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Circular Derivative Local Binary Pattern Feature Description for Facial Expression RecognitionTCHANGOU TOUDJEU, I., TAPAMO, J.-R.
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affective computing, classification, face recognition, feature extraction, image texture analysis
facial(19), recognition(18), local(13), binary(11), patterns(8), pattern(8), image(6), classification(6), icme(4), comput(4)
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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
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.
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| 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.
 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] [SCOPUS Times Cited 33]
 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] [SCOPUS Times Cited 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 308] [SCOPUS Times Cited 438]
 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.
 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] [SCOPUS Times Cited 24]
 O. Lahdenoja, J. Poikonen, M. Laiho, "Towards understanding the formation of uniform local binary patterns", ISRN Mach Vis., vol. 2013, pp. 1, Jun. 2013.
 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] [SCOPUS Times Cited 50]
 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 171] [SCOPUS Times Cited 210]
 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 5] [SCOPUS Times Cited 10]
 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.
 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 852] [SCOPUS Times Cited 1116]
 A. Sohail, P. Bhattacharya, "Classification of facial expressions using k-nearest neighbor classifier," Proc. Vision Computer Graphics Collaboration Techniques, pp. 555-566, 2007.
 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.
 S. Kasim, R. Hassan, N. H. Zaini, A. SyifaaAhmad, 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] [SCOPUS Times Cited 2]
 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 84] [SCOPUS Times Cited 119]
 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] [SCOPUS Times Cited 83]
 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 2975] [SCOPUS Times Cited 4035]
 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] [SCOPUS Times Cited 28]
 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 44] [SCOPUS Times Cited 43]
 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 520] [SCOPUS Times Cited 666]
 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 5864] [SCOPUS Times Cited 8111]
 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] [SCOPUS Times Cited 11]
 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] [SCOPUS Times Cited 14]
 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 1] [SCOPUS Times Cited 3]
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