Point target probabilistic multiple hypothesis tracking

Probabilistic Multiple Hypothesis Tracking (PMHT) is an algorithm for multi-target tracking in clutter with computational requirements, which are linear in the number of targets and the number of measurements. In order to achieve this, the PMHT removes the point target constraint, and uses the expectation maximisation procedure to optimise both data association probabilities and the target trajectory state estimates. However, PMHT is known to have high track-loss percentage in comparison with Probabilistic Data Association, at least in point target tracking. The authors propose a new PMHT-like algorithm to solve some problems of PMHT. In this study they revert the point target constraint. The authors call the new algorithm Point target PMHT. Simulation results show the efficiency of this method.This work was supported by the Defense Acquisition Program Administration and Agency for Defense Development, Korea, through the image Information Research Center at Korea Advanced Institute of Science and Technology under the contract UD100006 CD