• DocumentCode
    2067818
  • Title

    Commentary Paper 1 on "On Stable Dynamic Background Generation Technique Using Gaussian Mixture Models for Robust Object Detection"

  • Author

    Visentini, Ingrid

  • Author_Institution
    Univ. of Udine, Udine, Italy
  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    49
  • Lastpage
    49
  • Abstract
    In this paper a technique for motion detection that exploits the Gaussian mixture models (GMM) and basic background subtraction (BBS) is proposed. For every frame, each pixel is modeled with almost K Gaussian distributions. All the existing GMM based techniques use a threshold to set a priori the number of Gaussians to represent the background. The proposed approach avoids setting this threshold. The results show the effectiveness of the novel approach on benchmarks test sets sequences.
  • Keywords
    Gaussian distribution; Gaussian processes; object detection; Gaussian distributions; Gaussian mixture models; basic background subtraction; robust object detection; stable dynamic background generation technique; Benchmark testing; Gaussian distribution; Motion detection; Object detection; Robustness; Signal generators; Surveillance; Videoconference; Weaving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance, 2008. AVSS '08. IEEE Fifth International Conference on
  • Conference_Location
    Santa Fe, NM
  • Print_ISBN
    978-0-7695-3341-4
  • Electronic_ISBN
    978-0-7695-3422-0
  • Type

    conf

  • DOI
    10.1109/AVSS.2008.55
  • Filename
    4730381