Hao-Yu Wu, Michael Rubinstein, Eugene Shih, John Guttag, Frédo Durand, William Freeman (2012)
- Reveal temporal variations (both periodic and non-periodic) in videos that are impossible to see with the naked eye
- Lower spatial frequency can be exaggerated more without introducing artifacts
- Spatial decomposition --> temporal filtering --> amplification for certain temporal frequency band of interest (e.g. heart rate)
- Both color variation and small motion
- Temporal filtering needs sufficient spatial pooling to rise above noise
- Brightness constancy assumption used
- Lagrangian: trajectory of particles tracked over time
- Computationally expensive due to accurate motion estimation and hard to make artifact-free
- Better for enhancing fine point feature motion and large amplitudes
- Eulerian: properties of a voxel evolve over time
- Motion is not explicitly estimated, but exaggerated by amplifying temporal color changes at fixed locations
- Better for smoother structures and smaller amplitudes