• DocumentCode
    2017187
  • Title

    Moving Object Extraction in Complex Scenes

  • Author

    Fan, Sicun ; Liu, Zhijing

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an
  • Volume
    2
  • fYear
    2008
  • fDate
    17-18 Oct. 2008
  • Firstpage
    126
  • Lastpage
    129
  • Abstract
    Moving object detection plays an important roll in intelligent monitor system; it may have a direct influence on the final detection result. In this paper, a self-adaptive system of moving object detection based on Gaussian mixture models (GMM) is designed, and this method can reduce some unfavorable influences, such as weather or lighting changes. Moreover, this paper modifies the algorithm of combination of background subtraction method and temporal differencing method, makes the contour of moving object more precise and removes environmental noise points effectively. Many experiments on outdoor video streams are tested and the results have shown that this method gives stable performance and good robustness.
  • Keywords
    Gaussian distribution; edge detection; image denoising; image sequences; motion estimation; object detection; video signal processing; Gaussian distribution mixture model; background subtraction method; complex scene; environmental noise removal; intelligent video monitor system; moving object contour extraction; moving object detection; outdoor video stream; self-adaptive system; temporal differencing method; Computational intelligence; Computer science; Computerized monitoring; Data mining; Gaussian distribution; Image motion analysis; Intelligent systems; Layout; Object detection; Optical filters; Gaussian Mixture Models; background subtraction method; moving object extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3311-7
  • Type

    conf

  • DOI
    10.1109/ISCID.2008.168
  • Filename
    4725473