期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：1
页码：27-34
DOI：10.14257/ijhit.2015.8.1.03
出版社：SERSC
摘要：In a video surveillance network, it is always required to track and recognize people when they move through the environment. This paper presents a novel re-identification method for multiple-people using feature selection with sparsity. By using the multiple- shot approach, each of appearance models is created in this method. The human body is divided into five parts form which the features of color, height, gradient were extracted respectively. Our appearance model is represented by linear regression method. Experimental results show that our appearance model is robust and attain a high precision rate and processing performance.
