A Survey on Deep Learning Based Person Re-identification

被引：0
|
作者：
Luo H. [1 ]
Jiang W. [1 ]
Fan X. [1 ]
Zhang S.-P. [1 ]
机构：
[1] Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2019年 / 45卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Computer vision; Convolutional neural networks; Deep learning; Person re-identification;
D O I：
10.16383/j.aas.c180154
中图分类号：
学科分类号：
摘要：
Person re-identification (ReID) is a popular research topic in computer vision. It aims to retrieve the given pedestrian image across the device, which can be regarded as a sub-problem of image retrieval. The traditional methods rely on hand-crafted features and can not adapt to the complicated environment with a large number of data. In recent years, with the development of deep learning, a large number of ReID methods based on deep learning have been proposed. This paper briefly introduces the definition of the problem and the limitations of the traditional methods, and then lists some popular databases suitable for deep learning. Moreover, we summarize some typical deep learning based methods in detail, and compare the performance of some algorithms on Market1501. Finally, we make a prospect for the future research direction of person ReID. Copyright © 2019 Acta Automatica Sinica. All rights reserved.
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收藏
页码：2032 / 2049
页数：17
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