Efficient characterization of labeling uncertainty in closely-spaced targets tracking

Carlos Moreno Leon, Carlos Moreno Leon, Hans Driessen, Pranab K. Mandal

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    4 Citations (Scopus)

    Abstract

    In this paper we propose a novel solution to the labeled multi-target tracking problem. The method presented is specially effective in scenarios where the targets have once moved in close proximity. When this is the case, disregarding the labeling uncertainty present in a solution (after the targets split) may lead to a wrong decision by the end user. We take a closer look at the main cause of the labeling problem. By modeling the possible crosses between the targets, we define some relevant labeled point estimates. We extend the concept of crossing objects, which is obvious in one dimension, to scenarios where the objects move in multiple dimensions. Moreover, we provide a measure of uncertainty associated to the proposed solution to tackle the labeling problem. We develop a novel, scalable and modular framework in line with it. The proposed method is applied and analyzed on the basis of one-dimensional objects and two-dimensional objects simulation experiments.
    Original languageUndefined
    Title of host publicationProceedings of the 19th International Conference on Information Fusion (FUSION)
    Place of PublicationPiscataway, NJ, USA
    PublisherIEEE
    Pages449-456
    Number of pages8
    ISBN (Print)978-0-9964-5274-8
    Publication statusPublished - 6 Jul 2016
    Event19th International Conference on Information Fusion, FUSION 2016 - Heidelberg, Germany, Heidelberg, Germany
    Duration: 5 Jul 20168 Jul 2016
    Conference number: 19

    Publication series

    Name
    PublisherIEEE

    Conference

    Conference19th International Conference on Information Fusion, FUSION 2016
    Abbreviated titleFUSION 2016
    CountryGermany
    CityHeidelberg
    Period5/07/168/07/16
    Other5-8 July 2016

    Keywords

    • Particle filter
    • closely-spaced targets
    • labelling uncertainty
    • METIS-319493
    • EC Grant Agreement nr.: FP7/607400
    • IR-102418
    • Multi-target tracking
    • EWI-27457

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