• DocumentCode
    3129294
  • Title

    Efficient Multi-Layer Background Model on Complex Environment for Foreground Object Detection

  • Author

    Tsai, Wen-kai ; Sheu, Ming-hwa ; Lin, Chung-chi

  • Author_Institution
    Grad. Sch. of Eng. Sci. & Technol., Nat. Yunlin Univ. of Sci. & Technol., Yunlin, Taiwan
  • fYear
    2010
  • fDate
    15-17 Oct. 2010
  • Firstpage
    292
  • Lastpage
    295
  • Abstract
    This paper proposes an establishment of multi-layer background model, which can be used in a complex environment scene. In general, the surveillance system focuses on detecting the moving object, but in the real scenes there are many moving background, such as dynamic leaves, falling rain etc. In order to detect the object in the moving background environment, we use exponential distribution function to update background model and combine background subtraction with homogeneous region analysis to find out foreground object. The system uses the TI TMS320DM6446 Davinci development platform, and it can achieve 20 frames per second for benchmark images of size 160 × 120. From the experimental results, our approach has better performance in terms of detection accuracy and similarity measure, when comparing with other modeling techniques methods.
  • Keywords
    exponential distribution; image motion analysis; object detection; surveillance; TI TMS320DM6446 Davinci development platform; complex environment scene; exponential distribution function; foreground moving object detection; multilayer background model; surveillance system; Adaptation model; Analytical models; Computational modeling; Object detection; Pixel; Real time systems; Signal processing; background modeling; object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010 Sixth International Conference on
  • Conference_Location
    Darmstadt
  • Print_ISBN
    978-1-4244-8378-5
  • Electronic_ISBN
    978-0-7695-4222-5
  • Type

    conf

  • DOI
    10.1109/IIHMSP.2010.80
  • Filename
    5638033