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Conditional Random People: Tracking Humans with CRFs and Grid Filters
(2005-12-01)
We describe a state-space tracking approach based on a Conditional Random Field(CRF) model, where the observation potentials are \emph{learned} from data. Wefind functions that embed both state and observation into a space ...
Combining Object and Feature Dynamics in Probabilistic Tracking
(2005-03-02)
Objects can exhibit different dynamics at different scales, a property that isoftenexploited by visual tracking algorithms. A local dynamicmodel is typically used to extract image features that are then used as inputsto a ...