@Article{jnm.2020.09823,
AUTHOR = {Tong Jiang},
TITLE = {A Review of Person Re-Identification},
JOURNAL = {Journal of New Media},
VOLUME = {2},
YEAR = {2020},
NUMBER = {2},
PAGES = {45--60},
URL = {http://www.techscience.com/JNM/v2n2/39934},
ISSN = {2579-0129},
ABSTRACT = {Recently, person Re-identification (person Re-id) has attracted more and 
more attention, which has become a research focus of computer vision community. 
Person Re-id is used to ascertain whether the target pedestrians captured by cameras 
in different positions at different moments are the same person or not. However, due 
to the influence of various complex factors, person Re-id still has a lot of holes to be 
filled. In this paper, we first review the research process of person Re-id, and then, 
two kinds of mainstream methods for person Re-id are introduced respectively, 
according to the different types of training data they used. After that, we introduce 
some specific methods for different kinds of person Re-id, including handcrafted 
feature descriptor and metrics learning based methods as well as neural network 
based methods. Then, some commonly used datasets and their performance 
evaluation criteria are introduced. Finally, we compare these methods in order to 
display their advantages and disadvantages. Last but not list, depending on the 
current research status and development tendency, we make a prospect for person 
Re-id research.},
DOI = {10.32604/jnm.2020.09823}
}