M. S. Houari Sabirin

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This paper presents a spatio-temporal graph-based method of detecting and tracking moving objects by treating the encoded blocks with non-zero motion vectors and/or non-zero residues as potential parts of objects in H.264/AVC bitstreams. A spatio-temporal graph is constructed by first clustering the encoded blocks of potential object parts into block(More)
In this paper, we show that we can apply probabilistic spatiotemporal macroblock filtering (PSMF) and partial decoding processes to effectively detect and track multiple objects in real time in H.264|AVC bitstreams with stationary background. Our contribution is that our method cannot only show fast processing time but also handle multiple moving objects(More)
In this paper, we propose a new method of automatic silhouette extraction of multiple moving objects with high accuracy for free viewpoint stadium sports video synthesis. The proposed method is basically composed of three parts, including a global extraction based on temporal background subtraction, a classification step based on the constraints of(More)
In this paper, we report on an optimized union-find (UF) algorithm that can label the connected components on a 2D image efficiently by employing GPU architecture. The proposed method comprises three phases: UF-based local merge, boundary analysis, and link. The coarse labeling in local merge, which makes computation efficient because the length of the(More)
In this paper we present a novel method of detecting and tracking moving objects in H.264/SVC bitstreams for video surveillance applications. Efficient detection and reliable tracking of real moving objects are first performed in the spatial base layer of H.264/SVC based on a spatio-temporal graph which is constructed from the block partitions with non-zero(More)