Multi-view Body Tracking with a Detector-Driven Hierarchical Particle Filter

  • Sergio Navarro
  • Adolfo López-Méndez
  • Marcel Alcoverro
  • Josep Ramon Casas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7378)


In this paper we present a novel approach to markerless human motion capture that robustly integrates body part detections in multiple views. The proposed method fuses cues from multiple views to enhance the propagation and observation model of particle filtering methods aiming at human motion capture. We particularize our method to improve arm tracking in the publicly available IXMAS dataset. Our experiments show that the proposed method outperforms other state-of-the-art approaches.


human motion capture body part detection multi-view 3D reconstruction inverse kinematics 


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  1. 1.
    Holte, M.B., Tran, C., Trivedi, M.M., Moeslund, T.B.: Human action recognition using multiple views: a comparative perspective on recent developments. In: ACM Workshop on HGBU. J-HGBU 2011, pp. 47–52. ACM, New York (2011)Google Scholar
  2. 2.
    Gall, J., Rosenhahn, B., Brox, T., Seidel, H.-P.: Optimization and filtering for human motion capture. IJCV 87, 75–92 (2010), doi:10.1007/s11263-008-0173-1CrossRefGoogle Scholar
  3. 3.
    Bandouch, J., Beetz, M.: Tracking humans interacting with the environment using efficient hierarchical sampling and layered observation models. In: IEEE Int. Workshop on Human-Computer Interaction (HCI) and ICCV 2009 (2009)Google Scholar
  4. 4.
    Wang, J.M., Fleet, D.J., Hertzmann, A.: Gaussian process dynamical models for human motion. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2), 283–298 (2008)CrossRefGoogle Scholar
  5. 5.
    Gall, J., Yao, A., Van Gool, L.: 2D Action Recognition Serves 3D Human Pose Estimation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part III. LNCS, vol. 6313, pp. 425–438. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Singh, V.K., Nevatia, R., Huang, C.: Efficient inference with multiple heterogeneous part detectors for human pose estimation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part III. LNCS, vol. 6313, pp. 314–327. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    López-Méndez, A., Alcoverro, M., Pardàs, M., Casas, J.: Real-time upper body tracking with online initialization using a range sensor. In: HCI-ICCV (2011)Google Scholar
  8. 8.
    Inria: The IXMAS Dataset (2006),
  9. 9.
    Deutscher, J., Blake, A., Reid, I.: Articulated body motion capture by annealed particle filtering. In: CVPR, vol. 2, pp. 126–133 (2000)Google Scholar
  10. 10.
    MacCormick, J., Isard, M.: Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking. In: Vernon, D. (ed.) ECCV 2000, Part II. LNCS, vol. 1843, pp. 3–19. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  11. 11.
    Bălan, A.O., Sigal, L., Black, M.J.: A quantitative evaluation of video-based 3d person tracking. In: IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS, pp. 349–356 (2005)Google Scholar
  12. 12.
    Jones, M.J., Rehg, J.M.: Statistical Color Models with Application to Skin Detection. In: CVPR, vol. 1, pp. 274–280 (1999)Google Scholar
  13. 13.
    Salvador, J., Suau, X., Casas, J.R.: From silhouettes to 3d points to mesh: towards free viewpoint video. In: Proceedings of the 1st International Workshop on 3D Video Processing, 3DVP 2010, pp. 19–24 (2010)Google Scholar
  14. 14.
    Rusu, R.B.: Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments. PhD thesis, Computer Science department, Technische Universitaet Muenchen, Germany (October 2009)Google Scholar
  15. 15.
    Friedman, J.H., Bentley, J.L., Finkel, R.A.: An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw. 3, 209–226 (1977)zbMATHCrossRefGoogle Scholar
  16. 16.
    Hauberg, S., Pedersen, K.S.: Predicting articulated human motion from spatial processes. IJCV 94(3), 317–334 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Kallmann, M.: Analytical inverse kinematics with body posture control. Comput. Animat. Virtual Worlds 19(2), 79–91 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sergio Navarro
    • 1
  • Adolfo López-Méndez
    • 1
  • Marcel Alcoverro
    • 1
  • Josep Ramon Casas
    • 1
  1. 1.Technical University of Catalonia (UPC)BarcelonaSpain

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