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2008

Integrating robust likelihoods with Monte-Carlo filters for multi-target tracking

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Integrating robust likelihoods with Monte-Carlo filters for multi-target tracking
In this paper, a dynamic multi-modal fusion scheme for tracking multiple targets with Monte-Carlo filters is presented, with the goal of achieving robustness by combining complimentary likelihoods based on color and foreground segmentation. The generality of the proposed approach allows defining the measurements on different levels (pixel-, feature- and object-space) through dynamic data fusion. We demonstrate the approach in a people tracking context, by using a multi-target MCMC particle filter.
Giorgio Panin, Thorsten Röder, Alois Knoll
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2008
Where VMV
Authors Giorgio Panin, Thorsten Röder, Alois Knoll
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