Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network
Person re-identification is the technique of identifying the same person in different camera shots, known as ReID for short. Most existing models focus on single-modality person re-identification involving only visible images. However, the visible modality is not suitable for low-light environments...
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MDPI AG
2023-07-01
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Online Access: | https://www.mdpi.com/2079-9292/12/14/3193 |
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author | Jianfeng Song Jin Yang Chenyang Zhang Kun Xie |
author_facet | Jianfeng Song Jin Yang Chenyang Zhang Kun Xie |
author_sort | Jianfeng Song |
collection | DOAJ |
description | Person re-identification is the technique of identifying the same person in different camera shots, known as ReID for short. Most existing models focus on single-modality person re-identification involving only visible images. However, the visible modality is not suitable for low-light environments or at night, when crime is frequent. In contrast, infrared images can reflect the nighttime environment, and most surveillance systems are equipped with dual-mode cameras that can automatically switch between visible and infrared modalities based on light conditions. In contrast to visible-light cameras, infrared (IR) cameras can still capture enough information from the scene in those dark environments. Therefore, the problem of visible-infrared cross-modality person re-identification (VI-ReID) is proposed. To improve the identification rate of cross-modality person re-identification, a cross-modality person re-identification method based on a two-branch network is proposed. Firstly, we use infrared image colorization technology to convert infrared images into color images to reduce the differences between modalities and propose a visible-infrared cross-modality person re-identification algorithm based on Two-Branch Network with Double Constraints (VI-TBNDC), which consists of two main components: a two-branch network for feature extraction and a double-constrained identity loss for feature learning. The two-branch network extracts the features of both data sets separately, and the double-constrained identity loss ensures that the learned feature representations are discriminative enough to distinguish different people from two different patterns. The effectiveness of the proposed method is verified by extensive experimental analysis, and the method achieves good recognition accuracy on the visible-infrared image person re-identification standard dataset SYSU-MM01. |
first_indexed | 2024-03-11T01:08:02Z |
format | Article |
id | doaj.art-bd46b0f081d645cbb2390ee32bdb43cb |
institution | Directory Open Access Journal |
issn | 2079-9292 |
language | English |
last_indexed | 2024-03-11T01:08:02Z |
publishDate | 2023-07-01 |
publisher | MDPI AG |
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series | Electronics |
spelling | doaj.art-bd46b0f081d645cbb2390ee32bdb43cb2023-11-18T19:07:21ZengMDPI AGElectronics2079-92922023-07-011214319310.3390/electronics12143193Cross-Modality Person Re-Identification Algorithm Based on Two-Branch NetworkJianfeng Song0Jin Yang1Chenyang Zhang2Kun Xie3School of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaSchool of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaSchool of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaSchool of Computer Science and Technology, Xidian University, Xi’an 710071, ChinaPerson re-identification is the technique of identifying the same person in different camera shots, known as ReID for short. Most existing models focus on single-modality person re-identification involving only visible images. However, the visible modality is not suitable for low-light environments or at night, when crime is frequent. In contrast, infrared images can reflect the nighttime environment, and most surveillance systems are equipped with dual-mode cameras that can automatically switch between visible and infrared modalities based on light conditions. In contrast to visible-light cameras, infrared (IR) cameras can still capture enough information from the scene in those dark environments. Therefore, the problem of visible-infrared cross-modality person re-identification (VI-ReID) is proposed. To improve the identification rate of cross-modality person re-identification, a cross-modality person re-identification method based on a two-branch network is proposed. Firstly, we use infrared image colorization technology to convert infrared images into color images to reduce the differences between modalities and propose a visible-infrared cross-modality person re-identification algorithm based on Two-Branch Network with Double Constraints (VI-TBNDC), which consists of two main components: a two-branch network for feature extraction and a double-constrained identity loss for feature learning. The two-branch network extracts the features of both data sets separately, and the double-constrained identity loss ensures that the learned feature representations are discriminative enough to distinguish different people from two different patterns. The effectiveness of the proposed method is verified by extensive experimental analysis, and the method achieves good recognition accuracy on the visible-infrared image person re-identification standard dataset SYSU-MM01.https://www.mdpi.com/2079-9292/12/14/3193person re-identificationcross-modalitymodal transformationtwo-branch neural network |
spellingShingle | Jianfeng Song Jin Yang Chenyang Zhang Kun Xie Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network Electronics person re-identification cross-modality modal transformation two-branch neural network |
title | Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network |
title_full | Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network |
title_fullStr | Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network |
title_full_unstemmed | Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network |
title_short | Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network |
title_sort | cross modality person re identification algorithm based on two branch network |
topic | person re-identification cross-modality modal transformation two-branch neural network |
url | https://www.mdpi.com/2079-9292/12/14/3193 |
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