Computation of component image velocity from local phase information
International Journal of Computer Vision
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
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International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
The steerable pyramid: a flexible architecture for multi-scale derivative computation
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ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2006 Papers
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
Technical Section: Real-time temporal shaping of high-speed video streams
Computers and Graphics
A high-quality video denoising algorithm based on reliable motion estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Eulerian video magnification for revealing subtle changes in the world
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Selectively de-animating video
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Motion denoising with application to time-lapse photography
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Shiftable multiscale transforms
IEEE Transactions on Information Theory - Part 2
A phase-based approach to the estimation of the optical flow field using spatial filtering
IEEE Transactions on Neural Networks
Joint view expansion and filtering for automultiscopic 3D displays
ACM Transactions on Graphics (TOG)
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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.