Open Access

REVIEW

Review of Image-Based Person Re-Identification in Deep Learning

by Junchuan Yang

School of Computer & Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

* Corresponding Author: Junchuan Yang. Email:

Journal of New Media 2020, 2(4), 137-148. https://doi.org/10.32604/jnm.2020.014278

Received 10 September 2020; Accepted 11 September 2020; Issue published 23 December 2020

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.

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