Facial expression recognition using image orientation field in limited regions and MLP neural network

In this paper, a novel approach for facial expression is introduced by using face orientation field concept. This method is not sensitive to the obstacles such as hair, eyeglasses and surrounding illumination. The computational tools of this paper have been used in previous studies for fingerprint recognition systems. However, we have adopted them for facial expression recognition. The features which extracted from orientation field are applied to the MLP neural network and this network select facial expression among six universal expressions. The presented method, have been tested on the JAFFE database and reached the average accuracy of 90.33% in recognition of facial expressions.

[1]  Yung-Chang Chen,et al.  Facial Expression Analysis under Various Head Poses , 2002, IEEE Pacific Rim Conference on Multimedia.

[2]  Martin T. Hagan,et al.  Neural network design , 1995 .

[3]  Beat Fasel,et al.  Automati Fa ial Expression Analysis: A Survey , 1999 .

[4]  Andrew P. Witkin,et al.  Analyzing Oriented Patterns , 1985, IJCAI.

[5]  Gihan Shin,et al.  Spatio-temporal Facial Expression Recognition Using Optical Flow and HMM , 2008, Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[6]  Bogdan Raducanu,et al.  Efficient Facial Expression Recognition for Human Robot Interaction , 2007, IWANN.

[7]  Gregory D. Hager,et al.  Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Junchul Chun,et al.  Cylindrical Model-Based Head Tracking and 3D Pose Recovery from Sequential Face Images , 2006, 2006 International Conference on Hybrid Information Technology.

[9]  Xinhe Xu,et al.  Facial expression recognition based on PCA and NMF , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[10]  Wang Shitong,et al.  Facial expression recognition using RBF neural network based on improved artificial fish swarm algorithm , 2008, 2008 27th Chinese Control Conference.

[11]  P. Ekman,et al.  Unmasking the face : a guide to recognizing emotions from facial clues , 1975 .

[12]  Michael J. Lyons,et al.  Coding facial expressions with Gabor wavelets , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[13]  Anil K. Jain,et al.  Adaptive flow orientation-based feature extraction in fingerprint images , 1995, Pattern Recognit..