• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Journal articles
    • View Item
    • Home
    • Griffith Research Online
    • Journal articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • The Detection of Persons in Cluttered Beach Scenes using Digital Video Imagery and Neural Network-Based Classification

    Author(s)
    Green, Steven
    Blumenstein, Michael
    Browne, Matthew
    Tomlinson, Rodger
    Griffith University Author(s)
    Tomlinson, Rodger B.
    Year published
    2006
    Metadata
    Show full item record
    Abstract
    This paper presents an investigation into the detection and quantification of persons in real-world beach scenes for the automated monitoring of public recreation areas. Aside from the obvious use of video and digital imagery for surveillance applications, this research focuses on the analysis of images for the purpose of predicting trends in the intensity of public usage at beach sites in Australia. The proposed system uses image enhancement and segmentation techniques to detect objects in cluttered scenes. Following these steps, a newly proposed feature extraction technique is used to represent salient information in the ...
    View more >
    This paper presents an investigation into the detection and quantification of persons in real-world beach scenes for the automated monitoring of public recreation areas. Aside from the obvious use of video and digital imagery for surveillance applications, this research focuses on the analysis of images for the purpose of predicting trends in the intensity of public usage at beach sites in Australia. The proposed system uses image enhancement and segmentation techniques to detect objects in cluttered scenes. Following these steps, a newly proposed feature extraction technique is used to represent salient information in the extracted objects for training of a neural network. The neural classifier is used to distinguish the extracted objects between "person" and "non-person" categories to facilitate analysis of tourist activity. Encouraging results are presented for person classification on a database of real-word beach scene images.
    View less >
    Journal Title
    International Journal of Computational Intelligence and Applications
    Volume
    6
    Issue
    2
    Publisher URI
    http://www.worldscinet.com/ijcia/08/0802/S14690268090802.html
    DOI
    https://doi.org/10.1142/S1469026806001927
    Copyright Statement
    © 2006 Imperial College Press. Self-archiving of the author-manuscript version is not yet supported by this publisher. Please refer to International Journal of Computational Intelligence and Applications for access to the definitive, published version or contact the author for more information.
    Subject
    Information systems
    Information and computing sciences
    Publication URI
    http://hdl.handle.net/10072/11548
    Collection
    • Journal articles

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E
    • TEQSA: PRV12076

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander