• DocumentCode
    714367
  • Title

    Vessel classification on UAVs using inertial data and IR imagery

  • Author

    Demir, H. Seckin ; Akagunduz, Erdem ; Kubilay Pakin, S.

  • Author_Institution
    ASELSAN, MGEO, Ankara, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    499
  • Lastpage
    502
  • Abstract
    In this study, a civilian ship dataset is constructed via images captured by an infrared camera on an unmanned flying vehicle. By using this dataset and synchronized inertial data (UAV altitude and orientation, gimbal angles), a vessel classification method is proposed. The method first calculates the ship base length in meters by using segmented ship image and inertial data. By fusing the descriptors obtained from the segmented ship images and estimated ship base length, vessel classification is performed.
  • Keywords
    autonomous aerial vehicles; image classification; image segmentation; infrared imaging; IR imagery; UAV; civilian ship dataset; infrared camera; segmented ship image; ship base length; synchronized inertial data; unmanned flying vehicle; vessel classification; Augmented reality; Cameras; Computer vision; Histograms; Image segmentation; Marine vehicles; Vehicles; inertial data; infrared imaging; vessel classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7129869
  • Filename
    7129869