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Histogram of the node strength and histogram of the edge weight: two new features for RGB-D person re-identification

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Science China(Information Sciences) 2018年第9期61卷 112-125页

作者： Zeynab IMANI hadi soltanizadeh Electrical and Computer Engineering Faculty Semnan Univercity

Person re-identification is a classical task for any multi-camera surveillance system. Most of the existing researches on re-identification are based on features extracted from RGB images. However,there are many deficiencies in RGB image processing, some of which are requiring a lot of illumination and high computation. In this paper, novel features are proposed for RGB-D person re-identification. First, the complex network approach in texture recognition is modified and its threshold function is changed for using in depth images extracted by RGB-D sensors. Then, two novel measurements named the histogram of the edge weight(HEW) and the histogram of the node strength(HNS) are introduced on complex *** features fit both single-shot and multi-shot person re-identification. In the single-shot case, the HNS is extracted from only one frame while for the multi-shot case it is extracted from both one frame and multi-frames. These proposed measurements are called histogram of the spatial node strength(HSNS)and histogram of the temporal node strength(HTNS) respectively. Subsequently, these measurements are combined with skeleton features using score-level fusion. The method is evaluated using two benchmark databases and the results show that ours outperforms some state-of-the-art methods.

关键词： complex network edge weight graph node strength person re-identification skeleton features

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