• DocumentCode
    3672627
  • Title

    Visual vibrometry: Estimating material properties from small motions in video

  • Author

    Abe Davis;Katherine L. Bouman;Justin G. Chen;Michael Rubinstein;Frédo Durand;William T. Freeman

  • Author_Institution
    Massachusetts Institute of Technology, USA
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    5335
  • Lastpage
    5343
  • 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.
  • Keywords
    "Material properties","Resonant frequency","Vibrations","Shape","Geometry","Fabrics","Aluminum"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2015.7299171
  • Filename
    7299171