Abstract
In this paper, we present a 3D registration algorithm based on simulated physical force/moment for articulated human motion tracking. Provided with sparsely reconstructed 3D human surface points from multiple synchronized cameras, the tracking problem is equivalent to fitting the 3D model to the scene points. The simulated physical force/ moment generated by the displacement between the model and the scene points is used to align the model with the scene points in an Iterative Closest Points (ICP) [1] approach. We further introduce a hierarchical scheme for model state updating, which automatically incorporates human kinematic constraints. Experimental results on both synthetic and real data from several unconstrained motion sequences demonstrate the efficiency and robustness of our proposed method.
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References
Besl, P., McKay, H.: A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)
Gavrila, D., Davis, L.: 3-D model-based tracking of humans in action: A multi-view approach. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, pp. 73–80. IEEE Computer Society Press, Los Alamitos (1996)
Delamarre, Q., Faugeras, O.: 3D articulated models and multi-view tracking with silhouettes. In: Proc. IEEE International Conference on Computer Vision, Corfu, Greece, vol. 2, pp. 716–721. IEEE Computer Society Press, Los Alamitos (1999)
Deutscher, J., Blake, A., Reid, I.: Articulated body motion capture by annealed particle filtering. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head, SC, USA, vol. 2, pp. 126–133. IEEE Computer Society Press, Los Alamitos (2000)
Han, T., Huang, T.: Articulated body tracking using dynamic belief propagation. In: Sebe, N., Lew, M.S., Huang, T.S. (eds.) Proc. IEEE International Workshop on Human-computer Interaction. LNCS, vol. 3766, pp. 26–35. Springer, Heidelberg (2005)
Cheung, K., Baker, S., Kanade, T.: Shape-from-silhouette of articulated objects and its use for human body kinematics estimation and motion capture. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, Madison, Wisconsin, USA, vol. 1, pp. I–77–I–84 (2003)
Cheung, K., Kanade, T., Bouguet, J., Holler, M.: A real time system for robust 3D voxel reconstruction of human motions. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head, SC, USA, vol. 2, pp. 714–720. IEEE Computer Society Press, Los Alamitos (2000)
Delamarre, Q., Faugeras, O.: 3D articulated models and multi-view tracking with physical forces. Computer Vision and Image Understanding 81(2), 328–357 (2001)
Demirdjian, D.: Enforcing constraints for human body tracking. In: Proc. Workshop on Multi-Object Tracking (2003)
Knoop, S., Vacek, S., Dillmann, R.: Modeling joint constraints for an articulated 3D human body model with artificial correspondences in ICP. In: Proc. IEEE-RAS International Conference on Humanoid Robots, Tsukuba, Japan, pp. 74–79 (December 2005)
Lab, C.G.
Franco, J., Boyer, E.: Exact polyhedral visual hulls. In: Proc. British Machine Vision Conference (2003)
Belongie, S., Malik, J.: Matching with shape context. In: Proc. IEEE Workshop on Content-based Access of Image and Video Libraries, Hilton Head, SC, USA, pp. 20–26. IEEE Computer Society Press, Los Alamitos (2000)
Kortgen, M., Park, G., Novotni, M., Klein, R.: 3D shape matching with 3D shape context. In: Proc. 7th Central European Seminar on Computer Graphics (April 2003)
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Ni, B., Winkler, S., Kassim, A. (2007). Articulated Object Registration Using Simulated Physical Force/Moment for 3D Human Motion Tracking. In: Elgammal, A., Rosenhahn, B., Klette, R. (eds) Human Motion – Understanding, Modeling, Capture and Animation. HuMo 2007. Lecture Notes in Computer Science, vol 4814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75703-0_15
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DOI: https://doi.org/10.1007/978-3-540-75703-0_15
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