Video Acceleration Magnification

TL;DR

This paper introduces a novel Eulerian video acceleration magnification technique that effectively amplifies small changes in videos with large motions without relying on optical flow or region annotations.

Contribution

It proposes a new method that magnifies acceleration instead of linear motion, handling large motions better than existing linear magnification techniques.

Findings

Effective amplification of small changes in videos with large motions.

No need for optical flow or region annotations.

Outperforms state-of-the-art methods in qualitative and quantitative tests.

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 second-order 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.