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Motion Magnification

Motion magnification is a technique that acts like a microscope for visual motion. It can amplify subtle motions in a video sequence, allowing for visualization of deformations that would otherwise be invisible. To achieve motion magnification, we need to accurately measure visual motions, and group the pixels to be modified.

There are different approaches to motion magnification, such as Lagrangian and Eulerian methods. Lagrangian methods track the trajectories of moving objects and exaggerate them, while Eulerian methods manipulate the motions at fixed positions. Eulerian methods can be further divided into linear and phase-based methods. Linear methods apply a temporal bandpass filter to boost the linear term of a Taylor series expansion of the displacement function, while phase-based methods use complex wavelet transforms to manipulate the phase of the signal.

Motion magnification has various applications, such as measuring the human pulse, visualizing the heat plume of candles, revealing the oscillations of a wine glass, and detecting structural defects.

Papers

Showing 2130 of 38 papers

TitleStatusHype
Motion Magnification Algorithms for Video-Based Breathing Monitoring0
Lagrangian Motion Magnification with Double Sparse Optical Flow DecompositionCode0
Motion-Adjustable Neural Implicit Video Representation0
FLAVR: Flow-Agnostic Video Representations for Fast Frame InterpolationCode1
Surgical Video Motion Magnification with Suppression of Instrument Artefacts0
Little Motion, Big Results: Using Motion Magnification to Reveal Subtle Tremors in Infants0
Unsupervised Magnification of Posture Deviations Across Subjects0
Autonomous Apex Detection and Micro-Expression Recognition using Proposed Diagonal Planes0
A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework0
Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture0
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