# Camera Measurement of Physiological Vital Signs

arXiv: https://arxiv.org/abs/2111.11547 · HTML: https://mlsanity.com/paper/2111.11547/

## Key facts

- Cited by 49 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 187 references that are in the map.
- First posted on arXiv 22 Nov 2021.

## Builds on (most cited first, 30 of 30)

- [Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks](https://mlsanity.com/paper/1703.03400/) (2017)
- [Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision](https://mlsanity.com/paper/1803.11097/) (2018)
- [DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks](https://mlsanity.com/paper/1805.07888/) (2018)
- [Single Image Portrait Relighting](https://mlsanity.com/paper/1905.00824/) (2019)
- [FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals](https://mlsanity.com/paper/1901.02212/) (2019)
- [Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement](https://mlsanity.com/paper/2006.03790/) (2020)
- [Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement](https://mlsanity.com/paper/1907.11921/) (2019)
- [Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling](https://mlsanity.com/paper/2007.08213/) (2020)
- [The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video](https://mlsanity.com/paper/2111.09748/) (2021)
- [DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms](https://mlsanity.com/paper/2006.07634/) (2020)
- [PulseGAN: Learning to generate realistic pulse waveforms in remote photoplethysmography](https://mlsanity.com/paper/2006.02699/) (2020)
- [VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video](https://mlsanity.com/paper/1810.04927/) (2018)
- [Meta-rPPG: Remote Heart Rate Estimation Using a Transductive Meta-Learner](https://mlsanity.com/paper/2007.06786/) (2020)
- [A Reproducible Study on Remote Heart Rate Measurement](https://mlsanity.com/paper/1709.00962/) (2017)
- [Learning-based Video Motion Magnification](https://mlsanity.com/paper/1804.02684/) (2018)
- [Characterizing Bias in Classifiers using Generative Models](https://mlsanity.com/paper/1906.11891/) (2019)
- [The First Vision For Vitals (V4V) Challenge for Non-Contact Video-Based Physiological Estimation](https://mlsanity.com/paper/2109.10471/) (2021)
- [Video Acceleration Magnification](https://mlsanity.com/paper/1704.04186/) (2017)
- [Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars](https://mlsanity.com/paper/2010.12949/) (2020)
- [Real-time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation](https://mlsanity.com/paper/2012.15846/) (2020)
- [iPhys: An Open Non-Contact Imaging-Based Physiological Measurement Toolbox](https://mlsanity.com/paper/1901.04366/) (2019)
- [Synthetic Data for Multi-Parameter Camera-Based Physiological Sensing](https://mlsanity.com/paper/2110.04902/) (2021)
- [Can we still avoid automatic face detection?](https://mlsanity.com/paper/1602.04504/) (2016)
- [Overcoming Difficulty in Obtaining Dark-skinned Subjects for Remote-PPG by Synthetic Augmentation](https://mlsanity.com/paper/2106.06007/) (2021)
- [Diverse R-PPG: Camera-Based Heart Rate Estimation for Diverse Subject Skin-Tones and Scenes](https://mlsanity.com/paper/2010.12769/) (2020)
- [Making a Case for Learning Motion Representations with Phase](https://mlsanity.com/paper/1609.01693/) (2016)
- [On the Vector Space in Photoplethysmography Imaging](https://mlsanity.com/paper/1906.04431/) (2019)
- [Multispectral Video Fusion for Non-contact Monitoring of Respiratory Rate and Apnea](https://mlsanity.com/paper/2004.09834/) (2020)
- [Learning Higher-Order Dynamics in Video-Based Cardiac Measurement](https://mlsanity.com/paper/2110.03690/) (2021)
- [Non-contact hemodynamic imaging reveals the jugular venous pulse waveform](https://mlsanity.com/paper/1604.05213/) (2016)

## Built on by (most cited first, 30 of 49)

- [rPPG-Toolbox: Deep Remote PPG Toolbox](https://mlsanity.com/paper/2210.00716/) (2022)
- [MMPD: Multi-Domain Mobile Video Physiology Dataset](https://mlsanity.com/paper/2302.03840/) (2023)
- [Non-Contrastive Unsupervised Learning of Physiological Signals from Video](https://mlsanity.com/paper/2303.07944/) (2023)
- [Neuron Structure Modeling for Generalizable Remote Physiological Measurement](https://mlsanity.com/paper/2303.05955/) (2023)
- [RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention](https://mlsanity.com/paper/2402.12788/) (2024)
- [SCAMPS: Synthetics for Camera Measurement of Physiological Signals](https://mlsanity.com/paper/2206.04197/) (2022)
- [Facial Video-based Remote Physiological Measurement via Self-supervised Learning](https://mlsanity.com/paper/2210.15401/) (2022)
- [RhythmMamba: Fast, Lightweight, and Accurate Remote Physiological Measurement](https://mlsanity.com/paper/2404.06483/) (2024)
- [Spiking-PhysFormer: Camera-Based Remote Photoplethysmography with Parallel Spike-driven Transformer](https://mlsanity.com/paper/2402.04798/) (2024)
- [BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurements](https://mlsanity.com/paper/2303.11573/) (2023)
- [Motion Matters: Neural Motion Transfer for Better Camera Physiological Measurement](https://mlsanity.com/paper/2303.12059/) (2023)
- [How Suboptimal is Training rPPG Models with Videos and Targets from Different Body Sites?](https://mlsanity.com/paper/2403.10582/) (2024)
- [Synthetic Data in Healthcare](https://mlsanity.com/paper/2304.03243/) (2023)
- [Federated Remote Physiological Measurement with Imperfect Data](https://mlsanity.com/paper/2203.05759/) (2022)
- [Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation](https://mlsanity.com/paper/2404.09378/) (2024)
- [Bi-TTA: Bidirectional Test-Time Adapter for Remote Physiological Measurement](https://mlsanity.com/paper/2409.17316/) (2024)
- [Summit Vitals: Multi-Camera and Multi-Signal Biosensing at High Altitudes](https://mlsanity.com/paper/2409.19223/) (2024)
- [SympCam: Remote Optical Measurement of Sympathetic Arousal](https://mlsanity.com/paper/2410.20552/) (2024)
- [MSPM: A Multi-Site Physiological Monitoring Dataset for Remote Pulse, Respiration, and Blood Pressure Estimation](https://mlsanity.com/paper/2402.02224/) (2024)
- [SleepVST: Sleep Staging from Near-Infrared Video Signals using Pre-Trained Transformers](https://mlsanity.com/paper/2404.03831/) (2024)
- [Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin Tones](https://mlsanity.com/paper/2404.05003/) (2024)
- [Resolve Domain Conflicts for Generalizable Remote Physiological Measurement](https://mlsanity.com/paper/2404.07855/) (2024)
- [VitalVideos-Europe: A dataset of face videos with PPG and blood pressure ground truths](https://mlsanity.com/paper/2306.11891/) (2023)
- [Toward Motion Robustness: A masked attention regularization framework in remote photoplethysmography](https://mlsanity.com/paper/2407.06653/) (2024)
- [Non-Contact Health Monitoring During Daily Personal Care Routines](https://mlsanity.com/paper/2506.09718/) (2025)
- [SiNC+: Adaptive Camera-Based Vitals with Unsupervised Learning of Periodic Signals](https://mlsanity.com/paper/2404.13449/) (2024)
- [Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify Inference](https://mlsanity.com/paper/2407.13974/) (2024)
- [Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models](https://mlsanity.com/paper/2503.17269/) (2025)
- [Memory-efficient Low-latency Remote Photoplethysmography through Temporal-Spatial State Space Duality](https://mlsanity.com/paper/2504.01774/) (2025)
- [Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation](https://mlsanity.com/paper/2303.06452/) (2023)

## Abstract (arXiv)

The need for remote tools for healthcare monitoring has never been more apparent. Camera measurement of vital signs leverages imaging devices to compute physiological changes by analyzing images of the human body. Building on advances in optics, machine learning, computer vision and medicine these techniques have progressed significantly since the invention of digital cameras. This paper presents a comprehensive survey of camera measurement of physiological vital signs, describing they vital signs that can be measured and the computational techniques for doing so. I cover both clinical and non-clinical applications and the challenges that need to be overcome for these applications to advance from proofs-of-concept. Finally, I describe the current resources (datasets and code) available to the research community and provide a comprehensive webpage (https://cameravitals.github.io/) with links to these resource and a categorized list of all the papers referenced in this article.