Small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences

A. Murat Bagci; Yasemin C. Yardimci; Enis A. Cetin

doi:10.1117/12.492744

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26 November 2001 Small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences

A. Murat Bagci, Yasemin C. Yardimci, Enis A. Cetin

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Proceedings Volume 4473, Signal and Data Processing of Small Targets 2001; (2001) https://doi.org/10.1117/12.492744
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

Abstract

In this paper, a small moving object method detection method in video sequence 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.

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A. Murat Bagci, Yasemin C. Yardimci, and Enis A. Cetin "Small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences", Proc. SPIE 4473, Signal and Data Processing of Small Targets 2001, (26 November 2001); https://doi.org/10.1117/12.492744

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