Efficient multi-target tracking via discovering dense subgraphs
In this paper, we cast multi-target tracking as a dense subgraph discovering problem on the undirected relation graph of all given target hypotheses. We aim to extract multiple clusters (dense subgraphs), in which each cluster contains a set of hypotheses of one particular target. In the presence of occlusion or similar moving targets or when there is no reliable evidence for the target’s presence, each target trajectory is expected to be fragmented into multiple tracklets. The proposed...[Show more]
|Collections||ANU Research Publications|
|Source:||Computer Vision and Image Understanding|
|01_Bozorgtabar_Efficient_multi-target_2016.pdf||3.24 MB||Adobe PDF||Request a copy|
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