Human Facial Expression Recognition using MANFIS Model
Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
[1] Guoying Zhao and Matti Pietikainen, "Dynamic Texture Recognition
Using Local Binary Patterns with an Application to Facial Expressions",
IEEE Trans. Syst., Man, Cybern.B, Cybern., vol. 29, no. 6, pp. 915-928,
Jun. 2007.
[2] A. Mehrabian, "Communication without words", Psych. Today, vol. 2,
no. 4, pp. 53-56, 1968.
[3] J.N. Bassili, "Emotion Recognition: The Role of Facial Movementand
the Relative Importance of Upper and Lower Area of the Face", J.
Personality and Social Psychology., vol. 37, pp. 2049-2059, 1979.
[4] Irene Kotsia, Ioannis Pitas," Facial Expression Recognition in Image
Sequences Using Geometric Deformation Features and Support Vector
Machines", IEEE Trans. on Image Processing., vol. 16, no. 1, pp. 172-
187, Jan. 2007.
[5] Y. Zhang and Q. Ji, "Active and dynamic information fusion for facial
expression understanding from image sequences", IEEE Trans. Pattern
Anal. Mach. Intell., vol. 27, no. 5, pp. 699-714, May 2005.
[6] Spiros Ioannou, George Caridakis, Kostas Karpouzis, and Stefanos
Kollias, "Robust Feature Detection for Facial Expression Recognition"
EURASIP Journal on Image and Video Processing, vol. 2007, pp. 1-22,
May. 2007.
[7] Y. L. Tian, T. Kanade, and J. F. Cohn, "Recognizing action units for
facial expression analysis", IEEE Trans. Pattern Anal. Mach. Intell.,vol.
23, no. 2, pp. 97-115, Feb. 2001.
[8] Mohammed Yeasin, Baptiste Bullot, and Rajeev Sharma,"Recognition of
Facial Expressions and Measurement of Levels of Interest From Video",
IEEE Trans. Multimedia,, vol. 8, no. 3,pp. 500-508, Jun. 2006.
[9] Yan Tong, Wenhui Liao, and Qiang Ji,, "Facial Action Unit Recognition
by Exploiting Their Dynamic and Semantic Relationships", IEEE Trans.
Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1-17, Oct. 2007.
[10] Keith Anderson and Peter W. McOwan, "A Real-Time Automated
System for the Recognition of Human Facial Expressions", IEEE Trans.
Syst., Man, Cybern.B, Cybern., vol. 36, no. 1, pp. 96-105, Feb. 2006.
[11] I. Cohen, N. Sebe, S. Garg, L. S. Chen, and T. S. Huanga, "Facial
expression recognition from video sequences: temporal and static
modelling", Comput. Vis. Image Understand., vol. 91, pp. 160-
187,2003.
[12]M. Pantic and Ioannis Patras,"Dynamics of Facial Expression:
Recognition of Facial Actions and Their Temporal Segments From Face
Profile Image Sequences ", IEEE Trans. Syst., Man, Cybern.B, Cybern.,
vol. 36, no. 2, pp. 433-449, Apr. 2006.
[13] T. Ahonen, A. Hadid, and M. Pietikainen, "Face Description with Local
Binary Patterns: Application to Face Recognition", IEEE Trans. Pattern
Analysis and Machine Intelligence, vol. 28, no. 12, pp. 2037-2041, Dec.
2006.
[14] M. Pantic and L. J. M. Rothkrantz, "Automatic analysis of facial
expressions: the state of the art", IEEE Trans. Pattern Anal. Mach.
Intell., vol. 22, no. 12, pp. 1424-1445, Dec. 2000.
[15] Guoying Zhao and Matti Pietikainen, "Facial Expression Recognition
Using Constructive Feed forward Neural Networks", IEEE Trans. Syst.,
Man, Cybern.B, Cybern., vol. 34, no. 3, pp. 1588-1595, Jun. 2004.
[16] J.-S. Roger Jang, "ANFIS: Adaptive-Network-based Fuzzy Inference
Systems", IEEE Trans. Syst., Man, Cybernatics., vol. 23, no. 03, May,
pp. 665-685, 1993.
[17] J.-S. Roger Jang C.-T. Sun and E. Mizutani, "Chapter 19: ANFIS
Applications" Neuro-Fuzzy and Soft Computing: a computational
approach to learning and machine ntelligence, Prentice Hall, 1997, pp.
503-534.
[18] T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution Gray-Scale
and Rotation Invariant Texture Classification with Local Binary
Patterns", IEEE Trans. Pattern Analysis and Machine Intelligence, vol.
24, no. 7, pp. 971-987, July 2002.
