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A survey of person re-identification based on deep learning

open access: yes工程科学学报, 2022
Person re-identification is an important part of multi-target tracking across cameras; its aim is to identify the same person across different cameras. Given a query image, the purpose of person re-identification is to find the best match for the query ...
Qing LI   +4 more
doaj   +1 more source

Multi Scale-Adaptive Super-Resolution Person Re-Identification Using GAN

open access: yesIEEE Access, 2020
In real-world surveillance systems, the person images captured by the camera network consists of various low-resolution (LR) images. It creates a resolution mismatching problem when compared against high-resolution images of a targeted person.
Muhammad Adil   +4 more
doaj   +1 more source

Cross‐modality person re‐identification using hybrid mutual learning

open access: yesIET Computer Vision, 2023
Cross‐modality person re‐identification (Re‐ID) aims to retrieve a query identity from red, green, blue (RGB) images or infrared (IR) images. Many approaches have been proposed to reduce the distribution gap between RGB modality and IR modality. However,
Zhong Zhang   +5 more
doaj   +1 more source

Deep-Facial Feature-Based Person Re-identification for Authentication in Surveillance Applications [PDF]

open access: yesITM Web of Conferences, 2021
Nowadays, a large network of cameras is predominantly used in public places which provide enormous video data. These data are monitored manually and may be utilized only when the need arises to ascertain the facts.
Borse Pranjal   +3 more
doaj   +1 more source

Improving Person Re-Identification with Temporal Constraints [PDF]

open access: yes2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022
In this paper we introduce an image-based person re-identification dataset collected across five non-overlapping camera views in the large and busy airport in Dublin, Ireland. Unlike all publicly available image-based datasets, our dataset contains timestamp information in addition to frame number, and camera and person IDs.
Dietlmeier, Julia   +4 more
openaire   +3 more sources

Stochastic attentions and context learning for person re-identification [PDF]

open access: yesPeerJ Computer Science, 2021
The discriminative parts of people’s appearance play a significant role in their re-identification across non overlapping camera views. However, just focusing on the discriminative or attention regions without catering the contextual information does not
Nazia Perwaiz   +2 more
doaj   +2 more sources

Person Re-Identification

open access: yes, 2022
Person Re-Identification (Re-ID) is an important problem in computer vision-based surveillance applications, in which one aims to identify a person across different surveillance photographs taken from different cameras having varying orientations and field of views.
Chasmai, Mustafa Ebrahim   +1 more
openaire   +2 more sources

Person Re-Identification by Saliency Learning [PDF]

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
Human eyes can recognize person identities based on small salient regions, i.e. human saliency is distinctive and reliable in pedestrian matching across disjoint camera views. However, such valuable information is often hidden when computing similarities of pedestrian images with existing approaches.
Rui Zhao, Wanli Oyang, Xiaogang Wang
openaire   +3 more sources

Denseformer: A dense transformer framework for person re‐identification

open access: yesIET Computer Vision, 2023
Transformer has shown its effectiveness and advantage in many computer vision tasks, for example, image classification and object re‐identification (ReID).
Haoyan Ma   +3 more
doaj   +1 more source

Bike-Person Re-Identification: A Benchmark and a Comprehensive Evaluation

open access: yesIEEE Access, 2018
Existing person re-identification (re-id) datasets only consist of pedestrian images, which are far more behind what the real surveillance system holds.
Yuan Yuan, Jian'an Zhang, Qi Wang
doaj   +1 more source

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