Small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences
Author
Bağci, A.Murat
Yardımcı, Y.
Çetin, A. Enis
Date
2001-07-08Source 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 PaperItem Usage Stats
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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 decompositionLower 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