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Feature Extraction for Facial Expression Recognition based on Hybrid Face RegionsLAJEVARDI, S.M.   , HUSSAIN, Z. M. |
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Author keywords
facial expression recognition, Gabor filters, face regions, human computer interaction, feature extraction
References keywords
recognition(19), facial(18), lajevardi(8), gabor(7), pattern(6), image(6), hussain(5), neural(4), features(4), feature(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 63 - 67
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03012
Web of Science Accession Number: 000271872000012
SCOPUS ID: 77954728504
Abstract
Facial expression recognition has numerous applications, including psychological research, improved human computer interaction, and sign language translation. A novel facial expression recognition system based on hybrid face regions (HFR) is investigated. The expression recognition system is fully automatic, and consists of the following modules: face detection, facial detection, feature extraction, optimal features selection, and classification. The features are extracted from both whole face image and face regions (eyes and mouth) using log Gabor filters. Then, the most discriminate features are selected based on mutual information criteria. The system can automatically recognize six expressions: anger, disgust, fear, happiness, sadness and surprise. The selected features are classified using the Naive Bayesian (NB) classifier. The proposed method has been extensively assessed using Cohn-Kanade database and JAFFE database. The experiments have highlighted the efficiency of the proposed HFR method in enhancing the classification rate. |
| References | | | Cited By «-- Click to see who has cited this paper |
| [1] Kanade, T., Cohn, J. F., and Tian, Y., "Comprehensive database for facial expression analysis", Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, Grenoble, France, pp. 46-53, 2000
[2] Kaliouby, R. E., Robinson, P., "Real-time inference of complex mental states from facial expressions and head gestures", Conference on Computer Vision and Pattern Recognition Workshop, vol. 3, pp. 181-200, 2004 [3] Tian, Y., Kanade, T., Cohn, J. F., "Recognizing action units for facial expression analysis", IEEE Tran. on Pattern Analysis and Machine Intelligence, vol. 23, no. 2, pp. 97-115, 2001 [CrossRef] [Web of Science Times Cited 986] [SCOPUS Times Cited 1358] [4] Viola, P., Jones, M., "Robust real-time object detection", International Journal of Computer Vision, 57(2), pp. 137-154, 2004 [CrossRef] [Web of Science Times Cited 8262] [SCOPUS Times Cited 11046] [5] Guyon, I., Gunn, S., Nikravesh, M., Zadeh, A., "Feature Extraction Foundations and Applications", Springer, 2006 [CrossRef] [6] Lyons, M., Akamatsu, S., Kamachi, M., and Gyoba, J., "Coding facial expressions with Gabor wavelets", In FG'98: Proceedings of the 3rd International Conference on Face and Gesture Recognition, Washington, USA, 1998 [7] Zheng, D., Zhao, Y., Wang, J., "Features extraction using a Gabor filter family", Proceedings of the Sixth IASTED International Conference Signal and Image Processing, Hawaii, USA, 2004 [8] Rish, I., "An empirical study of the naive Bayes classifier", IJCAI Workshop on Empirical Methods in Artificial Intelligence, vol. 335, pp. 41-46, 2001 [9] Claude, F. B., Chibelushi, C., "Facial Expression Recognition: A Brief Tutorial Overview", 2003 [10] Battiti, R., "Using mutual information for selecting features in supervised neural net learning", IEEE Trans. on Neural Networks, vol. 5, no. 4, pp. 537-550, 1994 [CrossRef] [PubMed] [Web of Science Times Cited 1723] [SCOPUS Times Cited 2145] [11] Liu, F., Wang, Z., Wang, L., Meng, X., "Facial expression recognition using HLAC features and WPCA", Lecture Notes in Computer Science, Springer, 2005 [CrossRef] [SCOPUS Times Cited 5] [12] Buciu, I., Kotropoulos, C., and Pitas, I., "ICA and Gabor representation for facial expression recognition", International Conference on Image Processing, vol. 2, pp. 14-17, 2003 [CrossRef] [13] Field, D.J., "Relations between the images and the response properties of cortical cells", Jour. of the Optical Society of America, pp. 2379-2394, 1987 [CrossRef] [Web of Science Times Cited 2212] [SCOPUS Times Cited 2586] [14] Duda, R. O., Hart, P. E., Stork, D. G., "Pattern Classification", Wiley, New York, 2001 [15] Park, S., and Kim, D., "Subtle facial expression recognition using motion magnification", Pattern Recognition Letters, 30(7), pp. 708-716, 2009 [CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 45] [16] Xie, X., and Lam, K.M., "Facial expression recognition based on shape and texture", Pattern Recognition, 42(5), pp. 1003-1011, 2009 [CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 61] [17] Kotsia, I., Zafeiriou, S., and Pitas, I., "Novel multiclass classifiers based on the minimization of the within-class variance", IEEE Tran. on Neural Networks, 20(1), pp. 14-34, 2009 [CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 33] [18] Geetha, A., Ramalingam, V., Palanivel, S., Palaniappan, B., "Facial expression recognition: a real time approach", Expert Systems with Applications, 36(1), pp. 303-308, 2009 [CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 49] [19] Lajevardi, S. M., Lech, M., "Facial Expression Recognition Using Neural Networks and Log-Gabor Filters", Proceedings of Digital Image Computing: Techniques and Applications (DICTA'08), pp. 77-83, Australia, 2008 [CrossRef] [SCOPUS Times Cited 34] [20] Lajevardi, S. M., Lech, M., "Averaged Gabor filter features for facial expression recognition", Proceedings of Digital Image Computing: Techniques and Applications (DICTA'08), pp. 71-76, Australia, 2008 [CrossRef] [SCOPUS Times Cited 32] [21] Lajevardi, S. M., Lech, M., "Facial expression recognition from image sequences using optimised feature selection", 23rd International Conference on Image and Vision Computing (IVCNZ'08), pp. 1-6, New Zealand, 2008 [CrossRef] [SCOPUS Times Cited 29] [22] Lajevardi, S. M., Hussain, Z. M., "Facial expression recognition: Gabor filters versus higher-order correlators", International Conference on Communication, Computer and Power (ICCCP'08), pp. 354-358, Oman, 2009 [23] Lajevardi, S. M., Hussain, Z. M., "Facial expression recognition using log-Gabor filters and local binary pattern operators", International Conference on Communication, Computer and Power (ICCCP'08), pp. 349-353, Oman, 2009 [24] Lajevardi, S. M., Hussain, Z. M., "Zernike moments for facial expression recognition", International Conference on Communication, Computer and Power (ICCCP'08), pp. 371-381, Oman, 2009 [25] Lajevardi, S. M., Hussain, Z. M., "Feature selection for facial expression recognition based on mutual information", IEEE-GCC'09 Conference, Kuwait, 2009 [26] Lajevardi, S. M., Hussain, Z. M., "Feature selection for facial expression recognition based on optimization algorithm", Second International Workshop on Nonlinear Dynamics and Synchronization (INDS'09), Klagenfurt, Austria, 2009 Web of Science® Citations for all references: 13,330 TCR SCOPUS® Citations for all references: 17,423 TCR Web of Science® Average Citations per reference: 494 ACR SCOPUS® Average Citations per reference: 645 ACR 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 2025-01-01 10:41 in 95 seconds. Note1: Web of Science® is a registered trademark of Clarivate Analytics. Note2: SCOPUS® is a registered trademark of Elsevier B.V. Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). 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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
