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RGB Motion Segmentation using Background Subtraction based on AMF

  • Kim, Yoon-Ho (Dovosopn of comvergence computer & media fo Mokwon University)
  • Received : 2014.01.02
  • Accepted : 2014.01.27
  • Published : 2014.03.31

Abstract

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

Keywords

References

  1. Gary Brodski and Adrian Kaehler, "Learning OpenCV", O'Reilly, 2008.
  2. Thanarat Horprasert, David Harwood, Larry S. Davis, "A statistical approach for real-time robust background subtraction and shadow detection", 1999.
  3. Sen-Ching S. Cheung, Chandrika Kamath, "Robust techniques for background subtraction in urban traffic video", proceedings of the SPIE, Vol. 5308, pp. 881-892, 2004.
  4. T.Bouwmans, F. E Baf, B.Vachon, "Background Modeling using Mixture of Gaussians for Foreground Detection - A Survay", Recent Patents on Computer Science, Vol. 1, no. 3, 219-237, 2008. https://doi.org/10.2174/2213275910801030219
  5. Swantje Johnsen and Ashkey Tews, "Real-Time Object Tracking and Classification Using a Static Camera", Proceedings of the IEEE ICRA 2009, Workshop on People Detection and Tracking, Kobe,Japan,May,2009.
  6. P.Remagnino et al., "An integrated traffic and pedestrian model-based vision system", Proceedings of BMVC97, Vol. 2, Colchester, 8-11 th September, UniversityofEssex, UK, pp380-389, 1997.
  7. N.McFarlane and C. Shofield, "Segmentation and tracking of piglets in images", Machine Vision and Applications, Springer, Vol. 8, no.3, 1995.
  8. Seth Benton, "Background subtraction, Matlab Models", 2008.
  9. Rastislav Lukac, Konstantinos N. Plataniotis, "Color image processing: methods and applications", Published by CRC Press, ISBN 084939774X, 9780849397745, 2006.
  10. Turgay Celik, Hasan Demirel, Huseyin Ozkaramanli, Mustafa Uyguroglu, "Fire detection using statistical color model in video sequences", Journal of Visual Communication and Image Representation,Vol. 18, Issue 2, 2007.