Multi-object Tracking: Explicit Knowledge Representation and Implementation for Complexity Reduction

Many successful single-object tracking algorithms are formulated or may be reformulated as Bayesian inference problem. It is straight-forward to generalize the Bayesian formulation to the problem of multi-object tracking. However, due to the increase in dimensionality this formulation also opens Pandora’s box in terms of exponential explosion of the computational complexity. In this paper we propose to constraint the computational complexity by exploiting and explicitly using prior knowledge at various levels of the Bayesian formulation of multi-object tracking. More specifically we discuss the use of a knowledge hierarchy which makes explicit where and how to introduce available knowledge.

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