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Tensor compressive sensing (TCS) is a multidimensional framework of compressive sensing (CS), and it is advantageous in terms of reducing the amount of storage, easing hardware implementations, and preserving multidimensional structures of signals in comparison to a conventional CS system. In a TCS system, instead of using a random sensing matrix and a predefined dictionary, the average-case performance...
The task of visual tracking is to deal with dynamic image streams that change over time. For color object tracking, although a color object is a 3-order tensor in essence, little attention has been focused on this attribute. In this paper, we propose a novel Incremental Multiple Principal Component Analysis (IMPCA) method for online learning dynamic tensor streams. When newly added tensor set arrives,...
In this paper, a statistical texture modeling method is proposed for medical volumes. As the shapes of the human organ are very different from one case to another, 3D volume morphing is applied to normalize all the volume datasets to a same shape for removing shape variations. In order to deal with the problems of high-dimension and small number of medial samples, we propose an effective image compression...
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