Facial Expressions Animation and Lip Tracking Using Facial Characteristic Points and Deformable Model
Face and facial expressions play essential roles in
interpersonal communication. Most of the current works on the facial
expression recognition attempt to recognize a small set of the
prototypic expressions such as happy, surprise, anger, sad, disgust
and fear. However the most of the human emotions are
communicated by changes in one or two of discrete features. In this
paper, we develop a facial expressions synthesis system, based on the
facial characteristic points (FCP's) tracking in the frontal image
sequences. Selected FCP's are automatically tracked using a crosscorrelation
based optical flow. The proposed synthesis system uses a
simple deformable facial features model with a few set of control
points that can be tracked in original facial image sequences.
[1] P. Ekman and W.V. Friesen, Facial Action Coding System (FACS),
Consulting Psychologists Press, Inc., 1978.
[2] Z. Wu,P. S. Aleksic and A. K. Katsaggelos," Lip Tracking for MPEG-4
Facial Animation," in Proc. 4th IEEE Int. Conf. on Multimodal
Interfaces,ICMI'02,
[3] P. Eisert, T. Wiegand and B. G. Fellow," Model-Aided Coding: A New
Approach to Facial Animation into Motion Compensated Video Coding,"
IEEE Trans. On Circuits and Systems for Video Technology, vol. 10, No.
3, April 2000.
[4] S. T. Worral, A. H. Sadka, and A. M. Kondoz, "3-D Facial Animationfor
Very Low Bit Rate Mobile Video," in Proc. IEE Int. Conf. on 3G Mobile
Communication Technologies, May 2002.
[5] F. Erol, "Modeling and Animating Personalized Faces," M.Sc. Thesis,
Bilkent university, January 2002.
[6] T. Kanade, J. Cohn and Y. Tian. Comprehensive database for facial
expression analysis, 2000.
[7] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Facial
Expressions Recognition from Static Images using Neural Networks and
Fuzzy logic," The 2nd Iranian Conference on Machine Vision and Image
processing (MVIP2003),vol.1 pp 7-12, Tehran, 2003.
[8] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Facial
Expressions Recognition from Image Sequences using Cross-correlation
Based Optical-Flow and Radial Basis Neural Networks," The 12th Iranian
Conference on Electrical Engineering,(ICEE 2004), vol.1 pp 165-
170,Mashhad, 2004 .
[9] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Recognition
of Six Basic Facial Expressions by Feature-Points Tracking using RBF
Neural Networks and Fuzzy Inference System," The IEEE International
conference on Multimedia & Expo (ICME2004), Taipei, Taiwan ,June
2004.
[10] Ali Aghagolzadeh, Hadi Seyedarabi and Sohrab Khanmohammadi ,"
Single and Composite Action Units Classification in Facial Expressions
by Feature-Points Tracking and RBF Neural Networks", Ukrainian Int.
conf. on signal/Image processing,UkrObraz 2004, October 2004, Kiev,
Ukraine.
[1] P. Ekman and W.V. Friesen, Facial Action Coding System (FACS),
Consulting Psychologists Press, Inc., 1978.
[2] Z. Wu,P. S. Aleksic and A. K. Katsaggelos," Lip Tracking for MPEG-4
Facial Animation," in Proc. 4th IEEE Int. Conf. on Multimodal
Interfaces,ICMI'02,
[3] P. Eisert, T. Wiegand and B. G. Fellow," Model-Aided Coding: A New
Approach to Facial Animation into Motion Compensated Video Coding,"
IEEE Trans. On Circuits and Systems for Video Technology, vol. 10, No.
3, April 2000.
[4] S. T. Worral, A. H. Sadka, and A. M. Kondoz, "3-D Facial Animationfor
Very Low Bit Rate Mobile Video," in Proc. IEE Int. Conf. on 3G Mobile
Communication Technologies, May 2002.
[5] F. Erol, "Modeling and Animating Personalized Faces," M.Sc. Thesis,
Bilkent university, January 2002.
[6] T. Kanade, J. Cohn and Y. Tian. Comprehensive database for facial
expression analysis, 2000.
[7] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Facial
Expressions Recognition from Static Images using Neural Networks and
Fuzzy logic," The 2nd Iranian Conference on Machine Vision and Image
processing (MVIP2003),vol.1 pp 7-12, Tehran, 2003.
[8] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Facial
Expressions Recognition from Image Sequences using Cross-correlation
Based Optical-Flow and Radial Basis Neural Networks," The 12th Iranian
Conference on Electrical Engineering,(ICEE 2004), vol.1 pp 165-
170,Mashhad, 2004 .
[9] H. Seyedarabi, A. Aghagolzadeh and S. Khanmohammadi, "Recognition
of Six Basic Facial Expressions by Feature-Points Tracking using RBF
Neural Networks and Fuzzy Inference System," The IEEE International
conference on Multimedia & Expo (ICME2004), Taipei, Taiwan ,June
2004.
[10] Ali Aghagolzadeh, Hadi Seyedarabi and Sohrab Khanmohammadi ,"
Single and Composite Action Units Classification in Facial Expressions
by Feature-Points Tracking and RBF Neural Networks", Ukrainian Int.
conf. on signal/Image processing,UkrObraz 2004, October 2004, Kiev,
Ukraine.
@article{"International Journal of Information, Control and Computer Sciences:63907", author = "Hadi Seyedarabi and Ali Aghagolzadeh and Sohrab Khanmohammadi", title = "Facial Expressions Animation and Lip Tracking Using Facial Characteristic Points and Deformable Model", abstract = "Face and facial expressions play essential roles in
interpersonal communication. Most of the current works on the facial
expression recognition attempt to recognize a small set of the
prototypic expressions such as happy, surprise, anger, sad, disgust
and fear. However the most of the human emotions are
communicated by changes in one or two of discrete features. In this
paper, we develop a facial expressions synthesis system, based on the
facial characteristic points (FCP's) tracking in the frontal image
sequences. Selected FCP's are automatically tracked using a crosscorrelation
based optical flow. The proposed synthesis system uses a
simple deformable facial features model with a few set of control
points that can be tracked in original facial image sequences.", keywords = "Deformable face model, facial animation, facialcharacteristic points, optical flow.", volume = "1", number = "12", pages = "4077-4", }