• DocumentCode
    595173
  • Title

    Efficient UAV video event summarization

  • Author

    Hoang Trinh ; Jun Li ; Miyazawa, Shintaro ; Moreno, J. ; Pankanti, Sharath

  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    2226
  • Lastpage
    2229
  • Abstract
    In the paper, we present an approach to efficiently summarizing UAV video data. Our approach is based on first detecting and tracking moving objects. Significant camera motion usually present in UAV video data is successfully handled by a robust feature-based frame registration technique. We then devise a saliency-based scoring method to score and rank detected object tracks. Object tracks are then grouped into video segments. The final step is to generate a concise summarization and visualization. Experimental results on the VIRAT UAV dataset show that we can accomplish a data reduction rate in excess of 1000 without significantly missing any activities of interest.
  • Keywords
    autonomous aerial vehicles; data reduction; data visualisation; image motion analysis; image registration; object detection; object tracking; video signal processing; UAV video data; UAV video event summarization; VIRAT UAV dataset; camera motion; data reduction rate; detected object track ranking; detected object track scoring; moving object detection; moving object tracking; robust feature-based frame registration technique; saliency-based scoring method; unmanned aerial vehicle; video segments; Cameras; Image segmentation; Mathematical model; Robustness; Surveillance; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460606