A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset

Domenick Poster, Matthew D. Thielke, R. Nguyen, Srinivasan Rajaraman, Xing Di, Cedric Nimpa Fondje, Vishal M. Patel, Nathan J. Short, B. Riggan, N. Nasrabadi, Shuowen Hu
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引用次数: 29

Abstract

Thermal face imagery, which captures the naturally emitted heat from the face, is limited in availability compared to face imagery in the visible spectrum. To help address this scarcity of thermal face imagery for research and algorithm development, we present the DEVCOM Army Research Laboratory Visible-Thermal Face Dataset (ARL-VTF). With over 500,000 images from 395 subjects, the ARL-VTF dataset represents, to the best of our knowledge, the largest collection of paired visible and thermal face images to date. The data was captured using a modern long wave infrared (LWIR) camera mounted alongside a stereo setup of three visible spectrum cameras. Variability in expressions, pose, and eyewear has been systematically recorded. The dataset has been curated with extensive annotations, metadata, and standardized protocols for evaluation. Furthermore, this paper presents extensive benchmark results and analysis on thermal face landmark detection and thermal-to-visible face verification by evaluating state-of-the-art models on the ARL-VTF dataset.
一个大规模的、时间同步的可见光和热人脸数据集
与可见光谱的人脸图像相比,热人脸图像的可用性有限,它捕获了面部自然发射的热量。为了帮助解决研究和算法开发中热人脸图像的短缺问题,我们提出了DEVCOM陆军研究实验室可见热人脸数据集(ARL-VTF)。据我们所知,ARL-VTF数据集拥有来自395名受试者的50多万张图像,是迄今为止最大的配对可见光和热人脸图像集。这些数据是用一台现代的长波红外(LWIR)相机捕获的,它安装在由三台可见光谱相机组成的立体装置上。表情、姿势和眼镜的变化被系统地记录下来。该数据集包含大量注释、元数据和用于评估的标准化协议。此外,本文通过评估ARL-VTF数据集上最先进的模型,介绍了热人脸地标检测和热到可见人脸验证的广泛基准测试结果和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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