A PHD (probability hypothesis density) filter and multiscan association are combined in a feedback fashion in order to provide robust and efficient multitarget tracking. The resulting hybrid tracker, thanks to the feedback connection, provides remarkable performance improvements with respect to both an open-loop PHD filter with estimate extraction via clustering and a traditional tracker equipped with a track formation logic.
Multitarget tracking via joint PHD filtering and multiscan association / F. Papi; G. Battistelli; L. Chisci; S. Morrocchi; A. Farina; A. Graziano. - STAMPA. - (2009), pp. 1163-1170. (Intervento presentato al convegno 12th International Conference on Information Fusion, FUSION 2009 tenutosi a Seattle, USA).
Multitarget tracking via joint PHD filtering and multiscan association
PAPI, FRANCESCO;BATTISTELLI, GIORGIO;CHISCI, LUIGI;
2009
Abstract
A PHD (probability hypothesis density) filter and multiscan association are combined in a feedback fashion in order to provide robust and efficient multitarget tracking. The resulting hybrid tracker, thanks to the feedback connection, provides remarkable performance improvements with respect to both an open-loop PHD filter with estimate extraction via clustering and a traditional tracker equipped with a track formation logic.
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