Dense Multiperson Tracking with Robust Hierarchical Linear Assignment

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Abstract

We introduce a novel dual-stage algorithm for online multi-target tracking in realistic conditions. In the first stage, the problem of data association between tracklets and detections, given partial occlusion, is addressed using a novel occlusion robust appearance similarity method. This is used to robustly link tracklets with detections without requiring explicit knowledge of the occluded regions. In the second stage, tracklets are linked using a novel method of constraining the linking process that removes the need for ad-hoc tracklet linking rules. In this method, links between tracklets are permitted based on their agreement with optical flow evidence. Tests of this new tracking system have been performed using several public datasets.
Original languageEnglish
Pages (from-to)1276-1288
Number of pages13
JournalIEEE Transactions on Cybernetics
Volume45
Issue number7
Early online date05 Sep 2014
DOIs
Publication statusPublished - Jul 2015

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