Bio

Katherine Bouman received a B.S.E. in Electrical Engineering from University of Michigan, Ann Arbor, MI in 2011 respectively and an S.M. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), Cambridge, MA in 2013. She is currently a Ph.D. candidate in the Computer Vision group at MIT, working under the supervision of Prof. William Freeman. Katherine is the recipient of the NSF Graduate Fellowship, the Irwin Mark Jacobs and Joan Klein Jacobs Presidential Fellowship, and is a Goldwater Scholar. Her research interests include computer vision, computational photography, and inverse imaging algorithms.

Visual Vibrometry: Estimating Material Properties from Small Motions in Video

Visual Vibrometry: Estimating Material Properties from Small Motions in Video

The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering. We have connected fundamentals of vibration mechanics with computer vision techniques in order to infer material properties from small, often imperceptible motion in video. Objects tend to vibrate in a set of preferred modes. The shapes and frequencies of these modes depend on the structure and material properties of an object. Focusing on the case where geometry is known or fixed, we have shown how information about an object’s modes of vibration can be extracted from video and used to make inferences about that object’s material properties. We demonstrate our approach by estimating material properties for a variety of rods and fabrics by passively observing their motion in high-speed and regular framerate video.