APSIPA Transactions on Signal and Information Processing > Vol 3 > Issue 1

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

Chung-Hsien Wu, National Cheng Kung University, Taiwan, chunghsienwu@gmail.com , Jen-Chun Lin, National Cheng Kung University, Taiwan AND Institute of Information Science, Taiwan, Wen-Li Wei, National Cheng Kung University, Taiwan
 
Suggested Citation
Chung-Hsien Wu, Jen-Chun Lin and Wen-Li Wei (2014), "Survey on audiovisual emotion recognition: databases, features, and data fusion strategies", APSIPA Transactions on Signal and Information Processing: Vol. 3: No. 1, e12. http://dx.doi.org/10.1017/ATSIP.2014.11

Publication Date: 11 Nov 2014
© 2014 Chung-Hsien Wu, Jen-Chun Lin and Wen-Li Wei
 
Subjects
 
Keywords
Emotion recognitionhuman-computer interactionaudiovisual data fusion
 

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In this article:
I. INTRODUCTION 
II. AUDIOVISUAL EMOTION DATABASES 
III. AUDIOVISUAL BIMODAL FUSION FOR EMOTION RECOGNITION 
IV. CONCLUSION 

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.

DOI:10.1017/ATSIP.2014.11