articleTop 1% cited
Eulerian video magnification for revealing subtle changes in the world
ACM Transactions on Graphics · 2012 · Vol. 31(4) · pp. 1–8
Haoyu Wu✉Michael RubinsteinEugene Shih(Cambridge Quantum Computing (United Kingdom))John V. GuttagFrédo DurandWilliam T. Freeman
Abstract
Our goal is to reveal temporal variations in videos that are difficult or impossible to see with the naked eye and display them in an indicative manner. Our method, which we call Eulerian Video Magnification, takes a standard video sequence as input, and applies spatial decomposition, followed by temporal filtering to the frames. The resulting signal is then amplified to reveal hidden information. Using our method, we are able to visualize the flow of blood as it fills the face and also to amplify and reveal small motions. Our technique can run in real time to show phenomena occurring at the temporal frequencies selected by the user.
Non-Invasive Vital Sign MonitoringAnomaly Detection Techniques and ApplicationsTime Series Analysis and ForecastingEulerian pathComputer scienceComputer visionArtificial intelligenceMagnificationComputer graphics (images)SIGNAL (programming language)Face (sociological concept)Flow (mathematics)Mathematics
Funding
- National Science Foundation
Citations
1,250
FWCI
33.50
field-weighted impact
References
12
Percentile
100%
vs. same field & year
Citations per year
Cited by
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References
Non-contact, automated cardiac pulse measurements using video imaging and blind source separation
Optics Express · 2010 · 1,577 citations
Remote plethysmographic imaging using ambient light
Optics Express · 2008 · 1,631 citations
<title>Determining Optical Flow</title>
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1981 · 7,482 citations
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