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Presentation at Harvard, November 2007 (also talk at IEEE CVPR 2007, Minneapolis)
Presentation at BIRS, November 2006 (also talk at IEEE CVPR 2006, New York)
Learning Joint Top-down and Bottom-up Processes for 3D Visual Inference Paper (pdf), Talk (pdf), Video1 (variable background), Video 2 (3D reconstruction INRIA pedestrian), Video 3 (multiple people, automatic detection and 3D reconstruction)
Presentation at CMU, April 2006 (also talk at IEEE CVPR 2005, San Diego)
Static and Dynamic Ambiguities for 3D Human Pose Reconstruction
Paper: 3D Human Motion Reconstruction in Monocular Video. Techniques and Challenges (C. Sminchisescu), in Human Motion Capture: Modeling, Analysis, Animation, Springer, 2007
Video Set 1: Static, 3D from Monocular, Human Pose Reconstruction Ambiguities (Video)
Video Set 2: Dynamic, 3D from Video, Monocular Human Pose Reconstruction Ambiguities (noisy dynamics): Original Video, 2d tracking hypothesis 1, 3D reconstruction hypothesis 1 (filtered, smoothed), 2d tracking hypothesis 2, 3D reconstruction hypothesis 2 (filtered, smoothed)
Video Set 3: Dynamic, 3D from Video, Monocular Human Pose Reconstruction Ambiguities (state spaces restricted to non-linear manifolds learned from human motion capture data): Original Video, 2d tracking hypothesis 1, 3D reconstruction hypothesis 1, 2d tracking hypothesis 2, 3D reconstruction hypothesis 2
Optimization methods for ambiguous visual models with applications on 3D human tracking from monocular video given by Cristian Sminchisescu on 12/03/2003 at the Mittag-Leffler Institute of the Royal Swedish Academy of Sciences. The topic of the meeting was Vision from a Mathematical Perspective.
Talk at the IEEE CVPR, June 2003 (Madison, USA)
Kinematic jump sampling methods for monocular 3D human tracking given by Cristian Sminchisescu on 18/06/2003 at CVPR 2003.