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Practical ReProCS for separating sparse and low-dimensional signal sequences from their sum #x2014; Part 1

机译:实用的ReProCS,用于将稀疏和低维信号序列从其和中分离出来-第1部分

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This paper designs and evaluates a practical algorithm, called Prac-ReProCS, for recovering a time sequence of sparse vectors St and a time sequence of dense vectors Lt from their sum, Mt := St + Lt, when any subsequence of the Lt's lies in a slowly changing low-dimensional subspace. A key application where this problem occurs is in video layering where the goal is to separate a video sequence into a slowly changing background sequence and a sparse foreground sequence that consists of one or more moving regions/objects. Prac-ReProCS is the practical analog of its theoretical counterpart that was studied in our recent work.
机译:本文设计并评估了一种实用算法,称为Prac-ReProCS,用于在Lt的任何子序列位于以下位置时从其和Mt:= St + Lt中恢复稀疏向量St的时间序列和稠密向量Lt的时间序列。缓慢变化的低维子空间。发生此问题的关键应用是视频分层,其目标是将视频序列分为缓慢变化的背景序列和由一个或多个运动区域/对象组成的稀疏前景序列。 Prac-ReProCS是其理论对应物的实践类似物,我们在最近的工作中对其进行了研究。

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