A survey on automatic multimodal emotion recognition in the wild

Garima Sharma, Abhinav Dhall

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

1 Citation (Scopus)

Abstract

Affective computing has been an active area of research for the past two decades. One of the major component of affective computing is automatic emotion recognition. This chapter gives a detailed overview of different emotion recognition techniques and the predominantly used signal modalities. The discussion starts with the different emotion representations and their limitations. Given that affective computing is a data-driven research area, a thorough comparison of standard emotion labelled databases is presented. Based on the source of the data, feature extraction and analysis techniques are presented for emotion recognition. Further, applications of automatic emotion recognition are discussed along with current and important issues such as privacy and fairness.

Original languageEnglish
Title of host publicationAdvances in Data Science
Subtitle of host publicationMethodologies and Applications
EditorsGloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain
Place of PublicationCham Switzerland
PublisherSpringer
Chapter3
Pages35-64
Number of pages30
ISBN (Electronic)9783030518707
ISBN (Print)9783030518691
DOIs
Publication statusPublished - 2021

Publication series

NameIntelligent Systems Reference Library
PublisherSpringer
Volume189
ISSN (Print)1868-4394
ISSN (Electronic)1868-4408

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