Abstract
In this paper, we combine two approaches to multiple-target tracking: the first is a hierarchical approach to iteratively growing track fragments across gaps in detections, and the second is a network flow based optimization method for data association. We introduce a new parallel algorithm for initial track fragment formation as the base of the hierarchical approach. The network flow based optimization method is then utilized for the remaining levels of the hierarchy. This process is applied to solar data retrieved from the Heliophysics Event Knowledgebase (HEK). We compare our results to labeled data from the same, and show improvements over a non-hierarchical sequential approach.
Published Version
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