Human Motion Capture Using Data Fusion of Multiple Skeleton Data

  • Jean-Thomas Masse
  • Frédéric Lerasle
  • Michel Devy
  • André Monin
  • Olivier Lefebvre
  • Stéphane Mas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)


Joint advent of affordable color and depth sensors and super-realtime skeleton detection, has produced a surge of research on Human Motion Capture. They provide a very important key to communication between Man and Machine. But the design was willing and closed-loop interaction, which allowed approximations and mandates a particular sensor setup. In this paper, we present a multiple sensor-based approach, designed to augment the robustness and precision of human joint positioning, based on delayed logic and filtering, of skeleton detected on each sensor.


Human Posture Reconstruction Motion Capture Data Fusion Delayed Logic Kalman Filter Kinect 


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  1. 1.
    Alfonso, D.: Microsoft Investor Relations - Press Release, (accessed January 27, 2011)
  2. 2.
    Freedman, B., Shpunt, A., Arieli, Y.: Distance-Varying Illumination and Imaging Techniques for Depth Mapping. United States Patent US 20100290698 A1 (November 18, 2010)Google Scholar
  3. 3.
  4. 4.
    WordPress: OpenNI | The standard framework for 3D sensing,
  5. 5.
    PrimeSense: NiTE Middleware - PrimeSense,
  6. 6.
    Binney, D., Boehm, J.: Performance Evaluation of the PrimeSense IR Projected Pattern Depth Sensor, University College London, London, United Kingdom (2011)Google Scholar
  7. 7.
    Andersen, M., Jensen, T., Lisouski, P., Mortensen, A., Hansen, M., Gregsersen, T., Ahrendt, P.: Kinect Depth Sensor Evaluation for Computer Vision Applications, Aarhus (2012)Google Scholar
  8. 8.
    Zhang, L., Sturm, J., Cremers, D., Lee, D.: Real-Time Human Motion Tracking using Multiple Depth Cameras. In: Proc. of the International Conference on Intelligent Robot Systems, IROS (2012)Google Scholar
  9. 9.
    Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-time human pose recognition in parts from single depth images. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1297–1304 (2011)Google Scholar
  10. 10.
    Taylor, J., Shotton, J., Sharp, T., Fitzgibbon, A.: The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 103–110 (2012)Google Scholar
  11. 11.
    Moeslund, T., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding 104(2-3), 90–126 (2006)CrossRefGoogle Scholar
  12. 12.
    Deutscher, J., Reid, I.: Articulated Body Motion Capture by Stochastic Search. International Journal of Computer Vision 61(2), 185–205 (2005)CrossRefGoogle Scholar
  13. 13.
    Hofmann, M., Gavrila, D.: Multi-view 3D Human Pose Estimation combining Single-frame Recovery, Temporal Integration and Model Adaptation. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 2214–2221 (2009)Google Scholar
  14. 14.
    Abramov, A., Pauwels, K., Papon, J., Worgotter, F., Dellen, B.: Depth-supported real-time video segmentation with the Kinect. In: IEEE Workshop on Applications of Computer Vision (WACV), pp. 457–464 (2012)Google Scholar
  15. 15.
    Forsyth, D., Arikan, O., Ikemoto, L., O’Brien, J., Ramanan, D.: Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis. In: Foundations and Trends in Computer Graphics and Vision (2006)Google Scholar
  16. 16.
    Wojek, C., Walk, S., Schiele, B.: Multi-cue onboard pedestrian detection. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, Miami, FL, pp. 794–801 (2009)Google Scholar
  17. 17.
    Benfold, B., Reid, I.: Stable Multi-Target Tracking in Real-Time Surveillance Video. In: CVPR, pp. 3457–3464 (2011)Google Scholar
  18. 18.
    Berclaz, J., Fleuret, F., Fua, P.: Robust People Tracking with Global Trajectory Optimization. In: Society, I. (ed.) Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 744–750 (2006)Google Scholar
  19. 19.
    Andriluka, M., Roth, S., Schiele, B.: People-Tracking-by-Detection and People-Detection-by-Tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, Anchorage (2008)Google Scholar
  20. 20.
    Sigal, L., Balan, A., Black, M.: HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion. International Journal of Computer Vision 87(1-2), 4–27 (2010)CrossRefGoogle Scholar
  21. 21.
    Larson, R.E., Peschon, J.: A dynamic programming approach to trajectory estimation. IEEE Transactions on Automatic Control 11(3), 537–540 (1966)CrossRefGoogle Scholar
  22. 22.
    Viterbi, A.J.: A personal history of the Viterbi algorithm. IEEE Signal Processing Magazine 23(4), 120–142 (2006)CrossRefGoogle Scholar
  23. 23.
    Mekonnen, A.A., Lerasle, F., Herbulot, A.: Cooperative passers-by tracking with a mobile robot and external cameras. Computer Vision and Image Understanding (2012)Google Scholar
  24. 24.
    Maybeck, P.: Stochastic models, estimation, and control. Academic Press (1979)Google Scholar
  25. 25.
    Maloney, R.: Movement Analysis Products, (accessed January 4, 2013)
  26. 26.
    Herrera, C., Kannala, D., Heikkila, J., Joint Depth, J.: Color Camera Calibration with Distortion Correction. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(10) (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jean-Thomas Masse
    • 1
    • 2
  • Frédéric Lerasle
    • 1
    • 3
  • Michel Devy
    • 1
  • André Monin
    • 1
  • Olivier Lefebvre
    • 2
  • Stéphane Mas
    • 2
  1. 1.CNRS, Laboratoire d’Analyse et d’Architecture des SystèmesToulouseFrance
  2. 2.Magellium SASRamonville Saint-AgneFrance
  3. 3.Université de ToulouseToulouseFrance

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