Small moving object detection using adaptive subband decomposition in video sequences


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 'low-high' and 'high-low' subimages small moving objects appear as outliers and they are detected using a statistical Gaussianity detection test based on higher 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. Simulation examples are presented.

Date of Conference: 24-28 April 2000
Conference Name: SPIE Aerosense, 2000
Wavelet transforms, Adaptive subband decomposition, Higher order statistics, Least mean square, Moving object detection, Statistical Gaussianity detection test, Video sequences, Object recognition