Learning-based Video Motion Magnification

Understand

Video motion magnification techniques allow us to see small motions previously invisible to the naked eyes, such as those of vibrating airplane wings, or swaying buildings under the influence of the wind.

• Because the motion is small, the magnification results are prone to noise or excessive blurring.
• The state of the art relies on hand-designed filters to extract representations that may not be optimal.
• In this paper, we seek to learn the filters directly from examples using deep convolutional neural networks.