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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences

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      Author
      Bağci, A.Murat
      Yardımcı, Y.
      Çetin, A. Enis
      Date
      2001-07-08
      Source Title
      International Symposium on Optical Science and Technology, 2001 - Signal and Data Processing of Small Targets
      Print ISSN
      0277-786X
      Pages
      25 - 33
      Language
      English
      Type
      Conference Paper
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      Abstract
      In this paper, a small moving object method detection method in video sequences is described. In the first step, the camera motion is eliminated using motion compensation. An adaptive subband decomposition structure is then used to analyze the motion compensated image. In the highband subimages moving objects appear as outliers and they are detected using a statistical detection test based on lower order statistics. It turns out that in general, the distribution of the residual error image pixels is almost Gaussian. On the other hand, the distribution of the pixels in the residual image deviates from Gaussianity in the existence of outliers. By detecting the regions containing outliers the boundaries of the moving objects are estimated. Simulation examples are presented.
      Keywords
      Adaptive subband decomposition
      Lower order statistics
      Moving object detection
      Wavelet transform
      Computational methods
      Computer simulation
      Motion compensation
      Motion picture cameras
      Statistical methods
      Wavelet transforms
      Adaptive subband decompositions
      Video sequences
      Object recognition
      Permalink
      http://hdl.handle.net/11693/27595
      Published Version (Please cite this version)
      http://dx.doi.org/10.1117/12.492744
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      • Department of Electrical and Electronics Engineering 3524
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