论文标题
RPPG-Toolbox：深远程PPG工具箱
rPPG-Toolbox: Deep Remote PPG Toolbox
论文作者
论文摘要
基于相机的生理测量是计算机视觉的快速增长领域。远程光摄影学（RPPG）利用成像设备（例如，相机）通过光摄影学测量外周血体积脉冲（BVP），并通过网络摄像头和智能手机启用心脏测量。但是，该任务是不乏味的，具有重要的预处理，建模和后处理步骤，以获得最新的结果。结果的复制和新模型的基准测试对于科学进步至关重要。但是，与许多深度学习的应用一样，可靠的代码库并不容易找到或使用。我们提供了一个综合的工具箱RPPG-Toolbox，其中包含无监督和监督的RPPG模型，并支持公共基准数据集，数据增强和系统评估：\ url {https：//github.com/ubicoltab/rppg-toomplab/rppg-toollab/rppg-toolbob}}
Camera-based physiological measurement is a fast growing field of computer vision. Remote photoplethysmography (rPPG) utilizes imaging devices (e.g., cameras) to measure the peripheral blood volume pulse (BVP) via photoplethysmography, and enables cardiac measurement via webcams and smartphones. However, the task is non-trivial with important pre-processing, modeling, and post-processing steps required to obtain state-of-the-art results. Replication of results and benchmarking of new models is critical for scientific progress; however, as with many other applications of deep learning, reliable codebases are not easy to find or use. We present a comprehensive toolbox, rPPG-Toolbox, that contains unsupervised and supervised rPPG models with support for public benchmark datasets, data augmentation, and systematic evaluation: \url{https://github.com/ubicomplab/rPPG-Toolbox}
