A Review of Research on Person Re-identification in Surveillance Video  

作　　者：Yunzuo ZHANG Weiqi LIAN 

机构地区：[1]School of Information science and Technology,Shijiazhuang Tiedao University,Shijiazhuang,Hebei,050043,China

出　　处：《Mechanical Engineering Science》2023年第2期1-7,共7页机械工程（英文）

摘　　要：Person re-identification has emerged as a hotspot for computer vision research due to the growing demands of social public safety requirements and the quick development of intelligent surveillance networks.Person re-identification(Re-ID)in video surveillance system can track and identify suspicious people,track and statistically analyze persons.The purpose of person re-identification is to recognize the same person in different cameras.Deep learning-based person re-identification research has produced numerous remarkable outcomes as a result of deep learning's growing popularity.The purpose of this paperis to help researchers better understand where person re-identification research is at the moment and where it is headed.Firstly,this paper arranges the widely used datasets and assessment criteria in person re-identification and reviews the pertinent research on deep learning-based person re-identification techniques conducted in the last several years.Then,the commonly used method techniques are also discussed from four aspects:appearance features,metric learning,local features,and adversarial learning.Finally,future research directions in the field of person re-identification are outlooked.

关 键 词：Person re-identification Deep learning Metric learning Local features Adversarial learning 

分 类 号：H31[语言文字—英语]