[1] Guoying Zhao and Matti Pietikainen, "Dynamic Texture Recognition
Using Local Binary Patterns with an Application to Facial Expressions",
IEEE Trans. Syst., Man, Cybern.B, Cybern., vol. 29, no. 6, pp. 915-928,
Jun. 2007.
[2] A. Mehrabian, "Communication without words", Psych. Today, vol. 2,
no. 4, pp. 53-56, 1968.
[3] J.N. Bassili, "Emotion Recognition: The Role of Facial Movementand
the Relative Importance of Upper and Lower Area of the Face", J.
Personality and Social Psychology., vol. 37, pp. 2049-2059, 1979.
[4] Irene Kotsia, Ioannis Pitas," Facial Expression Recognition in Image
Sequences Using Geometric Deformation Features and Support Vector
Machines", IEEE Trans. on Image Processing., vol. 16, no. 1, pp. 172-
187, Jan. 2007.
[5] Y. Zhang and Q. Ji, "Active and dynamic information fusion for facial
expression understanding from image sequences", IEEE Trans. Pattern
Anal. Mach. Intell., vol. 27, no. 5, pp. 699-714, May 2005.
[6] Spiros Ioannou, George Caridakis, Kostas Karpouzis, and Stefanos
Kollias, "Robust Feature Detection for Facial Expression Recognition"
EURASIP Journal on Image and Video Processing, vol. 2007, pp. 1-22,
May. 2007.
[7] Y. L. Tian, T. Kanade, and J. F. Cohn, "Recognizing action units for
facial expression analysis", IEEE Trans. Pattern Anal. Mach. Intell.,vol.
23, no. 2, pp. 97-115, Feb. 2001.
[8] Mohammed Yeasin, Baptiste Bullot, and Rajeev Sharma,"Recognition of
Facial Expressions and Measurement of Levels of Interest From Video",
IEEE Trans. Multimedia,, vol. 8, no. 3,pp. 500-508, Jun. 2006.
[9] Yan Tong, Wenhui Liao, and Qiang Ji,, "Facial Action Unit Recognition
by Exploiting Their Dynamic and Semantic Relationships", IEEE Trans.
Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1-17, Oct. 2007.
[10] Keith Anderson and Peter W. McOwan, "A Real-Time Automated
System for the Recognition of Human Facial Expressions", IEEE Trans.
Syst., Man, Cybern.B, Cybern., vol. 36, no. 1, pp. 96-105, Feb. 2006.
[11] I. Cohen, N. Sebe, S. Garg, L. S. Chen, and T. S. Huanga, "Facial
expression recognition from video sequences: temporal and static
modelling", Comput. Vis. Image Understand., vol. 91, pp. 160-
187,2003.
[12]M. Pantic and Ioannis Patras,"Dynamics of Facial Expression:
Recognition of Facial Actions and Their Temporal Segments From Face
Profile Image Sequences ", IEEE Trans. Syst., Man, Cybern.B, Cybern.,
vol. 36, no. 2, pp. 433-449, Apr. 2006.
[13] T. Ahonen, A. Hadid, and M. Pietikainen, "Face Description with Local
Binary Patterns: Application to Face Recognition", IEEE Trans. Pattern
Analysis and Machine Intelligence, vol. 28, no. 12, pp. 2037-2041, Dec.
2006.
[14] M. Pantic and L. J. M. Rothkrantz, "Automatic analysis of facial
expressions: the state of the art", IEEE Trans. Pattern Anal. Mach.
Intell., vol. 22, no. 12, pp. 1424-1445, Dec. 2000.
[15] Guoying Zhao and Matti Pietikainen, "Facial Expression Recognition
Using Constructive Feed forward Neural Networks", IEEE Trans. Syst.,
Man, Cybern.B, Cybern., vol. 34, no. 3, pp. 1588-1595, Jun. 2004.
[16] J.-S. Roger Jang, "ANFIS: Adaptive-Network-based Fuzzy Inference
Systems", IEEE Trans. Syst., Man, Cybernatics., vol. 23, no. 03, May,
pp. 665-685, 1993.
[17] J.-S. Roger Jang C.-T. Sun and E. Mizutani, "Chapter 19: ANFIS
Applications" Neuro-Fuzzy and Soft Computing: a computational
approach to learning and machine ntelligence, Prentice Hall, 1997, pp.
503-534.
[18] T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution Gray-Scale
and Rotation Invariant Texture Classification with Local Binary
Patterns", IEEE Trans. Pattern Analysis and Machine Intelligence, vol.
24, no. 7, pp. 971-987, July 2002.
@article{"International Journal of Information, Control and Computer Sciences:62988", author = "V. Gomathi and Dr. K. Ramar and A. Santhiyaku Jeevakumar", title = "Human Facial Expression Recognition using MANFIS Model", abstract = "Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.", keywords = "Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram", volume = "3", number = "2", pages = "463-5", }