Abstract
This paper presents methods that utilize the advantages of modern graphics card hardware for real-time full body tracking with a 3D body model. By means of the presented methods the tracking of full body can be performed at frame-rates of 5 frames per second using a single low-cost moderately-priced graphics card and images from single camera. For a model with 26 DOF we achieved 15 times speed-up. The pose configuration is given by the position and orientation of the pelvis as well as relative joint angles between the connected limbs. The tracking is done through searching for a model configuration that best corresponds to the observed human silhouette in the input image. The searching is done via particle swarm optimization, where each particle corresponds to some hypothesized set of model parameters.
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Deutscher, J., Blake, A., Reid, I.: Articulated body motion capture by annealed particle filtering. In: IEEE Int. Conf. on Pattern Recognition, pp. 126–133 (2000)
Poppe, R.: Vision-based human motion analysis: an overview. Computer Vision and Image Understanding 108, 4–18 (2007)
Fritsch, J., Schmidt, J., Kwolek, B.: Kernel particle filter for real-time 3D body tracking in monocular color images. In: IEEE Int. Conf. on Face and Gesture Rec., Southampton, UK, pp. 567–572. IEEE Computer Society Press, Los Alamitos (2006)
Zhao, T., Nevatia, R., Wu, B.: Segmentation and tracking of multiple humans in crowded environments. PAMI 30, 1198–1211 (2008)
Wu, C., Aghajan, H.K.: Human pose estimation in vision networks via distributed local processing and nonparametric belief propagation. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2008. LNCS, vol. 5259, pp. 1006–1017. Springer, Heidelberg (2008)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. of IEEE Int. Conf. on Neural Networks, pp. 1942–1948. IEEE Press, Piscataway (1995)
Matsumoto, M., Nishimura, T.: Mersenne twister: a 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Trans. Model. Comput. Simul. 8, 3–30 (1998)
Box, G.E.P., Muller, M.E.: A note on the generation of random normal deviates. The Annals of Mathematical Statistics 29, 610–611 (1958)
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Krzeszowski, T., Kwolek, B., Wojciechowski, K. (2010). GPU-Accelerated Tracking of the Motion of 3D Articulated Figure. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15910-7_18
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DOI: https://doi.org/10.1007/978-3-642-15910-7_18
Publisher Name: Springer, Berlin, Heidelberg
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