Recent applications of spatial point processes to multiple-object tracking
Seminar Room 1, Newton Institute
AbstractThe Point Process framework is natural for the multiple-object tracking problem and is increasingly playing a central role in the derivation of new inference schemes. Interest in this framework is largely due to the derivation of a filter that propagates the first moment of a Markov-in-time Spatial Point Processes observed in noise by Ronald Mahler. Since then there have been several extensions to this result with accompanying numerical implementations based on Sequential Monte Carlo. These results will be presented.
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