The First Vision For Vitals (V4V) Challenge for Non-Contact Video-Based Physiological Estimation
| Autor: | Umur Aybars Ciftci, Ambareesh Revanur, Zhihua Li, László A. Jeni, Lijun Yin |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Alternative methods Estimation Facial expression Computer Science - Machine Learning Research groups Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Image and Video Processing (eess.IV) Computer Science - Computer Vision and Pattern Recognition Telehealth Electrical Engineering and Systems Science - Image and Video Processing Machine Learning (cs.LG) Computer Science - Computers and Society Photoplethysmogram Computers and Society (cs.CY) FOS: Electrical engineering electronic engineering information engineering Computer vision Artificial intelligence business Protocol (object-oriented programming) Video based |
| Popis: | Telehealth has the potential to offset the high demand for help during public health emergencies, such as the COVID-19 pandemic. Remote Photoplethysmography (rPPG) - the problem of non-invasively estimating blood volume variations in the microvascular tissue from video - would be well suited for these situations. Over the past few years a number of research groups have made rapid advances in remote PPG methods for estimating heart rate from digital video and obtained impressive results. How these various methods compare in naturalistic conditions, where spontaneous behavior, facial expressions, and illumination changes are present, is relatively unknown. To enable comparisons among alternative methods, the 1st Vision for Vitals Challenge (V4V) presented a novel dataset containing high-resolution videos time-locked with varied physiological signals from a diverse population. In this paper, we outline the evaluation protocol, the data used, and the results. V4V is to be held in conjunction with the 2021 International Conference on Computer Vision. ICCVw'21. V4V Dataset and Challenge: https://vision4vitals.github.io/ |
| Databáze: | OpenAIRE |
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