Open AccessSurvey on person re‐identification based on deep learning
Author(s) -
Wang Kejun,
Wang Haolin,
Liu Meichen,
Xing Xianglei,
Han Tian
Publication year - 2018
Publication title -
caai transactions on intelligence technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 15
ISSN - 2468-2322
DOI - 10.1049/trit.2018.1001
Subject(s) - deep learning , artificial intelligence , field (mathematics) , identification (biology) , computer science , first person , focus (optics) , data science , machine learning , psychology , mathematics , botany , physics , psychoanalysis , pure mathematics , optics , biology
Person re‐identification (Re‐ID) is a fundamental subject in the field of the computer vision technologies. The traditional methods of person Re‐ID have difficulty in solving the problems of person illumination, occlusion and attitude change under complex background. Meanwhile, the introduction of deep learning opens a new way of person Re‐ID research and becomes a hot spot in this field. This study reviews the traditional methods of person Re‐ID, then the authors focus on the related papers about different person Re‐ID frameworks on the basis of deep learning, and discusses their advantages and disadvantages. Finally, they propose the direction of further research, especially the prospect of person Re‐ID methods based on deep learning.