Facial Expression Recognition via Sparse Representation-Reference-Cited by-同舟云学术

Facial Expression Recognition via Sparse Representation

Published:2012 Issue:9 Volume:E95.D Page:2347-2350
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

ZHI Ruicong¹²,RUAN Qiuqi¹,WANG Zhifei¹

Affiliation:

1. Institute of Information Science, Beijing Jiaotong University

2. Food and Standardization, China National Institute of Standardization

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E95.D/9/E95.D_2347/_pdf

Reference11 articles.

1. [1] I. Buciu and I. Pitas, Subspace Image Representation for Facial Expression Analysis and Face Recognition and Its Relation to the Human Visual System, Organic Computing, pp.303-320, Springer Verlag, 2008.

2. [2] M.S. Barlett, G. Littlewort, M. Frank, and C. Lainscsek, “Recognizing facial expression: Machine learning and application to spontaneous behavior,” International Conference on Computer Vision and Pattern Recognition (CVPR), pp.568-573, 2005.

3. [3] R. Duda, P. Hart, and D. Stork, Pattern Classification, 2nd ed. John Wiley & Sons, 2001.

4. [4] J. Ho, M. Yang, J. Lim, K. Lee, and D. Kriegman, “Clustering appearances of objects under varying illumination conditions,” Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp.11-18, 2001.

5. [5] A.Y. Yang, J. Wright, Y. Ma, and S. Sastry, “Feature selection in face recognition: A sparse representation perspective,” UC Berkeley Tech Report UCB/EECS-2007-99, 2007.

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