FEATURE-BASED FACIAL EXPRESSION RECOGNITION FROM IMAGE SEQUENCES USING RBF NEURAL NETWORKS AND FUZZY INFERENCE SYSTEM

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SEYED ARABI M.H.; AGHA GOLZADEH A.; KHAN MOHAMMADI S.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ) Year:2006 | Volume:33 | Issue:1 (43) ELECTRICAL ENGINEERING Page(s): 25-35

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

2,725

Download:

Cites:

Information Journal Paper

Title

FEATURE-BASED FACIAL EXPRESSION RECOGNITION FROM IMAGE SEQUENCES USING RBF NEURAL NETWORKS AND FUZZY INFERENCE SYSTEM

Author(s)

SEYED ARABI M.H. | AGHA GOLZADEH A. | KHAN MOHAMMADI S. | Issue Writer Certificate

Keywords

FACIAL EXPRESSIONS RECOGNITIONQ1

FACIAL FEATURE POINTSQ1

RBF NEURAL NETWORKSQ1

FUZZY INFERENCE SYSTEMQ1

Abstract

In this Paper a facial expression recognition system based on facial characteristic points and facial features extracted from them in frontal image sequences is presented. In the first digitized frame, 21 key feature points were manually marked with a computer-mouse around facial landmarks. Selected FACIAL FEATURE POINTS were automatically tracked using a cross-correlation based optical flow. At first a Radial Basis Function (RBF) neural network were used to classify four facial expressions using feature vector extracted from position of FACIAL FEATURE POINTS (FFP) in the first and the last frame. Then 7 features were extracted from FFP's movement and were used to classify six basic facial emotions using RBF NEURAL NETWORKS and FUZZY INFERENCE SYSTEM (FIS). The recognition results from proposed classifiers showed that comparing with static image classifier, using image sequences gives higher recognition rate. Comparing RBF NEURAL NETWORKS and FIS classifier systems shows that RBF classifier acts better than FIS classifier and gives higher recognition rate but it takes more processing time and for the real time implementation FIS classifier is preferred.

Cites

No record.

References

No record.

Cite

APA: Copy

SEYED ARABI, M.H., AGHA GOLZADEH, A., & KHAN MOHAMMADI, S.. (2006). FEATURE-BASED FACIAL EXPRESSION RECOGNITION FROM IMAGE SEQUENCES USING RBF NEURAL NETWORKS AND FUZZY INFERENCE SYSTEM. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), 33(1 (43) ELECTRICAL ENGINEERING), 25-35. SID. https://sid.ir/paper/43692/en

Vancouver: Copy

SEYED ARABI M.H., AGHA GOLZADEH A., KHAN MOHAMMADI S.. FEATURE-BASED FACIAL EXPRESSION RECOGNITION FROM IMAGE SEQUENCES USING RBF NEURAL NETWORKS AND FUZZY INFERENCE SYSTEM. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ)[Internet]. 2006;33(1 (43) ELECTRICAL ENGINEERING):25-35. Available from: https://sid.ir/paper/43692/en

IEEE: Copy

M.H. SEYED ARABI, A. AGHA GOLZADEH, and S. KHAN MOHAMMADI, “FEATURE-BASED FACIAL EXPRESSION RECOGNITION FROM IMAGE SEQUENCES USING RBF NEURAL NETWORKS AND FUZZY INFERENCE SYSTEM,” JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), vol. 33, no. 1 (43) ELECTRICAL ENGINEERING, pp. 25–35, 2006, [Online]. Available: https://sid.ir/paper/43692/en

Related Journal Papers