• DocumentCode
    133704
  • Title

    Ship detection for automating navigational watch

  • Author

    Matsumoto, Yohei

  • Author_Institution
    Dept. of Marine Eng., Tokyo Univ. of Marine Sci. & Technol., Tokyo, Japan
  • fYear
    2014
  • fDate
    3-7 Aug. 2014
  • Firstpage
    103
  • Lastpage
    108
  • Abstract
    Automatic navigational watch system is currently under development. Because the system should detect ships over a miles away from own ship, the depth of the field is extremely deeper than that of ordinal computer vision applications. This paper shows the results applying typical HOG (Histograms of Oriented Gradients)-SVM (Support Vector Machine) based sliding window object detector to the navigational images, and discusses the difficulties and their possible remedies.
  • Keywords
    computer vision; computerised navigation; marine navigation; object detection; ships; support vector machines; HOG-SVM; automatic navigational watch system; computer vision application; histograms of oriented gradient; ship detection; sliding window object detector; support vector machine; Manuals; Support vector machine classification; Training; HOG; Navigation; SVM; Ship;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    World Automation Congress (WAC), 2014
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/WAC.2014.6935702
  • Filename
    6935702