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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  1/2019 - 7

 HIGHLY CITED PAPER 

Circular Derivative Local Binary Pattern Feature Description for Facial Expression Recognition

TCHANGOU TOUDJEU, I. See more information about TCHANGOU TOUDJEU, I. on SCOPUS See more information about TCHANGOU TOUDJEU, I. on IEEExplore See more information about TCHANGOU TOUDJEU, I. on Web of Science, TAPAMO, J.-R. See more information about TAPAMO, J.-R. on SCOPUS See more information about TAPAMO, J.-R. on SCOPUS See more information about TAPAMO, J.-R. on Web of Science
 
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Download PDF pdficon (1,929 KB) | Citation | Downloads: 1,232 | Views: 2,458

Author keywords
affective computing, classification, face recognition, feature extraction, image texture analysis

References keywords
facial(19), recognition(18), local(13), binary(11), patterns(8), pattern(8), image(6), classification(6), icme(4), comput(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-02-28
Volume 19, Issue 1, Year 2019, On page(s): 51 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.01007
Web of Science Accession Number: 000459986900007
SCOPUS ID: 85064192591

Abstract
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This paper presents a novel feature extraction technique called circular derivative local binary pattern (CD-LBP) for Facial Expression Recognition (FER). Motivated by uniform local binary patterns (uLBPs) which exhibits high discriminative potential at a reduced data dimension of the original LBP feature vector, we extract CD-LBP feature descriptors as a result of binary derivatives of the circular binary patterns formed by LBPs. Seven datasets consisting of CD-LBP feature vectors are derived from the Japanese female facial expression (JAFFE) database, fed individually in a K-nearest neighbor classifier and evaluated with respect to their respective recognition rate and feature vector size. The experimental results demonstrate the relevance of the proposed feature description especially when performance metrics such as recognition accuracy and running time are considered.


References | Cited By  «-- Click to see who has cited this paper

[1] N. N. Khatri, Z. H. Shah, S. A. Patel, "Facial expression recognition: A survey," International Journal of Computer Science and Information Technologies (IJCSIT), vol. 5, pp. 149-152, 2014.

[2] X. Feng, M. Pietikinen, A. Hadid, "Facial Expression Recognition with Local Binary Patterns and Linear Programming," Pattern Recognition and Image Analysis, vol. 15, no. 2, pp. 546-548, 2005.
[CrossRef]


[3] L. B. Majumder, V. K. Subramanian, "Local binary pattern based facial expression recognition using Self-organizing Map," in International Joint Conference on Neural Networks (IJCNN), pp. 2375-2382, 2014.
[CrossRef]


[4] D. Huang, C. Shan, M. Ardabilian, Y. Wang, L. Chen, "Local binary patterns and its application to facial image analysis: A survey," IEEE Trans. Syst. Man. Cybern. C Appl. Rev., vol. 41, no. 6, pp. 765-781, Nov. 2011.
[CrossRef] [Web of Science Times Cited 547]


[5] C. Silva, T. Bouwmans, C. Frélicot, "An eXtended center-symmetric local binary pattern for background modeling and subtraction in videos," Proc. Int. Conf. Comput. Vis. Theory Appli., pp. 395-402, 2015.
[CrossRef]


[6] G. Xue, L. Song, J. Sun, and M. Wu, "Hybrid center-symmetric local pattern for dynamic background subtraction," in Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2011.
[CrossRef]


[7] O. Lahdenoja, J. Poikonen, M. Laiho, "Towards understanding the formation of uniform local binary patterns", ISRN Mach Vis., vol. 2013, pp. 1, Jun. 2013.
[CrossRef]


[8] I. Cohen, N. Sebe, A. Garg, M. S. Lew, T. S. Huang, "Facial expression recognition from video sequences," in Proc. of IEEE International Conference on Multimedia and Expo (ICME), pp. 121-124, 2002.
[CrossRef]


[9] S. Moore, R. Bowden, "Local binary patterns for multi-view facial expression recognition," Comput. Vis. Image Understanding, vol. 115, no. 4, pp. 541-558, 2011.
[CrossRef] [Web of Science Times Cited 244]


[10] X. M. Zhao, S.Q. Zhang, "A review on facial expression recognition: feature extraction and classification," IETE Technical Review, vol. 33, no. 5, pp. 505-517, 2016.
[CrossRef] [Web of Science Times Cited 34]


[11] X. Feng, A. Hadid, M. Pietikinen, "A coarse-to-fine classification scheme for facial expression recognition," Proc. Int. Conf. Image Anal. Recog., pp. 668-675, 2004.
[CrossRef]


[12] C. Shan, S. Gong, P. W. McOwan, "Facial expression recognition based on local binary patterns: A comprehensive study," Image Vis. Comput., vol. 27, no. 6, pp. 803-816, 2009.
[CrossRef] [Web of Science Times Cited 1391]


[13] A. Sohail, P. Bhattacharya, "Classification of facial expressions using k-nearest neighbor classifier," Proc. Vision Computer Graphics Collaboration Techniques, pp. 555-566, 2007.
[CrossRef]


[14] R. Suresh, S. Audithan, G. Kannan and K. Raja, "Facial Expression Recognition System Using Local Texture Features of Contourlet Transformation," Australian Journal of Basic and Applied Sciences, vol. 10. no. 2, 2016.

[15] S. Kasim, R. Hassan, N. H. Zaini, A. Syifaa’Ahmad, A. A. Ramli, R. R. Saedudin, "A Study on Facial Expression Recognition Using Local Binary Pattern," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, pp. 1621-6, 26 Oct. 26, 2017.
[CrossRef]


[16] Y. Chang, C. Hu, R. Feris, M. Turk, "Manifold Based Analysis of Facial Expression," J. Image and Vision Computing, vol. 24, no. 6, pp. 605-614, 2006.
[CrossRef] [Web of Science Times Cited 103]


[17] S. Berretti, A. D. Bimbo, P. P. B.B. Amor, M. Daoudi, "A set of selected SIFT features for 3D facial expression recognition," Proc. 20th International Conference on Pattern Recognition, pp. 4125-4128, 2010.
[CrossRef]


[18] T. Ojala, M. Pietikinen, D. Harwood, "A Comparative Study of Texture Measures with Classification Based on Feature Distributions," Pattern Recognition, vol. 29, pp. 51-59, 1996.
[CrossRef] [Web of Science Times Cited 4505]


[19] S. L. Happy, A. George, A. Routray, "A real time facial expression classification system using local binary patterns," Proc. 4th Int. Conf. Intell. Human Comput. Interaction, pp. 1-5, 2012.
[CrossRef]


[20] X. Zhao, S. Zhang, "Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding," EURASIP Journal of Advances in Signal Processing, vol. 2012, no. 20, pp. 1-9, 2012.
[CrossRef] [Web of Science Times Cited 69]


[21] M. J. Lyons, J. Budynek, S. Akamatsu, "Automatic Classification of Single Facial Images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 12, pp. 1,357-1,362, 1999.
[CrossRef] [Web of Science Times Cited 694]


[22] P. Viola, M. Jones, "Robust Real-Time Face Detection," International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, May 2004.
[CrossRef] [Web of Science Times Cited 8138]


[23] X. Feng, B. Lv, Z. Li, J. Zhang, "A novel feature extraction method for facial expression recognition," Proc. Joint Conf. Inform. Sci. Issue Adv. Intell. Syst. Res., pp. 371-375, 2006.
[CrossRef]


[24] K. Meena and A. Suruliandi, "Local binary patterns and its variants for face recognition," in Recent Trends in Information Technology (ICRTIT), 2011 International Conference on, 2011, pp. 782-786.
[CrossRef]


[25] Y. Wu and Q. Weigen, "Facial expression recognition based on improved deep belief networks," IAP Conference Proceedings, vol. 1864, no. 1, 2017.
[CrossRef] [Web of Science Times Cited 2]




References Weight

Web of Science® Citations for all references: 15,727 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 605 ACR
SCOPUS® Average Citations per reference: 0

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-18 12:36 in 222 seconds.




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