Image Processing for Motion Magnification
This work addresses the need to enhance human visual perception of small motions in videos, but it appears incremental as it builds on existing Phase-Based Motion Magnification methods.
The paper tackles the problem of making subtle motions in videos more visible by proposing a numerical technique based on Phase-Based Motion Magnification that analyzes video sequences in the Fourier Domain using the Fourier Shifting Property, with preliminary experiments conducted on synthetic images.
Motion Magnification (MM) is a collection of relative recent techniques within the realm of Image Processing. The main motivation of introducing these techniques in to support the human visual system to capture relevant displacements of an object of interest; these motions can be in object color and in object location. In fact, the goal is to opportunely process a video sequence to obtain as output a new video in which motions are magnified and visible to the viewer. We propose a numerical technique using the Phase-Based Motion Magnification which analyses the video sequence in the Fourier Domain and rely on the Fourier Shifting Property. We describe the mathematical foundation of this method and the corresponding implementation in a numerical algorithm. We present preliminary experiments, focusing on some basic test made up using synthetic images.