Bill Freeman of MIT will present “A Big World of Tiny Motions” in the Distinguished Lecture series, Wednesday, October 21, 2015 Computer Science Building, Room 151 from 4:00pm to 5:00pm. A reception will be held in the Atrium at 3:40 pm.
Abstract. We have developed a “motion microscope” to visualize small motions by synthesizing a video with the desired motions amplified. The project began as an algorithm to amplify small color changes in videos, allowing color changes from blood flow to be visualized. Modifications to this algorithm allow small motions to be amplified in a video. I’ll describe the algorithms, and show color-magnified videos of adults and babies, and motion-magnified videos of throats, pipes, cars, smoke, and pregnant bellies. The motion microscope lets us see the world of tiny motions, and it may be useful in areas of science and engineering.
Having this tool led us to explore other vision problems involving tiny motions. I’ll describe recent work in analyzing fluid flow and depth by exploiting small motions in video or stereo video sequences caused by refraction of turbulent air flow (joint work with the authors below and Tianfan Xue, Anat Levin, and Hossein Mobahi). We have also developed a “visual microphone” to record sounds by watching objects, like a bag of chips, vibrate (joint with the authors below and Abe Davis and Gautam Mysore).
Collaborators: Michael Rubinstein, Neal Wadhwa, and co-PI Fredo Durand.
For project web pages and radio segments, visit the events page.
TED or TEDx talks by students:
See invisible motion, hear silent sounds
How a silent video can reveal sound: Abe Davis’ knockout tech demo at TED2015
Bio: William T. Freeman is the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) there. He is currently on a partial leave from MIT, starting a computer vision group at Google in Cambridge, MA.
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, and test-of-time awards for papers from 1990 and 1995. Previous research topics include steerable filters and pyramids, orientation histograms, the generic viewpoint assumption, color constancy, computer vision for computer games, and belief propagation in networks with loops.
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 for CVPR 2013.