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High density crowd tracking

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Uploaded on Jan 13, 2011

Results of a methio for tracking individual
targets in high density unstructured crowded scenes, a class
of crowded scenes where the motion of the crowd at any
given location is multi-modal over time. To this end we
adopted the Correlated Topic Model (CTM) in which each
scene is associated with a set of behavior proportions,where
behaviors represent distributions over low-level motion features.
Unlike some existing formulations, our model is capable
of capturing both the correlation amongst different
patterns of behavior as well as allowing for the multi-modal
nature of unstructured crowded scenes. In order to test our
approach we performed experiments on a range of unstructured
crowd domains, from cluttered time-lapse microscopy
videos of cell populations in vitro to videos of sporting
events. In each of these domains we found that explicitly
modeling the interrelationships between different behaviors
in the scene allowed us to improve tracking predictions.

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