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Frédo Durand and Willam T. Freeman. Wu, Hao-Yu, M. Eng. Massachusetts Institute of Technology Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2013-03-01T15:06:39Z 2013-03-01T15:06:39Z 2012 2012 http://hdl.handle.net/1721.1/77452 826647817 Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 68-69). Our goal is to reveal subtle yet informative signals in videos that are difficult or impossible to see with the naked eye. We can either display them in an indicative manner, or analyse them to extract important measurements, such as vital signs. Our method, which we call Eulerian Video Processing, takes a standard video sequence as input, and applies spatial decomposition, followed by temporal filtering to the frames. The resulting signals can be visually amplified to reveal hidden information, the process we called Eulerian Video Magnification. Using Eulerian Video Magnification, we are able to visualize the flow of blood as it fills the face and to amplify and reveal small motions. Our technique can be run in real time to instantly show phenomena occurring at the temporal frequencies selected by the user. Those signals can also be used to extract vital signs contactlessly. We presented a heart rate extraction system that is able to estimate heart rate of newborns from videos recorded in the real nursery environment. Our system can produce heart rate measurement that has clinical accuracy when newborns only have mild motions, and when the videos are acquired in brightly lit environments. by Hao-Yu Wu. M.Eng. S.B. 69 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Eulerian Video Processing and medical applications Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="14dde3ba-2067-4460-86b6-43776f0afb2a"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Eulerian Video Processing and medical applications</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Wu, Hao-Yu, M. Eng. Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Our goal is to reveal subtle yet informative signals in videos that are difficult or impossible to see with the naked eye. We can either display them in an indicative manner, or analyse them to extract important measurements, such as vital signs. Our method, which we call Eulerian Video Processing, takes a standard video sequence as input, and applies spatial decomposition, followed by temporal filtering to the frames. The resulting signals can be visually amplified to reveal hidden information, the process we called Eulerian Video Magnification. Using Eulerian Video Magnification, we are able to visualize the flow of blood as it fills the face and to amplify and reveal small motions. Our technique can be run in real time to instantly show phenomena occurring at the temporal frequencies selected by the user. Those signals can also be used to extract vital signs contactlessly. We presented a heart rate extraction system that is able to estimate heart rate of newborns from videos recorded in the real nursery environment. Our system can produce heart rate measurement that has clinical accuracy when newborns only have mild motions, and when the videos are acquired in brightly lit environments.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>