Abstract:I will describe two recent projects that both seek to reveal things in images or videos that are otherwise difficult to see. Video magnification amplifies small motion or color changes in videos, allowing a real-time "microscope" to view otherwise invisible changes. (Joint work with Michael Rubinstein, Hao-Yu Wu, Neal Wadhwa, Eugene Shih, John Guttag, and Fredo Durand). The second project, accidental camera, reveals information about structures outside the frame of a photograph or a video through the relatively common formation of accidental cameras. (Joint work with Antonio Torralba).

Bio: William T. Freeman is Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, joining the faculty in 2001. His current research interests include machine learning applied to computer vision, Bayesian models of visual perception, and computational photography. He received outstanding paper awards at computer vision or machine learning conferences in 1997, 2006, 2009 and 2012. Previous research topics include steerable filters and pyramids, the generic viewpoint assumption, color constancy, computer vision for computer games, and bilinear models for separating style and content. He is active in the program or organizing committees of computer vision, graphics, and machine learning conferences. He was the program co-chair for ICCV 2005, and is program co-chair for CVPR
2013.