Multiple Hypothesis Tracking Using Hough Transform Track Detector

The Multiple Hypothesis Tracking algorithm (MHT) is an effective algorithm for moving objects detection and tracking.1,2 Few versions of this complex algorithm are described and evaluated in 1,2,4. Its measurement oriented version is considered as the most effective from theoretical point of view, but its practical implementation is limited because of the required significant computational load in cluttered environment. Several techniques minimizing this load were proposed,1,2,4 but they do not provide general solution to these problems. A new problem solution is proposed in this paper. A Hough Transform (HT) track detector is used for preliminary filtering of arriving false alarms (FA). The tracks detected in this way are processed asynchronously with another standard MHT algorithm to include them in the overall MHT scheme. The standard and the proposed MHT-HT algorithm (MHT2-HT) are evaluated and compared in the paper. The proposed algorithm shows remarkably good performance in cluttered environment at the cost of delayed track detection process.