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For more recent talks please see our home and publication pages.
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.