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Deep Insights of Learning based Micro Expression Recognition: A Perspective on Promises, Challenges and Research Needs

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posted on 03.03.2022, 05:27 authored by Monu VermaMonu Verma, Santosh kumar Vipparthi
Micro expression recognition (MER) is a very challenging area of research due to its intrinsic nature and finegrained changes. In the literature, the problem of MER has been solved through handcrafted/descriptor-based techniques. However, in recent times, deep learning (DL) based techniques have been adopted to gain higher performance for MER. Also, rich survey articles on MER are available by summarizing the datasets, experimental settings, conventional and deep learning methods. In contrast, these studies lack the ability to convey the impact of network design paradigms and experimental setting strategies for DL based MER. Therefore, this paper aims to provide a deep insight into the DL-based MER frameworks with a perspective on promises in network model designing, experimental strategies, challenges, and research needs. Also, the detailed categorization of available MER frameworks is presented in various aspects of model design and technical characteristics. Moreover, an empirical analysis of the experimental and validation protocols adopted by MER methods is presented. The challenges mentioned earlier and network design strategies may assist the affective computing research community in forge ahead in MER research. Finally, we point out the future directions, research needs and draw our conclusions.

History

Email Address of Submitting Author

monuverma.cv@gmail.com

ORCID of Submitting Author

https://orcid.org/ 0000-0003-4962-882X

Submitting Author's Institution

university of miami

Submitting Author's Country

United States of America