Emotion Recognition Using Cloud Model

WANG Shuliang; CHI Hehua; YUAN Ziqiang; GENG Jing

doi:10.1049/cje.2018.09.020

Volume 28 Issue 3

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Article Navigation > Chinese Journal of Electronics > 2019 > 28(3): 470-474

WANG Shuliang, CHI Hehua, YUAN Ziqiang, et al., “Emotion Recognition Using Cloud Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 470-474, 2019, doi: 10.1049/cje.2018.09.020

Citation:

WANG Shuliang, CHI Hehua, YUAN Ziqiang, et al., “Emotion Recognition Using Cloud Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 470-474, 2019, doi: 10.1049/cje.2018.09.020

WANG Shuliang, CHI Hehua, YUAN Ziqiang, et al., “Emotion Recognition Using Cloud Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 470-474, 2019, doi: 10.1049/cje.2018.09.020

Citation:

WANG Shuliang, CHI Hehua, YUAN Ziqiang, et al., “Emotion Recognition Using Cloud Model,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 470-474, 2019, doi: 10.1049/cje.2018.09.020

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Emotion Recognition Using Cloud Model

doi: 10.1049/cje.2018.09.020

1.
School of Computer Science, Wuhan University, Wuhan 430079, China;
2.
School of software, Beijing Institute of Technology, Beijing 100081, China;
3.
Goergen Institute for Data Science, University of Rochester, Rochester NY 14627, USA

Funds: This work is supported by the National Key Research and Development Plan of China (No.2016YFC0803000, No.2016YFB0502604) and National Natural Science Fund of China (No.61472039).

More Information

Corresponding author: CHI Hehua (corresponding author) is a Ph.D. candidate in Wuhan University and also a graduate student in University of Rochester. (Email:hchi3@ur.rochester.edu)
Received Date: 2017-05-16
Publish Date: 2019-05-10

Abstract

Abstract

Emotions often facilitate interactions among human beings, but the big variation of human emotional states make a negative effect on the reliable emotion recognition. We propose a novel algorithm to extract common features for each type of emotional states which can reliably present human emotions. To uncover the common features from uncertain emotional states, the backward cloud generator is used to discover {Ex, En, He} by integrating randomness and fuzziness. Finally, the proposed method for emotion recognition is verified on the common facial expression datasets, the Extended Cohn-Kanade (CK₊) dataset and the Japanese female facial expression (JAFFE). The results are satisfactory, which shows cloud model is potentially useful in pattern recognition and machines learning.
- Cloud model,
- Feature extraction,
- Human-machine interaction,
- Emotion recognition

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References(22)

References

L.C. De Silva, T. Miyasato and R. Nakatsu, "Facial emotion recognition using multi-modal information", In Proceedings of IEEE International Conference on In Information, Communications and Signal Processing, ICICS, Beijing, China, Vol.1, pp.397-401, 1997.

K. Durand, M. Gallay, A. Seigneuric, et al., "The development of facial emotion recognition:The role of configural information", Journal of Experimental Child Psychology, Vol.97, No.1, pp.14-27, 2007.

C.D. Kashyap and P.R. Vishnu, "Facial emotion recognition", International Journal of Engineering and Future Technology, Vol.7, No.7, pp.18-29, 2016.

O. Russakovsky, J. Deng, H. Su, et al., "ImageNet large scale visual recognition challenge", International Journal of Computer Vision, Vol.115, No.3, pp.211-252, 2015.

Beymer DJ, "Face recognition under varying pose", In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Seattle, Washington, USA, pp.756-761, 1994.

G. Ralph, B. Simon, M. Iain, et al., Face Recognition across Pose and Illumination, Springer-Verlag, Berlin, Germany, 2004.

R. Jenkins and A.M. Burton, "Stable face representations", Philosophical Transactions ofthe Royal Society B Biological Sciences, Vol.366, No.1571, pp.1671-1683, 2011.

W. Zhao, R. Chellappa, A. Rosenfeld, et al., "Face recognition:A literature survey", ACM Computing Surveys, Vol.35, No.4, pp.399-458, 2003.

Zhou Q, Shafiq U R, Zhou Y, et al., "Face recognition using dense sift feature alignment", Chinese Journal of Electronics, Vol.25, No.6, pp.1034-1039, 2016.

L. Wang, Y. Liang, W. Cai, et al., "Failure detection and correction for appearance based facial tracking", Chinese Journal of Electronics, Vol.24, No.1, pp.20-25, 2015.

Wang S, Yuan H, Cao B, et al., "Facial data field", Chinese Journal of Electronics, Vol.24, No.4, pp.667-673, 2015.

D. Li, C. Liu and W. Gan, "A new cognitive model:cloud model", International Journal of Intelligent Systems, Vol.24, No.3, pp.357-375, 2009

S L Wang and H N. Yuan, "View-angle of spatial data mining", Lecture Notes in Artificial Intelligence, Vol.4093, No.5, pp.1065-1076, 2006.

C. Szegedy, S. Ioffe, V. Vanhoucke, et al., "Inception-v4, Inception-ResNet and the impact of residual connections on learning", In Proceedings of AAAI, San Francisco, California, USA, pp.4278-4284, 2017.

D.R. Li, S.L. Wang and D.Y. Li, Spatial Data Mining:Theory and Application, Springer, Berlin, Germany, pp.187-201, 2015.

J.B. Wu, H.H. Chi and L.H. Chi, "A cloud modelbased approach for facial expression synthesis", Journal of Multimedia, Vol.6, No.2, pp.217-224, 2011

H.H. Chi, L.H. Chi, M. Fang, et al., "Facial expression recognition based on cloud model", The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.38, Part Ⅱ, pp.124-128, 2010.

M JLyons, S Akamatsu, M Kamachi, et al., "The japanese female facial expression (JAFFE) database", In Proceedings of The Third International Conference on Automatic Face and Gesture Recognition, Nara, Japan, pp.14-16, 1998.

PLucey, J F Cohn, T Kanade, et al., "The extended cohnkanade dataset (CK₊):A complete dataset for action unit and emotion-specified expression", In Proceedings of Computer Vision and Pattern Recognition Workshop on Human-Communicative Behavior, San Francisco, California, USA, pp.94-101, 2010.

K. He, X. Zhang, S. Ren, et al., "Deep residual learning for image recognition", In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA, pp.770-778, 2016.

S. Srinivas, R.K. Sarvadevabhatla, K.R. Mopuri, et al., "A taxonomy of deep convolutional neural nets for computer vision. frontiers in robotics and AI, Vol.2, AritcleID 36, pp.1-13, 2016

S.L. Wang, H.H. Chi, H.N. Yuan, et al., "Extraction and representation of common feature from uncertain facial expressions with cloud model", Environmental Science and Pollution Research, Vol.24, No.36, pp.27778-27787, 2017.

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