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Facial Expression Recognition Based on BoostingTree

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

In recent years, facial expression recognition has become an active research area that finds potential applications in the fields such as images processing and pattern recognition, and it plays a very important role in the applications of human-computer interfaces and human emotion analysis. This paper proposes an algorithm called BoostingTree, which is based on the conventional Adaboost and uses tree-structure to convert seven facial expressions to six binary problems, and also presents a novel method to compute projection matrix based on Principal Component Analysis (PCA). In this novel method, a block-merger combination is designed to solve the “data disaster” problem due to the combination of eigenvectors. In the experiment, we construct the weak classifiers set based on this novel method. The weak classifiers selected from the above set by Adaboost are combined into strong classifier to be as node classifier of one level of the tree structure. N-level tree structure built by BoostingTree can effectively solve multiclass problem such as facial expression recognition

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References

  1. Ekman, P., Friesen, W.V.: Constants Across Cultures in The Face And Emotion, J. Personality Social Psychol 17(2), 124–129 (1971)

    Article  Google Scholar 

  2. Calder, A.J., Burton, A.M., Miller, P., Young, A.W.: A Principal Component Analysis of Facial Expressions. Vision research 41, 1179–1208 (2001)

    Article  Google Scholar 

  3. Otsuka, T., Ohya, J.: Spotting Segments Displaying Facial Expressions from Image Sequences Using HMM. In: IEEE Proc. Int’l conf. on FG, Nara, Japan, pp. 442–447 (1998)

    Google Scholar 

  4. Zheng, W., Zhou, X., Zou, C., Zhao, L.: Facial Expression Recognition Using Kernel Canonical Correlation Analysis (KCCA). IEEE Transactions on Neural Networks (to appear)

    Google Scholar 

  5. Freund, Y.: Boosting A Weak Learning Algorithm by Majority. Information and Computation 121(2), 256–285 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  6. Schapire, R.C., Singer, Y.: BoosTexter: A Boosting-based System for Text Categorization. Machine Learning 39(2), 135–168 (2000)

    Article  MATH  Google Scholar 

  7. Yang, P., Shan, S., Gao, W., Li, S.Z.: Face Recognition Using Ada-Boosted Gabor Features. In: Proceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR, pp. 356–361 (2004)

    Google Scholar 

  8. Viola, P., Jones, M.: Robust Real Time Object Detection. In: 8th IEEE International Conference on Computer Vision (IC2CV), Vancouver, British Columbia (2001)

    Google Scholar 

  9. The Japanese Female Expression (JAFFE) Database, http://ww.mis.atr.co.jp/~mlyons/jaffe.html

  10. Guo, G., Dyer, C.R.: Learning From Examples in the Small Sample Case: Face Expression Recognition. IEEE Trans. On System Man and Cybernetics 35(3), 477–488 (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Research Center of Learning Science, Southeast University, Nanjing, 210096, China

    Ning Sun, Wenming Zheng & Li Zhao

  2. Department of Radio Engineering, Southeast University, Nanjing, 210096, China

    Ning Sun, Cairong Zou & Li Zhao

  3. College of Electrical Engineering, Hohai University, Nanjing, Jiangsu, 210098, China

    Changyin Sun

Authors
  1. Ning Sun
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  2. Wenming Zheng
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  3. Changyin Sun
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  4. Cairong Zou
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  5. Li Zhao
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Sun, N., Zheng, W., Sun, C., Zou, C., Zhao, L. (2006). Facial Expression Recognition Based on BoostingTree. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_12

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  • DOI: https://doi.org/10.1007/11760023_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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