A Novel Supervised Bimodal Emotion Recognition Approach Based on Facial Expression and Body Gesture-Reference-Cited by-同舟云学术

A Novel Supervised Bimodal Emotion Recognition Approach Based on Facial Expression and Body Gesture

Published:2018-11-01 Issue:11 Volume:E101.A Page:2003-2006
ISSN:0916-8508
Container-title:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
language:en
Short-container-title:IEICE Trans. Fundamentals

Author:

YAN Jingjie¹,LU Guanming¹,BAI Xiaodong¹,LI Haibo¹,SUN Ning²,LIANG Ruiyu³

Affiliation:

1. Jiangsu Provincial Key Laboratory of Image Processing and Image Communication, College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications

2. Engineering Research Center of Wide band Wireless Communication Technology, Nanjing University of Posts and Telecommunications

3. School of Communication Engineering, Nanjing Institute of Technology

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing

Link

https://www.jstage.jst.go.jp/article/transfun/E101.A/11/E101.A_2003/_pdf

Reference38 articles.

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2. [2] H. Gunes, M. Piccardi, “From mono-modal to multi-modal: Affect recognition using visual modalities,” in Intelligent Environments, pp.154-182, Springer, London, 2009. 10.1007/978-1-84800-346-0_10

3. [3] H. Gunes, M. Piccardi, M. Pantic, “From the lab to the real world: Affect recognition using multiple cues and modalities,” in Affective Computing: Focus on Emotion Expression, Synthesis, and Recognition, pp.185-218, InTech Education and Publishing, Vienna, 2008. 10.5772/6180

4. [4] J. Yan, W. Zheng, M. Xin, and J. Yan, “Integrating facial expression and body gesture in videos for emotion recognition,” IEICE Trans. Inf & Syst., vol.E97-D, no.3, pp.610-613, March 2014. 10.1587/transinf.e97.d.610

5. [5] Z. Zeng, M. Pantic, and T.S. Huang, “Emotion recognition based on multimodal information,” in Affective Information Processing, pp.241-265, Springer, London, 2009. 10.1007/978-1-84800-306-4_14

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