Journal of Multimedia, Vol 6, No 2 (2011), 217-224, Apr 2011
doi:10.4304/jmm.6.2.217-224

A Cloud Model-based Approach for Facial Expression Synthesis

Juebo Wu, Hehua Chi, Lianhua Chi

Abstract


The process to synthesize feature for human facial expression often implies both fuzziness, randomness and their certain relevance in image data. By using the advantage of cloud model, this paper presents a new approaches and applications for comprehensive analysis of human facial expression synthesis using cloud model, in order to realize the rapid and effective facial expression processing in analysis and application. It gives the comprehensive analysis for the fuzziness and randomness of facial expression feature and the relationship between them based on cloud model, including the new method of facial expression synthesis with the uncertainty. It proposes the method of facial expression feature synthesis by cloud model, using the three numerical characteristics (Expectation, Entropy and Hyper Entropy) as the features and concepts of facial expression with its fuzziness, randomness and certain relevance in them. Through such three numerical characteristics, it introduces the framework of facial expression synthesis and the detail procedures based on cloud model. It puts forward the synthesis method of facial expression and gives the concrete realization and the implementation process. The facial expressions after synthesis can express the different expressions for one person, and it can meet a variety of demands for facial expression. The experimental results show that the proposed method is feasible and effective in facial expression synthesis.


Keywords


facial expression feature extraction; facial expression synthesis; cloud generator; cloud model

References


[1] W. Li. Facial expression recognition method. Electronic technology, 2007.

[2] H.B. Deng, L.W. Jin. A method based on local Gabor filter and PCA + LDA face recognition method [J]. Chinese Journal of Image and Graphics, 2007, (02).

[3] X.G. Yu, T.H. Cao, B.S. Chen. Face recognition and implement based on Eigenface. Hebei Industrial Technology, 2009, (05).

[4] H.Q. Deng, Q.J. Huang. Method of Eye Detection Combining Correlation Pattern Match and Improved Integral Projection [J]. Traffic and computer, 2007, (02).

[5] H. Jiang. Study on face recognition algorithm based on the geometric feature. Dalian university of technology, 2008.

[6] X.J. Zhou et al. A New Face Recognition Method Based on The Combination of Multi-Subspace [J]. Video Engineering, 2009, (S1).

[7] F.S. Hu et al. Pose and Illumination Invariant Face Recognition Based on HMM with One Sample Per Person [J]. CHINESE JOURNAL OF COMPUTERS, 2009, (07).

[8] Y. Peng. Image Local Feature Extraction and Detection [J]. EQUIPMENT MANUFACTURING TECHNOLOGY, 2010, (02).

[9] Z.Q. Hu, H.W. Liu. A research in face recognition based on wavelet analysis and geometric features [J]. MICROCOMPUTER & ITS APPLICATIONS, 2009, (15).

[10] A. L. Yuille, P. W. Hallinan, D. S. Cohen. Feature extraction from faces using deformable templates[J]. International Journal of Computer Vision, 1992, 8(2).

[11] L. H. Zhao, X. L. Zhang, X. H. Xu. Face recognition based on 2D symmetrical PCA[J]. Chinese Journal of ScientificInstrument, 2008, 29(6): 1290-1294.

[12] X. S. Zhuang, D. Q. Dai. Inverse fisher discriminate cri-teria for small sample size problem and its application to face recognition. Pattern Recognition, 2005, 38: 2192-2194.
doi:10.1016/j.patcog.2005.02.011

[13] K. C. Kwak, W. Pedrycz. Face recognition using a fuzzyfisherface classifier[J]. Pattern Recognition, 2005, 38, pp. 1717-1732.
doi:10.1016/j.patcog.2005.01.018

[14] H.W. Hao, L. Zhang. Face recognition based on SVD and LDA [J]. APPLICATION RESEARCH OF COMPUTERS, 2007, (12).

[15] H. Luo, C.L. Meng. A Combination of Eigenface Recognition and LDA Algorithm for Recognitin of Human Face Images[J]. Guizhou industrial university (natural science edition), 2005, (01).

