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An overview of Eulerian video motion magnification methods

  • Ahmed Mohamed Ahmed
  • , Mohamed Abdelrazek
  • , Sunil Aryal
  • , Thanh Thi Nguyen

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The concept of video motion magnification has become increasingly relevant due to its ability to detect small and invisible motions that can be of great value in a variety of applications. A variety of approaches have been developed to magnify these motions and variations. While both Eulerian and Lagrangian processing methods are widely used for motion magnification, Eulerian approaches are more commonly employed due to their lower computational cost. This paper provides an overview of the powerful Eulerian motion magnification techniques. We begin with a brief introduction to technical concepts associated with Eulerian motion techniques such as pyramids and filters in image processing. Additionally, we provide a comparison between the Lagrangian and Eulerian perspectives, followed by a comprehensive overview of the various Eulerian motion magnification (EVM) techniques available. Finally, we present implementation results and a comparative analysis of some of the Eulerian motion techniques.

Original languageEnglish
Pages (from-to)145-163
Number of pages19
JournalComputers and Graphics (Pergamon)
Volume117
DOIs
Publication statusPublished - Dec 2023
Externally publishedYes

Keywords

  • Deep convolutional neural network
  • Eulerian
  • Lagrangian
  • Motion magnification

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