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Efficient Multiple People Tracking Using Minimum Cost Arborescences

  • Roberto Henschel
  • Laura Leal-Taixé
  • Bodo Rosenhahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8753)

Abstract

We present a new global optimization approach for multiple people tracking based on a hierarchical tracklet framework. A new type of tracklets is introduced, which we call tree tracklets. They contain bifurcations to naturally deal with ambiguous tracking situations. Difficult decisions are postponed to a later iteration of the hierarchical framework, when more information is available. We cast the optimization problem as a minimum cost arborescence problem in an acyclic directed graph, where a tracking solution can be obtained in linear time. Experiments on six publicly available datasets show that the method performs well when compared to state-of-the art tracking algorithms.

Keywords

Time Complexity False Detection Data Association Hierarchical Framework Social Force Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Roberto Henschel
    • 1
  • Laura Leal-Taixé
    • 2
  • Bodo Rosenhahn
    • 1
  1. 1.Institut Für InformationsverarbeitungLeibniz Universität HannoverHannoverGermany
  2. 2.Institute of Geodesy and PhotogrammetryETH ZurichZurichSwitzerland

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