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Background-foreground tracking for video object segmentation

机译:视频对象分割的背景-前景跟踪

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We present a method to segment objects of interest in video sequences by combining robust background and foreground point tracking with joint color and motion-based segmentation. Our approach is sequential in time, avoiding a global processing of the video, while being simple and generic. This makes the method attractive for online applications, including video editing or augmented reality, as it can be adapted for both automated and interactive work-flows. We present visual and quantitative experiments to compare with existing algorithms, showing promising results.
机译:我们通过将鲁棒背景和前景点跟踪与联合颜色和基于运动的分割组合来介绍一种对视频序列的感兴趣对象的方法。我们的方法是顺序及时,避免了视频的全球处理,同时简单而通用。这使得该方法对在线应用程序具有吸引力,包括视频编辑或增强现实,因为它可以适用于自动和交互式工作流程。我们呈现了视觉和定量实验,以与现有算法进行比较,显示出现有前途的结果。

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