Autonomous Multi-camera Tracking Using Distributed Quadratic Optimization

  • Yusuf OsmanlıoğluEmail author
  • Bahareh Shakibajahromi
  • Ali Shokoufandeh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)


Multi-camera object tracking is an efficient approach commonly used in security and surveillance systems. In a conventional multi-camera setup, a central computational unit processes large amounts of data in real time that is provided by distributed cameras. High network traffic, cost of storage on the central unit, scalability of the system, and vulnerability of the central unit to attacks are among the disadvantages of such systems. In this paper, we present an autonomous multi-camera tracking system to overcome these challenges. We assume cameras that are capable of limited computation for locally tracking a subset of objects in the scene, as well as peer-to-peer network connectivity among the cameras with a decent bandwidth that is sufficient for message passing to achieve coordination. We propose an efficient distributed algorithm for coordination and load-balancing among the cameras. We also provide experimental results to validate the utility of the proposed algorithm in comparison to a centralized algorithm.


Multi-camera tracking Distributed assignment problem Metric labeling Primal-dual approximation 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Section of Biomedical Image AnalysisUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of Computer ScienceDrexel UniversityPhiladelphiaUSA

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