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- W1509589980 abstract "Background subtraction is a common method for detecting moving objects from static cameras able to achieve real-time performance. However, it is highly dependent on a good background model particularly to deal with dynamic scenes. In this paper a novel real-time algorithm for creating a robust and multimodal background model is presented. The proposed approach is based on an on-line clustering algorithm to create the model and on a novel conditional update mechanism that allows for obtaining an accurate foreground mask. A quantitative comparison of the algorithm with several state-of-the-art methods on a well-known benchmark dataset is provided demonstrating the effectiveness of the approach." @default.
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- W1509589980 date "2012-09-13" @default.
- W1509589980 modified "2023-10-10" @default.
- W1509589980 title "Independent multimodal background subtraction" @default.
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- W1509589980 doi "https://doi.org/10.1201/b12753-8" @default.
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