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• W1570873695 abstract "In this paper we give a new model for foreground-back-ground-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly background like colors and shadows are observable on the image. It does not need any a priori information about the shapes of the objects, it assumes only they are not point-wise. The method exploits temporal statistics to characterize the background and shadow, and spatial statistics for the foreground. A Markov Random Field model is used to enhance the accuracy of the separation. We validated our method on outdoor and indoor video sequences captured by the surveillance system of the university campus, and we also tested it on well-known benchmark videos." @default.
• W1570873695 created "2016-06-24" @default.
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• W1570873695 date "2006-01-01" @default.
• W1570873695 modified "2023-10-16" @default.
• W1570873695 title "Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes" @default.
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• W1570873695 doi "https://doi.org/10.1007/11612032_90" @default.
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