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

作　　者：Zeynab IMANI Hadi SOLTANIZADEH 

机构地区：[1]Electrical and Computer Engineering Faculty,Semnan Univercity

出　　处：《Science China(Information Sciences)》2018年第9期106-119,共14页中国科学（信息科学）（英文版）

摘　　要：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 networks.Our 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.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 networks.Our 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 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TU472[自动化与计算机技术—计算机科学与技术]