Survey on audiovisual emotion recognition: Databases, features, and data fusion strategies

Chung Hsien Wu, Jen Chun Lin, Wen Li Wei

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)

Abstract

Emotion recognition is the ability to identify what people would think someone is feeling from moment to moment and understand the connection between his/her feelings and expressions. In today's world, human-computer interaction (HCI) interface undoubtedly plays an important role in our daily life. Toward harmonious HCI interface, automated analysis and recognition of human emotion has attracted increasing attention from the researchers in multidisciplinary research fields. In this paper, a survey on the theoretical and practical work offering new and broad views of the latest research in emotion recognition from bimodal information including facial and vocal expressions is provided. First, the currently available audiovisual emotion databases are described. Facial and vocal features and audiovisual bimodal data fusion methods for emotion recognition are then surveyed and discussed. Specifically, this survey also covers the recent emotion challenges in several conferences. Conclusions outline and address some of the existing emotion recognition issues.

Original languageEnglish
Article numbere12
JournalAPSIPA Transactions on Signal and Information Processing
Volume3
DOIs
Publication statusPublished - 2014 Nov 11

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems

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