Abstract
The ability to amplify or reduce subtle image changes
over time is useful in contexts such as video editing, medical
video analysis, product quality control and sports. In these
contexts there is often large motion present which severely
distorts current video amplification methods that magnify
change linearly. In this work we propose a method to cope
with large motions while still magnifying small changes. We
make the following two observations: i) large motions are
linear on the temporal scale of the small changes; ii) small
changes deviate from this linearity. We ignore linear motion
and propose to magnify acceleration. Our method is pure
Eulerian and does not require any optical flow, temporal
alignment or region annotations. We link temporal secondorder derivative filtering to spatial acceleration magnification. We apply our method to moving objects where we show
motion magnification and color magnification. We provide
quantitative as well as qualitative evidence for our method
while comparing to the state-of-the-art.