Visual Vibrometry: Estimating Material Properties from Small Motions in Video
Name
Freeman_Virtual Vibrometry.pdf
Size
6.67 MB
Format
Adobe PDF
Checksum (MD5)
11534d3a1c89485fdd6dd6c8d94cbfa1
Author(s)
Davis, Myers Abraham
Bouman, Katherine L.
Chen, Justin Gejune
Rubinstein, Michael
Durand, Fredo
Freeman, William T.
Date Issued
June 2015
Journal
Proceedings of the 2015 Computer Vision and Pattern Recognition Conference
Publisher
Computer Vision Foundation
Citation
Davis, Abe, Katherine L. Bouman, Justin G. Chen, Michael Rubinstein, Fredo Durand, and William T. Freeman. "Visual Vibrometry: Estimating Material Properties from Small Motions in Video." 2015 Computer Vision and Pattern Recognition Conference (June 2015).
Version
Author's final manuscript
Abstract
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering. This paper connects 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 show 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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Davis_Visual_Vibrometry_Estimating_2015_CVPR_paper.pdf
