@Article{jnm.2020.014278,
AUTHOR = {Junchuan Yang},
TITLE = {Review of Image-Based Person Re-Identification in Deep Learning},
JOURNAL = {Journal of New Media},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {137--148},
URL = {http://www.techscience.com/JNM/v2n4/40918},
ISSN = {2579-0129},
ABSTRACT = {Person Re-identification (re-ID) is a hot research topic in the field of 
computer vision now, which can be regarded as a sub-problem of image retrieval. 
The goal of person re-ID is to give a monitoring pedestrian image and retrieve 
other images of the pedestrian across the device. At present, person re-ID is mainly 
divided into two categories. One is the traditional methods, which relies heavily
on manual features. The other is to use deep learning technology to solve. Because 
traditional methods mainly rely on manual feature, they cannot adapt well to a 
complex environment with a large amount of data. In recent years, with the 
development of deep learning technology, a large number of person re-ID methods 
based on deep learning have been proposed, which greatly improves the accuracy 
of person re-ID.},
DOI = {10.32604/jnm.2020.014278}
}