Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.825
JCR 5-Year IF: 0.752
SCOPUS CiteScore: 2.5
Issues per year: 4
Current issue: Aug 2022
Next issue: Nov 2022
Avg review time: 76 days
Avg accept to publ: 48 days
APC: 300 EUR


PUBLISHER

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


TRAFFIC STATS

1,972,678 unique visits
787,504 downloads
Since November 1, 2009



Robots online now
Googlebot
bingbot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 22 (2022)
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
 Volume 20 (2020)
 
     »   Issue 4 / 2020
 
     »   Issue 3 / 2020
 
     »   Issue 2 / 2020
 
     »   Issue 1 / 2020
 
 
 Volume 19 (2019)
 
     »   Issue 4 / 2019
 
     »   Issue 3 / 2019
 
     »   Issue 2 / 2019
 
     »   Issue 1 / 2019
 
 
  View all issues  








LATEST NEWS

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

2021-Apr-15
Release of the v3 version of AECE Journal website. We moved to a new server and implemented the latest cryptographic protocols to assure better compatibility with the most recent browsers. Our website accepts now only TLS 1.2 and TLS 1.3 secure connections.

Read More »


    
 

  3/2009 - 12

 HIGH-IMPACT PAPER 

Feature Extraction for Facial Expression Recognition based on Hybrid Face Regions

LAJEVARDI, S.M. See more information about LAJEVARDI, S.M. on SCOPUS See more information about LAJEVARDI, S.M. on IEEExplore See more information about LAJEVARDI, S.M. on Web of Science, HUSSAIN, Z. M. See more information about HUSSAIN, Z. M. on SCOPUS See more information about HUSSAIN, Z. M. on SCOPUS See more information about HUSSAIN, Z. M. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (2,006 KB) | Citation | Downloads: 1,480 | Views: 6,564

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
Quick view
Full text preview
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 862] [SCOPUS Times Cited 1174]


[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 7736] [SCOPUS Times Cited 10153]


[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 1494] [SCOPUS Times Cited 1853]


[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 2085] [SCOPUS Times Cited 2399]


[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 35] [SCOPUS Times Cited 42]


[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 42] [SCOPUS Times Cited 60]


[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 28] [SCOPUS Times Cited 31]


[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 35] [SCOPUS Times Cited 48]


[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 31]


[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 30]


[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 28]


[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



References Weight

Web of Science® Citations for all references: 12,317 TCR
SCOPUS® Citations for all references: 15,854 TCR

Web of Science® Average Citations per reference: 456 ACR
SCOPUS® Average Citations per reference: 587 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 2022-09-25 08:37 in 92 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). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2022
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.




Website loading speed and performance optimization powered by: