• DocumentCode
    231969
  • Title

    Moving object detection in dynamic background

  • Author

    Liu Ting ; Chi Hai-hong ; Hong Chao ; Zhao Meng-shou

  • Author_Institution
    Coll. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    4914
  • Lastpage
    4919
  • Abstract
    A new method of detecting moving object in dynamic background is proposed in this paper. At first, an adaptive threshold Harris algorithm is proposed in this paper to extract feature points, then, SIFT algorithm is used to describe these extracted feature points. The similarity function is used to match feature points and RANSAC algorithm is used to eliminate the pseudo matches. According to the correct matches, we get the affine transformation matrix which used to compensate the motion of background caused by camera motion, and update the dynamic background with the background model. Finally, the moving object can be detected by background subtraction method. Experimental results show that the method presented in this paper improves the accuracy of feature point extraction and detects moving target in dynamic background accurately.
  • Keywords
    affine transforms; feature extraction; image matching; matrix algebra; motion compensation; object detection; RANSAC algorithm; SIFT algorithm; adaptive threshold Harris algorithm; affine transformation matrix; background subtraction method; camera motion; dynamic background model; feature point extraction; motion compensation; moving object detection; pseudomatching; similarity function; Accuracy; Algorithm design and analysis; Dynamics; Feature extraction; Heuristic algorithms; Motion compensation; Object detection; Background Modeling; Harris-SIFT Algorithm; Motion Compensation; Moving Object Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2014 33rd Chinese
  • Conference_Location
    Nanjing
  • Type

    conf

  • DOI
    10.1109/ChiCC.2014.6895773
  • Filename
    6895773