和不同的头部位置。在捕获每个图像时，用面部标志，环境温度，相对湿度，房间的空气速度，与相机的距离以及主题热感觉完全注释数据。我们的数据集是第一个在不同的热条件下以每个受试者的热感知的注释的公开可用的热数据集，也是原始16位格式的少数数据集之一。最后，我们对数据集进行了初步分析，以显示面部热量成像中热条件的适用性和重要性。完整的数据集（包括注释）可以在https://github.com/tecsar-uncc/uncc-thermalface上自由使用。
Facial thermography is one of the most popular research areas in infrared thermal imaging, with diverse applications in medical, surveillance, and environmental monitoring. However, in contrast to facial imagery in the visual spectrum, the lack of public datasets on facial thermal images is an obstacle to research improvement in this area. Thermal face imagery is still a relatively new research area to be evaluated and studied in different domains.The current thermal face datasets are limited in regards to the subjects' distance from the camera, the ambient temperature variation, and facial landmarks' localization. We address these gaps by presenting a new facial thermography dataset. This article makes two main contributions to the body of knowledge. First, it presents a comprehensive review and comparison of current public datasets in facial thermography. Second, it introduces and studies a novel public dataset on facial thermography, which we call it Charlotte-ThermalFace. Charlotte-ThermalFace contains more than10000 infrared thermal images in varying thermal conditions, several distances from the camera, and different head positions. The data is fully annotated with the facial landmarks, ambient temperature, relative humidity, the air speed of the room, distance to the camera, and subject thermal sensation at the time of capturing each image. Our dataset is the first publicly available thermal dataset annotated with the thermal sensation of each subject in different thermal conditions and one of the few datasets in raw 16-bit format. Finally, we present a preliminary analysis of the dataset to show the applicability and importance of the thermal conditions in facial thermography. The full dataset, including annotations, are freely available for research purpose at https://github.com/TeCSAR-UNCC/UNCC-ThermalFace
