Human Main Facial Expressions Recognition from the Fixed Images by the Modified Gabor Filter and its Simulation

Abstract. Face is one of the most important communicative tools in humans’ social interactions. As a person can recognize the other’s feeling from his facial expression without saying a word. Facial expression recognition is a subject that has been aimed to develop the previous results by providing solutions through implementing and investigating the results of available algorithms in this paper. The use of averaging filter in facial expression recognition from the fixed images is a common method, however it has more errors. The other method is to use Gabor wavelets with a range of Frequencies and angles in spatial domain oriented to the input images. Although this method is highly accurate, it has time complexity and high memory usage due to the large-scale computations. In this article by segmenting the input image components into 5 parts and conflating the averaging filter with Gabor wavelets which has been derived for each segment with effective angles. In addition to the increase of previous methods’ computational speed, its accuracy has been also increased. Furthermore, designing the graphical face with the name of Robofis in Webots simulation environment indicates an imitation of those facial expressions which had been recognized by the implemented methods.                                                                     

___

  • Asl Jalili, S.S., Seyyed Arabi,M.H. (1391). The Recognition of Main Facial Component’s Movements and its Simulation. The Second National Conference on Software Engineering. Lahijan, Iran: The Azad Islamic University of Lahijan.
  • Mistry,. V& ,.Goyani, M. M .(2013) .A literature survey on Facial Expression Recognition using Technology,IJEAT,653-657 Journal of Engineering and Advanced
  • Kalita, J& ,.Karen, D, (2013) .Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique . International Journal of Advanced Computer Science and Applications, 196-202.
  • Srivastava, T& ,.Kant, N .(2012) .Facial Expression Recognition System: Basics . International Journal of Advanced Electrical and Electronics Engineering (IJAEEE, 45-50).
  • Huang, H.-F& ,.Tai, S.-C .(2012) .Facial Expression Recognition Using New Feature Extraction Algorithm .Electronic Letters on Computer Vision and Image Analysis, 41-54.
  • Youssif, A. A& ,.Asker, W. A .(2011) .Automatic Facial Expression Recognition System Based on Geometric and Appearance Features. Computer and Information Science, 115- 127.
  • Wu, T., Bartlett, M. S& ,.Movellan, J. R .(2010) .Facial Expression Recognition Using Gabor Motion Energy Filters .IEEE CVPR workshop on Computer Vision and Pattern Recognition for Human Communicative Behavior Analysis ., 1-6.
  • Bashyal, S& ,.K.Venayagamoorthy, G .(2008) .Recognition of facial expression using Gabor Wavelets and learning vector quantization .Elsevier, Engineering applications of Artificial Intelligence.
  • Gonzalez, R. C .(2007) .Digital Image Processing .MA, US: Addison-Wesley Longman Publishing Co., Inc.
  • Deng, H.-B., Jin, L.-W., Zhen, L.-X& ,.Huang, J.-C .(2005) .A New Facial Expression Recognition Method Based on Local Gabor Filter Bank and PCA plus LDA. International Journal of Information Technology ,86-96.
  • Khanum, A., Mufti, M., Javed, M. Y& ,.Shafiq, M .(2001) .Fuzzy case-based reasoning for facial expression recognition .IEEE transaction on Pattern nalysis and Machine Intelligent, 50-57.
  • FELLENZ, W. A., TAYLOR, J. G., TSAPATSOULIS, N& ,.KOLLIAS, S .(1999) . Comparing Template-based, Feature-based and Supervised Classification of Facial Expressions from Static Images .MLP CSCC, 5331-5336.
  • Zhang, Z.(1999) .Feature-Based Facial Expression Recognition: Sensitivity Analysis and Experiments With a Multi-Layer Perceptron .International Journal of Pattern Recognition and ArtiŞcial Interlligence (IJPRAI, 1-26).
  • Lyons, M& ,.Shigeru, A .(1998) .Coding Facial Expressions with Gabor Wavelets . Proceedings, Third IEEE International Conference on Automatic Face and Gesture Recognition(200-205) .Nara Japan: IEEE Computer Society. [15] scherer,
  • K& ,.P.Ekman .(1982) .Handbook of methods in nonverbal behavior
  • Research.Cambridge, UK: Cambridge Univ. Press.
  • P.Ekman& ,Friesen, W .(1979) .Pictures of facial Affects.Calif :Palo Alto Consulting Psychologist.
  • Mehrabian .(1968) .Communication without words .Pschology Today, Vol.2, No. 4.