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Phase-based video motion processing

ACM Transactions on Graphics · 2013 · Vol. 32(4) · pp. 1–10

Abstract

We introduce a technique to manipulate small movements in videos based on an analysis of motion in complex-valued image pyramids. Phase variations of the coefficients of a complex-valued steerable pyramid over time correspond to motion, and can be temporally processed and amplified to reveal imperceptible motions, or attenuated to remove distracting changes. This processing does not involve the computation of optical flow, and in comparison to the previous Eulerian Video Magnification method it supports larger amplification factors and is significantly less sensitive to noise. These improved capabilities broaden the set of applications for motion processing in videos. We demonstrate the advantages of this approach on synthetic and natural video sequences, and explore applications in scientific analysis, visualization and video enhancement.

Image and Signal Denoising MethodsAdvanced Image Processing TechniquesDigital Holography and MicroscopyComputer scienceComputer visionArtificial intelligenceOptical flowMotion (physics)Video processingVisualizationMotion analysisSet (abstract data type)Image processing

Funding

  • National Science Foundation
  • U.S. Department of Defense
  • Microsoft Research
  • Defense Advanced Research Projects Agency
  • National Defense Science and Engineering Graduate
Citations
763
FWCI
22.09
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18
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References
Microsaccades: Small steps on a long way
Vision Research · 2009 · 540 citations
Eulerian video magnification for revealing subtle changes in the world
ACM Transactions on Graphics · 2012 · 1,250 citations
Computation of component image velocity from local phase information
International Journal of Computer Vision · 1990 · 1,059 citations
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision · 2000 · 1,820 citations
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