The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation: Wu, Hao-Yu, Michael Rubinstein, Eugene Shih, John Guttag, Frédo Durand, and William Freeman. “Eulerian Video Magnification for Revealing Subtle Changes in the World.” ACM Transactions on Graphics 31, no. 4 (July 1, 2012): 1–8. As Published: http://dx.doi.org/10.1145/2185520.2185561 Publisher: Association for Computing Machinery Persistent URL: http://hdl.handle.net/1721.1/86955 Version: Author’s final manuscript: final author’s manuscript post peer review, without publisher’s formatting or copy editing Terms of use: Creative Commons Attribution-Noncommercial-Share Alike Figure 1: An example of using our Eulerian Video Magnification framework for visualizing the human pulse. (a) Four frames from the original video sequence (face). (b) The same four frames with the subject's pulse signal amplified. (c) A vertical scan line from the input (top) and output (bottom) videos plotted over time shows how our method amplifies the periodic color variation. In the input sequence the signal is imperceptible, but in the magnified sequence the variation is clear. The complete sequence is available in the supplemental video. ### 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 temporal frequencies selected by the user. CR Categories: I.4.7 [Image Processing and Computer Vision]: Scene Analysis—Time-varying Imagery; Keywords: video-based rendering, spatio-temporal analysis, Eulerian motion, motion magnification Links: DL PDF WEB ## 1 Introduction The human visual system has limited spatio-temporal sensitivity, but many signals that fall below this capacity can be informative. For example, human skin color varies slightly with blood circulation. This variation, while invisible to the naked eye, can be exploited to extract pulse rate [Verkruysse et al. 2008; Poh et al. 2010; Philips 2011]. Similarly, motion with low spatial amplitude, while hard or impossible for humans to see, can beThe MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation: Wu, Hao-Yu, Michael Rubinstein, Eugene Shih, John Guttag, Frédo Durand, and William Freeman. “Eulerian Video Magnification for Revealing Subtle Changes in the World.” ACM Transactions on Graphics 31, no. 4 (July 1, 2012): 1–8. As Published: http://dx.doi.org/10.1145/2185520.2185561 Publisher: Association for Computing Machinery Persistent URL: http://hdl.handle.net/1721.1/86955 Version: Author’s final manuscript: final author’s manuscript post peer review, without publisher’s formatting or copy editing Terms of use: Creative Commons Attribution-Noncommercial-Share Alike Figure 1: An example of using our Eulerian Video Magnification framework for visualizing the human pulse. (a) Four frames from the original video sequence (face). (b) The same four frames with the subject's pulse signal amplified. (c) A vertical scan line from the input (top) and output (bottom) videos plotted over time shows how our method amplifies the periodic color variation. In the input sequence the signal is imperceptible, but in the magnified sequence the variation is clear. The complete sequence is available in the supplemental video. ### 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 temporal frequencies selected by the user. CR Categories: I.4.7 [Image Processing and Computer Vision]: Scene Analysis—Time-varying Imagery; Keywords: video-based rendering, spatio-temporal analysis, Eulerian motion, motion magnification Links: DL PDF WEB ## 1 Introduction The human visual system has limited spatio-temporal sensitivity, but many signals that fall below this capacity can be informative. For example, human skin color varies slightly with blood circulation. This variation, while invisible to the naked eye, can be exploited to extract pulse rate [Verkruysse et al. 2008; Poh et al. 2010; Philips 2011]. Similarly, motion with low spatial amplitude, while hard or impossible for humans to see, can be