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CDoTS: Change detection on time series background for video foreground segmentation

机译:CDoTS:对时间序列背景进行更改检测以进行视频前景分割

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Although many adaptive background subtraction methods have been proposed for image-based foreground detection, dynamic background in the scene, such as an electronic billboard, still causes a serious problem of false alarm. Exclusion of such area from region of interest may prevent the problem, however an issue of security hole on that area becomes another concern. A method of change detection on repetitive time series background is proposed in this paper. Our method extends an adaptive multiresolution background subtraction to allow detection of time series, which is in turn used for foreground extraction on such area. The accuracy of segmentation on static background is barely changed, while that on the area of periodic change is significantly improved.
机译:尽管已经提出了许多自适应背景扣除方法用于基于图像的前景检测,但是场景中的动态背景,例如电子广告牌,仍然会引起严重的误报问题。将此类区域排除在关注区域之外可能会阻止此问题,但是,该区域的安全漏洞成为另一个问题。提出了一种在重复时间序列背景下进行变化检测的方法。我们的方法扩展了自适应多分辨率背景减法以允许检测时间序列,该时间序列又用于此类区域的前景提取。静态背景下的分割精度几乎不变,而周期性变化区域上的分割精度则大大提高。

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