Browsing by Author "Zaibi, Rabi"
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Item Open Access Change detection in digital video signals(1999) Zaibi, RabiWe present a method for scene change detection based on projections onto the vertical, horizontal and diagonal axes. At first, vertical projection of each two consecutive interframe differences are calculated. Then based on the distance measure between them, together with proportionality and sign tests, fade in/out, dissolve, wipe and cut can be classified. We also propose a method for small moving object detection in video sequences based on adaptive prediction and higher order statistical tests. We first eliminate camera movement using subpixel accurate motion estimation. Then adaptive prediction is applied on the image obtained from motion compensation and an error image is obtained. Higher order statistical test is then applied on the residual image to detect small moving objects whose size may consist of only a few pixels.Item Open Access Small moving object detection in video sequences(IEEE, 2000-06) Zaibi, Rabi; Çetin, A. Enis; Yardımcı, Y.In this paper, we propose a method for detection of small moving objects in video. We first eliminate the camera motion using motion compensation. We then use an adaptive predictor to estimate the current pixel using neighboring pixels in the motion compensated image and, in this way, obtain a residual error image. Small moving objects appear as outliers in the residual image and 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.Item Open Access Small moving object detection using adaptive subband decomposition in video sequences(SPIE, 2000) Zaibi, Rabi; Çetin, A. Enis; Yardımcı, Y. C.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.