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After the elimination of the camera movement using motion compensation, the resulting panoramic image should essentially contain the background and the ghost-like traces of the moving objects. In fact, an initial panoramic background is modeled using region-based mosaicing in order to be sufficiently robust to noise from lighting effects and shadowing by foreground objects. The information of background regions is exploited to make moving objects detection more efficient, and vice-versa. The originality of this work lies essentially in our use of the semantic information provided by the regions while simultaneously identifying novel objects (foreground) and non-novel ones (background). The proposed framework works under difficult conditions such as dynamic background and nominally moving camera. This paper explores a robust region-based general framework for discriminating between background and foreground objects within a complex video sequence. A robust framework for joint background/foreground segmentation of complex video scenes filmed with freely moving camera A robust framework for joint background/foreground segmentation of complex video scenes filmed.Īmri, Slim Barhoumi, Walid Zagrouba, Ezzeddine