Facial Expression Analysis using Active Shape Model

Facial expressions analysis is a vital part of the research in human-machine interaction. This chapter introduces an automatic recognition system for facial expression from a front view human face image. Obtaining an effective facial representation from initial face images is an essential phase for strong and efficient facial expression system. In this chapter we have developed a facial expression analysis system. Firstly we have tried to evaluate facial analysis base on Active shape model (ASM). In order to detect the face images, Adaboost classifier and Haar-Like feature has been adopted to achieve face detection and tracking. The ASM then has been automatically initiated in the detected face image. Then, discriminates and reliable facial feature points has been extracted applying ASM fitting technique. The geometric displacement among the projected ASM feature points coordinates and the mean shape of ASM were used to evaluate facial expression. Using support vector machine (SVM) classifier, the obtained results has reached a recognition rate of 93 %.

[1]  Maja Pantic,et al.  Facial Action Unit Detection using Probabilistic Actively Learned Support Vector Machines on Tracked Facial Point Data , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[2]  Marian Stewart Bartlett,et al.  Face recognition by independent component analysis , 2002, IEEE Trans. Neural Networks.

[3]  Takeo Kanade,et al.  Comprehensive database for facial expression analysis , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[4]  Maja Pantic,et al.  Fully Automatic Facial Action Unit Detection and Temporal Analysis , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[5]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[6]  Zhengyou Zhang,et al.  Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[7]  Takeo Kanade,et al.  A Unified Gradient-Based Approach for Combining ASM into AAM , 2006, International Journal of Computer Vision.

[8]  Fernando Pereira,et al.  MPEG-4 facial animation technology: survey, implementation, and results , 1999, IEEE Trans. Circuits Syst. Video Technol..

[9]  Edward H. Adelson,et al.  Exploring features in a Bayesian framework for material recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Franck Davoine,et al.  Facial expression recognition and synthesis based on an appearance model , 2004, Signal Process. Image Commun..

[11]  P. Ekman,et al.  Facial action coding system: a technique for the measurement of facial movement , 1978 .

[12]  Matti Pietikäinen,et al.  Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  P. Ekman.  Pictures of Facial Affect , 1976 .

[14]  S. Demleitner.  [Communication without words]. , 1997, Pflege aktuell.

[15]  Marian Stewart Bartlett,et al.  Facial expression recognition using Gabor motion energy filters , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

[16]  Takeo Kanade,et al.  Recognizing Action Units for Facial Expression Analysis , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Maja Pantic,et al.  Affect-Sensitive Multi-Modal Monitoring in Ubiquitous Computing: Advances and Challenges , 2001, ICEIS.

[18]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

[19]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[20]  Bir Bhanu,et al.  Facial expression recognition using emotion avatar image , 2011, Face and Gesture 2011.