• DocumentCode
    3660019
  • Title

    Exploring the most appropriate feature detector and descriptor algorithm for on-board UAV image processing

  • Author

    Boxin Zhao;Tianjiang Hu;Yifeng Niu;Dengqing Tang;Zhaowei Ma;Weiwei Kong;Lincheng Shen

  • Author_Institution
    College of Mechatronics and Automation, National University of Defense Technology, Changsha, China, 410073
  • fYear
    2015
  • Firstpage
    56
  • Lastpage
    61
  • Abstract
    With the development of computer vision technology, many researches about feature detectors and descriptors have been published in the last decades. In order to explore what kind of approaches are appropriate for unmanned aerial vehicle (UAV) onboard video processing, the popular feature detectors and descriptors are analyzed and combined with each other. Three practical videos captured in indoor environments and outdoor environments are used to test the accuracy, runtime and robustness of these combined algorithms. Results validate that the combinations of different feature detectors and descriptors balance well the accuracy and runtime. This will provide references for choosing appropriate onboard video processing algorithms.
  • Keywords
    "Detectors","Accuracy","Feature extraction","Runtime","Robustness","Cameras","Indexes"
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICInfA.2015.7279258
  • Filename
    7279258