Facial Expression Recognition System using Statistical Feature and Neural Network
TL;DR: A new technique for facial expression recognition is proposed which uses the statistical feature of the whole face and classify the expression using neural network classifier, which is being implemented in MATLAB 7.0.
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Abstract: In this paper, a new technique for facial expression recognition is proposed which uses the statistical feature of the whole face and classify the expression using neural network classifier. When the face image is input, region of interest (ROI) is being obtained to evaluate the statistical feature of the face. Using these, features we classify the face into one of the seven different expressions by using multi label Back Propagation neural network classifier. To demonstrate the proposed recognition technique we use JAFFE facial database and the whole program is being implemented in MATLAB 7.0. General Terms Pattern Recognition.
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References
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TL;DR: The capability of the human visual system with respect to these problems is discussed, and it is meant to serve as an ultimate goal and a guide for determining recommendations for development of an automatic facial expression analyzer.
Facial Expression Recognition
Maja Pantic
- 20 Jul 2009
TL;DR: Facial expression recognition is a process performed by humans or computers that consists of analyzing the motion of facial features and/or the changes in the appearance of facial Features and classifying this information into some facialexpression-interpretative categories such as facial muscle activations.
Facial expression recognition from line-based caricatures
Yongsheng Gao,Maylor K. H. Leung,Siu Cheung Hui,M.W. Tananda +3 more
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TL;DR: This work has proven the proposed idea that facial expressions can be characterized and recognized by caricatures and is thus suitable for real-time applications.
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Facial expression recognition using Support Vector Machines
Muzammil Abdulrahman,Alaa Eleyan +1 more
- 16 May 2015
TL;DR: A facial expression recognition approach based on Principal Component Analysis (PCA) and Local Binary Pattern (LBP) algorithms is proposed that has an average recognition rate of 87% and 77%, respectively.
113
A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network
TL;DR: This research proposes a novel approach using Canny, Principal Component Analysis (PCA) and Artificial Neural Network for Facial Expression Classification and shows the feasibility of this method.