[16] S. Marcel. A Symmetric Transformation for LDA-Based Face Verification. Proc of the 6th International Conference on Automatic Face and Gesture Recognition. 2004, pp. 207-212.
doi:10.1109/AFGR.2004.1301532

[17] Y. Fan et al. Symmetrical LDA and Its Application in Face Recognition [J]. COMPUTER ENGINEERING, 2010, (01).

[18] C.J. Zhou et al. Face Recognition Based on ICA and Features Fusion [J]. JOURNAL OF BASIC SCIENCE AND ENGINEERING, 2009, (05).

[19] C.X. Zhou, J.Y. Yi. Human Face Detection and Location Method Based on Improved BP Network [J]. SCIENCE TECHNOLOGY AND ENGINEERING, 2008, (06).

[20] Z.B. Zhang, S.L. Ma, J. Ma. Application of Wavelet and Neural Network in the Human Face Illumination Compensation [J]. JOURNAL OF JILIN UNIVERSITY(SCIENCE EDITION), 2005, (02).

[21] [21] M. Ma, L.B. Zhang, C.Y. Zhao. Fast Human Face Detection Based on Skin Color Segmentation and Neural Network VerificationJ]. JOURNAL OF BEIHUA UNIVERSITY(NATURAL SCIENCE), 2004, (04).

[22] J.H. Tang, Y.W. Zhang. The Expression Recognition Method of SVM Based on FLD Extracting Feature [J]. COMPUTER ENGINEERING AND APPLICATIONS, 2006, (11).

[23] S.R. Zhou. Face recognition algorithm analysis [D]. Zhongnan university, 2009.

[24] X.D. Li, Z.Y. Zhang. Facial Expression Synthesis from Multiple Facial Expressions [J]. JOURNAL OF COMPUTER-AIDED DESIGN & COMPUTER GRAPHICS, 2005, (01).

[25] P. Ekman, W. Friesen. Facial Action CodingSystem (FACS): A technique for the measurement of facial action.Palo Alto, California.: Consulting Psychologists Press, 1978.

[26] Y. Lee, D. Terzopoulos, and K. Waters. Realistic modeling forfacial animation. In Computer Graphics Proceedings, Annual Con-ference Series, Proceedings of SIGGRAPH 95, pages 55 62. ACMSIGGRAPH, 1995.
doi:10.1145/218380.218407

[27] W. K. Wai, L. K. Man, C. Kit. An accurate active shape model for facial featureextraction[J]. Pattern Recognition Letters, 2005, 26(12), pp. 2409-2423.

[28] B.F. Hu, L.M. Qiu. 3D Face Pose Estimation Based on Multi-points Model [J]. JOURNAL OF IMAGE AND GRAPHICS, 2008, (07).

[29] H. Liu. Research on 3D and visual ear recognition [D]. Shanghai jiaotong university, 2008.

[30] S.D. Li. Face detection based on multi-characteristics [D]. Zhongnan university, 2009.

[31] Y. Zhen. Face modeling study based on image 3d [D]. China university of science and technology, 2009.

[32] K. Pan. Research on Part-based Face Recognition [D]. China university of science and technology, 2009.

[33] J. Noh and U. Neumann. Expression cloning. In Com-puter Graphics Proc. SIGGRAPH 2001. ACM Press, pp. 277–288.

[34] J.Y. Liu. Enhancement Algorithm of Robustness for Expression Ratio Image [J]. JOURNAL OF XI'AN JIAOTONG UNIVERSITY, 2006, (08).

[35] G.Y. An. A study of complex conditions for face recognition [D]. Beijing jiaotong university, 2009.

[36] D.R. Li, S.L. Wang, D.Y. Li. Spatial data mining theories and applications. Science press, 2006.

[37] J.Y. Wu, D.L. Zhou. Survey of face recognition [J]. APPLICATION RESEARCH OF COMPUTERS, 2009, (09).


Full Text: PDF


Journal of Multimedia (JMM, ISSN 1796-2048)

Copyright @ 2006-2012 by ACADEMY PUBLISHER – All rights reserved.