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The track-oriented multiple hypothesis tracker is currently the preferred method for tracking multiple targets in clutter with medium to high computational resources. This method maintains a structured representation of the track posterior distribution, which it repeatedly extends and optimizes over. This representation of the posterior admits probabilistic inference tasks beyond MAP estimation that have yet to be explored. To this end we formulate the posterior as a graphical model and showdoi:10.1109/ssp.2012.6319817 dblp:conf/ssp/FrankSI12 fatcat:epehfy5yhrdl7hxnouswqw6g3u