PPG3D: Does 3D head tracking improve camera-based PPG estimation?
PPG3D: Does 3D head tracking improve camera-based PPG estimation?
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PPG3D：3D 头部跟踪是否可以改进基于摄像头的 PPG 估计？
DOI：
10.1109/embc44109.2020.9176065
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Kawasaki, Hiroshi
中科院分区：
文献类型：
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作者：
Nagamatsu, Genki;Nowara, Ewa Magdalena;Pai, Amruta;Veeraraghavan, Ashok;Kawasaki, Hiroshi
在过去的几年中，被称为成像光电体积描记术（iPPG）的基于相机的生命体征估计由于这种测量提供的相对简单、容易、不显眼和灵活性而引起了极大的关注。预计iPPG可以集成到自动汽车、新生儿监测和远程医疗等领域的许多新兴应用中。尽管有这种潜力，基于相机的非接触式测量的主要挑战是相机和对象之间的相对运动。当前的技术采用2D特征跟踪来减少主体和相机运动的影响，但是它们限于处理平移和平面内运动。在本文中，我们研究，第一次，3D人脸跟踪的效用，让iPPG保持强大的性能，即使在存在的平面外和大的相对运动。我们使用RGB-D摄像机从被摄体获得3D信息，并使用空间和深度信息来拟合3D人脸模型并在视频帧上跟踪模型。这使我们能够以像素级的精度估计整个视频的对应关系，即使存在平面外或大的运动。然后，我们从扭曲的视频数据中估计iPPG，以确保在用于估计的整个窗口长度上的每像素对应关系。我们的实验表明，头部运动时，鲁棒性的改善是大的。
Over the last few years, camera-based estimation of vital signs referred to as imaging photoplethysmography (iPPG) has garnered significant attention due to the relative simplicity, ease, unobtrusiveness and flexibility offered by such measurements. It is expected that iPPG may be integrated into a host of emerging applications in areas as diverse as autonomous cars, neonatal monitoring, and telemedicine. In spite of this potential, the primary challenge of non-contact camera-based measurements is the relative motion between the camera and the subjects. Current techniques employ 2D feature tracking to reduce the effect of subject and camera motion but they are limited to handling translational and in-plane motion. In this paper, we study, for the first-time, the utility of 3D face tracking to allow iPPG to retain robust performance even in presence of out-of-plane and large relative motions. We use a RGB-D camera to obtain 3D information from the subjects and use the spatial and depth information to fit a 3D face model and track the model over the video frames. This allows us to estimate correspondence over the entire video with pixel-level accuracy, even in the presence of out-of-plane or large motions. We then estimate iPPG from the warped video data that ensures per-pixel correspondence over the entire window-length used for estimation. Our experiments demonstrate improvement in robustness when head motion is large.