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- W2135304920 abstract "The extraction of relevant objects (foreground) from a background is an important first step in many applications. We propose a technique that tackles this problem using a cascade of change detection tests, including noise-induced, illumination variation and structural changes. An objective comparison of pixel-wise modellingmethods is first presented. Given its best relation performance/complexity, the mixture of Gaussians was chosen to be used in the proposed method to detect structural changes. Experimental results show that the cascade technique consistently outperforms the commonly used mixture of Gaussians, without additional post-processing and without the expense of processing overheads." @default.
- W2135304920 created "2016-06-24" @default.
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- W2135304920 date "2007-02-01" @default.
- W2135304920 modified "2023-10-16" @default.
- W2135304920 title "Cascaded change detection for foreground segmentation" @default.
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- W2135304920 doi "https://doi.org/10.1109/wmvc.2007.11" @default.
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