DeepMag: Source Specific Motion Magnification Using Gradient Ascent

Understand

Many important physical phenomena involve subtle signals that are difficult to observe with the unaided eye, yet visualizing them can be very informative.

• Current motion magnification techniques can reveal these small temporal variations in video, but require precise prior knowledge about the target signal, and cannot deal with interference motions at a similar frequency.
• We present DeepMag an end-to-end deep neural video-processing framework based on gradient ascent that enables automated magnification of subtle color and motion signals from a specific source, even in the presence of large motions of various velocities.
• While the approach is generalizable, the advantages of DeepMag are highlighted via the task of video-based physiological visualization.