Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Tracking, Identification and Classification of Random Finite Sets

    Access Status
    Fulltext not available
    Authors
    Vo, Ba Tuong
    Vo, Ba-Ngu
    Date
    2013
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Vo, Ba Tuong and Vo, Ba Ngu. 2013. Tracking, Identification and Classification of Random Finite Sets, in Kadar, I. (ed), Proceedings SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, Apr 29 2013. Baltimore, Maryland, USA: SPIE.
    Source Title
    Proceedings SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII
    Source Conference
    SPIE Security and Defence Symposium 2013
    DOI
    10.1117/12.2015370
    ISSN
    0277-786X
    URI
    http://hdl.handle.net/20.500.11937/22708
    Collection
    • Curtin Research Publications
    Abstract

    This paper considers the problem of joint multiple target tracking, identification, and classification. Standard approaches tend to treat the tasks of data association, estimation, track management and classification as separate problems. This paper outlines how it is possible to formulate a unified a Bayesian recursion for joint tracking, identification and classification. The formulation is based on the theory of random finite sets or finite set statistics, and specifically labeled random finite sets, which results in a propagation of a multi-target posterior which contains not only target information but all available track information. Implementations are briefly discussed. Where appropriate for particular applications this method can be considered Bayes optimal.

    Related items

    Showing items related by title, author, creator and subject.

    • Application of advanced techniques for the remote detection, modelling and spatial analysis of mesquite (prosopis spp.) invasion in Western Australia
      Robinson, Todd Peter (2008)
      Invasive plants pose serious threats to economic, social and environmental interests throughout the world. Developing strategies for their management requires a range of information that is often impractical to collect ...
    • A labeled random finite set online multi-object tracker for video data
      Kim, Du Yong; Vo, Ba-Ngu; Vo, Ba Tuong; Jeon, M. (2019)
      This paper proposes an online multi-object tracking algorithm for image observations using a top-down Bayesian formulation that seamlessly integrates state estimation, track management, handling of false positives, false ...
    • A Multiple-Detection Probability Hypothesis Density Filter
      Tang, X.; Chen, X.; McDonald, M.; Mahler, Ronald; Tharmarasa, R.; Kirubarajan, T. (2015)
      © 1991-2012 IEEE. Most conventional target tracking algorithms assume that one target can generate at most one detection per scan. However, in many practical target tracking applications, one target may generate multiple ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.