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Paper Information

Journal:   JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ)   SUMMER 2006 , Volume 33 , Number 1 (43) ELECTRICAL ENGINEERING; Page(s) 25 To 35.
 
Paper: 

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.
 
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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.

 
Keyword(s): FACIAL EXPRESSIONS RECOGNITION, FACIAL FEATURE POINTS, RBF NEURAL NETWORKS, FUZZY INFERENCE SYSTEM
 
References: 
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