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Extracting a background image by a multi-modal scene background model

机译:通过多模式场景背景模型提取背景图像

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In scene analysis, the availability of an initial background model that describes the scene without foreground objects is at the basis of many computer vision applications. Multi-modal models of the scene background are frequently adopted in the applications, where each mode tries to keep track of the multiple background modes observed along the sequence. In this work we specifically address the problem of extracting a single background image by a multi-modal model of the scene background, in order to compare it against a given ground truth image of the background. Experimental results are provided on the SBMnet dataset, based on an existing multi-model background model and different extraction criteria, and general conclusions are drawn.
机译:在场景分析中,描述没有前景对象的场景的初始背景模型的可用性是许多计算机视觉应用程序的基础。在应用程序中经常采用场景背景的多模式模型,其中每种模式都试图跟踪沿序列观察到的多个背景模式。在这项工作中,我们专门解决了通过场景背景的多模式模型提取单个背景图像的问题,以便将其与背景的给定地面真实图像进行比较。基于现有的多模型背景模型和不同的提取标准,在SBMnet数据集上提供了实验结果,并得出了一般结论。

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