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Comparative Analysis of Facial Expression Recognition Algorithms

  • M. K. Ujjwal
  • , Sunil Parameswaran
  • , V. Guna Chowdary
  • , Varun Bharadwaj
  • , Dayananda Pruthviraja*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial expression recognition has emerged as a significant area of research in computer vision and pattern recognition due to its wide range of applications that include emotion analysis, human–computer interaction among many others. In recent times, multiple facial expression recognition algorithms have come into light. Each of these techniques employs different techniques and principles. This paper aims to provide a comprehensive analysis and comparison of these algorithms by evaluating their performance, strengths, capabilities, and limitations to provide an overall understanding of the algorithm. By doing the comparative analysis, this paper aims to facilitate a better understanding of these algorithms.

Original languageEnglish
Title of host publicationData Science and Security - Proceedings of IDSCS 2023
EditorsSamiksha Shukla, Hiroki Sayama, Joseph Varghese Kureethara, Durgesh Kumar Mishra
PublisherSpringer Science and Business Media Deutschland GmbH
Pages419-431
Number of pages13
ISBN (Print)9789819709748
DOIs
Publication statusPublished - 2024
EventInternational Conference on Data Science, Computation and Security, IDSCS 2023 - Indore, India
Duration: 02-11-202303-11-2023

Publication series

NameLecture Notes in Networks and Systems
Volume922 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Conference on Data Science, Computation and Security, IDSCS 2023
Country/TerritoryIndia
CityIndore
Period02-11-2303-11-23

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

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