IEEE Trans Image Process - Video tracking based on sequential particle filtering on graphs.

Tópicos

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Resumo

In this paper, we develop a novel solution for particle filtering on general graphs. We provide an exact solution for particle filtering on directed cycle-free graphs. The proposed approach relies on a partial-order relation in an antichain decomposition that forms a high-order Markov chain over the partitioned graph. We subsequently derive a closed-form sequential updating scheme for conditional density propagation using particle filtering on directed cycle-free graphs. We also provide an approximate solution for particle filtering on general graphs by splitting graphs with cycles into multiple directed cycle-free subgraphs. We then use the sequential updating scheme by alternating among the directed cycle-free subgraphs to obtain an estimate of the density propagation. We rely on the proposed method for particle filtering on general graphs for two video tracking applications: 1) object tracking using high-order Markov chains; and 2) distributed multiple object tracking based on multi-object graphical interaction models. Experimental results demonstrate the improved performance of the proposed approach to particle filtering on graphs compared with existing methods for video tracking.

Resumo Limpo

paper develop novel solut particl filter general graph provid exact solut particl filter direct cyclefre graph propos approach reli partialord relat antichain decomposit form highord markov chain partit graph subsequ deriv closedform sequenti updat scheme condit densiti propag use particl filter direct cyclefre graph also provid approxim solut particl filter general graph split graph cycl multipl direct cyclefre subgraph use sequenti updat scheme altern among direct cyclefre subgraph obtain estim densiti propag reli propos method particl filter general graph two video track applic object track use highord markov chain distribut multipl object track base multiobject graphic interact model experiment result demonstr improv perform propos approach particl filter graph compar exist method video track

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