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Bimanual Hand Tracking

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Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3980))

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Abstract

This paper proposes a novel real-time hand tracking algorithm in the presence of occlusion. For this purpose, we construct a limb model and maintain the model obtained from ARKLT methods with respect to second-order auto-regression model and Kanade-Lucas-Tomasi(KLT) features, respectively. Furthermore, this method do not require to categorize types of superimposed hand motion based on directivity obtained by the slope’s direction of KLT regression. Thus, we can develop a method of hand tracking for gesture and activity recognition techniques frequently used in conjunction with Human-Robot Interaction (HRI) components.

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References

  1. Shan, C., et al.: Real time hand tracking by combining particle filtering and mean shift. In: IEEE International Conference on Automatic Face and Gesture Recognition (2004)

    Google Scholar 

  2. Kolsch, M., Turk, M.: Real time hand tracking by combining particle filtering and mean shift. In: IEEE International Conference on Automatic Face and Gesture Recognition (2004)

    Google Scholar 

  3. Fei, H., Reid, I.: Probabilistic tracking and recognition of non-rigid hand motion. In: IEEE International Workshop on Analysis and Modeling of Faces and Gestures (2003)

    Google Scholar 

  4. Ishihara, T., Otsu, N.: Gesture recognition using auto-regressive coefficients of higher-order local auto-correlation features. In: Proceedings of IEEE International Conference on Automatic Face and Gesture Recogniiton (2004)

    Google Scholar 

  5. Francçis, A.: Real-time multi-resolution blob tracking. IRIS Technical Report, 827–840 (2004)

    Google Scholar 

  6. Shamaie, A., Sutherland, A.: A dynamic model for real-time tracking of hands in bimanual movements. In: Gesture Workshop (2003)

    Google Scholar 

  7. McKenna, S.J., McAllister, G., Ricketts, I.W.: Hand tracking for behavior understanding. Image and Vision Computing 20, 827–840 (2002)

    Article  Google Scholar 

  8. Blake, A., Isard, M.: Active Contours (2000)

    Google Scholar 

  9. Shi, J., Tomasi, C.: Good feature to track. In: Proc. IEEE Conference on Computer Vision and Pattern Recognitionl (1994)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Human Robot Interaction Research Team, Intelligent Robot Research Division, ETRI, 161 Gajeong-Dong, Yuseong-Gu, Daejeon, 305-350, Korea

    Hye-Jin Kim, Keun-Chang Kwak & Jaeyeon Lee

Authors
  1. Hye-Jin Kim
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  2. Keun-Chang Kwak
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  3. Jaeyeon Lee
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kim, HJ., Kwak, KC., Lee, J. (2006). Bimanual Hand Tracking. In: Gavrilova, M., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3980. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751540_104

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  • DOI: https://doi.org/10.1007/11751540_104

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34070-6

  • Online ISBN: 978-3-540-34071-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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