We introduce a new approach to tracking a large number of objects. Specifically we consider tracking in the context of higher order Markov interactions which can not be modeled using network flow techniques as currently developed. Our approach relies on delayed column generation and is inspired by the corresponding approach to the cutting stock problem. Columns can be generated exactly using dynamic programming.
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