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

Date
2001-07-08
Advisor
Instructor
Source Title
International Symposium on Optical Science and Technology, 2001 - Signal and Data Processing of Small Targets
Print ISSN
0277-786X
Electronic ISSN
Publisher
Volume
Issue
Pages
25 - 33
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
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.

Course
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Book Title
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
Citation
Published Version (Please cite this version)