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Recognizing Two Handed Gestures with Generative, Discriminative and Ensemble Methods Via Fisher Kernels

  • Oya Aran
  • Lale Akarun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4105)

Abstract

Use of gestures extends Human Computer Interaction (HCI) possibilities in multimodal environments. However, the great variability in gestures, both in time, size, and position, as well as interpersonal differences, makes the recognition task difficult. With their power in modeling sequence data and processing variable length sequences, modeling hand gestures using Hidden Markov Models (HMM) is a natural extension. On the other hand, discriminative methods such as Support Vector Machines (SVM), compared to model based approaches such as HMMs, have flexible decision boundaries and better classification performance. By extracting features from gesture sequences via Fisher Kernels based on HMMs, classification can be done by a discriminative classifier. We compared the performance of this combined classifier with generative and discriminative classifiers on a small database of two handed gestures recorded with two cameras. We used Kalman tracking of hands from two cameras using center-of-mass and blob tracking. The results show that (i) blob tracking incorporates general hand shape with hand motion and performs better than simple center-of-mass tracking, and (ii) in a stereo camera setup, even if 3D reconstruction is not possible, combining 2D information from each camera at feature level decreases the error rates, and (iii) Fisher Score methodology combines the powers of generative and discriminative approaches and increases the classification performance.

Keywords

Support Vector Machine Hide Markov Model Gesture Recognition Hand Gesture Fisher Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Ong, S.C.W., Ranganath, S.: Automatic sign language analysis: A survey and the future beyond lexical meaning. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 873–891 (2005)CrossRefGoogle Scholar
  2. 2.
    Pavlovic, V., Sharma, R., Huang, T.S.: Visual interpretation of hand gestures for human-computer interaction: A review. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 677–695 (1997)CrossRefGoogle Scholar
  3. 3.
    Heckenberg, D., Lovell, B.C.: MIME: A gesture-driven computer interface. In: Visual Communications and Image Processing, SPIE, Perth, Australia, vol. 4067, pp. 261–268 (2000)Google Scholar
  4. 4.
    Wu, Y., Huang, T.S.: Hand modeling, analysis, and recognition for vision based human computer interaction. IEEE Signal Processing Magazine 21, 51–60 (2001)Google Scholar
  5. 5.
    Jaakkola, T.S., Haussler, D.: Exploiting generative models in discriminative classifiers. In: Proceedings of the 1998 Conference on Advances in Neural Information Processing Systems II, pp. 487–493. MIT Press, Cambridge (1998)Google Scholar
  6. 6.
    Smith, N., Gales, M.: Using SVMs to classify variable length speech patterns. Technical report, Cambridge University Engineering Department (2002)Google Scholar
  7. 7.
    Holub, A., Welling, M., Perona, P.: Combining generative models and fisher kernels for object class recognition. In: Int. Conference on Computer Vision (2005)Google Scholar
  8. 8.
    Liu, N., Lovell, B.C., Kootsookos, P.J., Davis, R.I.A.: Model structure selection and training algorithms for a HMM gesture recognition system. In: International Workshop in Frontiers of Handwriting Recognition, Tokyo, pp. 100–106 (2004)Google Scholar
  9. 9.
    Marcel, S., Just, A.: (IDIAP Two handed gesture dataset), available at: http://www.idiap.ch/~marcel/
  10. 10.
    Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines (2001), Software available at: http://www.csie.ntu.edu.tw/~cjlin/libsvm

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Oya Aran
    • 1
  • Lale Akarun
    • 1
  1. 1.Department of Computer EngineeringBogazici UniversityIstanbulTurkey

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