3D Human Motion Tracking Using Progressive Particle Filter
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-89646-3_82
Reference9 articles.
1. Deutscher: Articulated Body Motion Capture by Annealed Particle Filtering. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 126–133 (2000)
2. Navarantnam: Hierarchical Part-Based Human Body Pose Estimation. In: Proc. British Machine Vision Conf., vol. 1, pp. 479–488 (2005)
3. Saboune: Using Interval Particle Filtering for Marker less 3D Human Motion Capture. In: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence, p. 7 (2005)
4. Schimidt: Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images. In: Proc IEEE International Conference on Automatic Face and Gesture Recognition, pp. 567–572 (2006)
5. Cheng: Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(8), 790–799 (1995)
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1. Dynamic Kernel-Based Progressive Particle Filter for 3D Human Motion Tracking;Computer Vision – ACCV 2009;2010
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