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» A Probabilistic Framework for Combining Tracking Algorithms
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IJCV
2000
161views more  IJCV 2000»
13 years 7 months ago
Probabilistic Detection and Tracking of Motion Boundaries
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Michael J. Black, David J. Fleet
ICCV
2001
IEEE
14 years 9 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
FGCS
1992
107views more  FGCS 1992»
13 years 8 months ago
Logic Programming, Abduction and Probability
Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning into a coherent practical framework. The numbers can be consistently interpreted ...
David Poole
CVPR
2010
IEEE
14 years 3 months ago
Efficient Extraction of Human Motion Volumes by Tracking
We present an automatic and efficient method to extract spatio-temporal human volumes from video, which combines top-down model-based and bottom-up appearancebased approaches. Fr...
Juan Carlos Niebles, Bohyung Han, Li Fei-Fei
TMI
2008
122views more  TMI 2008»
13 years 7 months ago
Tractography Gone Wild: Probabilistic Fibre Tracking Using the Wild Bootstrap With Diffusion Tensor MRI
Diffusion tensor magnetic resonance imaging (DT-MRI) permits the noninvasive assessment of tissue microstructure and, with fibre-tracking algorithms, allows for the 3-D trajectorie...
D. K. Jones