Cross perspective person re-identification (drone and ground cameras)
Person Re-Identification(Re-ID) is a task to identify the same individual shown up in different camera video streams. It is getting more useful as the development of guard surveillance and camera technology. In the meanwhile, UAVs are also getting more and more frequently used, so combining Re-ID...
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2023
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sg-ntu-dr.10356-1687082023-07-04T16:37:43Z Cross perspective person re-identification (drone and ground cameras) Zhou,Wenbo Alex Chichung Kot School of Electrical and Electronic Engineering Rapid-Rich Object Search (ROSE) Lab EACKOT@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Person Re-Identification(Re-ID) is a task to identify the same individual shown up in different camera video streams. It is getting more useful as the development of guard surveillance and camera technology. In the meanwhile, UAVs are also getting more and more frequently used, so combining Re-ID and Unmanned Aerial Vehicles (UAV) is a new area. Normally,the difficulties of person Re-ID is occlusion and background difference, low resolution, illumination changes, and viewpoint variations. In this project, different cameras at different perspectives are used to collect our own dataset(NTU-Drone). We use our ResNet baseline model to train Market- 1501, MSMT17-V2, DukeMTMC-ReID dataset, PRAI-1518, P-DRSTRE, and UAVHuman dataset and then test on UAV-Human, P-Destre, PRAI-1518 datasets, and NTU-Drone datasets. We are able to achieve the state of the art or at least idea accuracy. We classified our NTU-Drone dataset by the camera height to find the suitable big datasets to train before the test. Keywords: Person Re-Identification, UAV, Computer vision. Master of Science (Computer Control and Automation) 2023-06-16T02:27:29Z 2023-06-16T02:27:29Z 2023 Thesis-Master by Coursework Zhou, W. (2023). Cross perspective person re-identification (drone and ground cameras). Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/168708 https://hdl.handle.net/10356/168708 en title ID:ISM-DISS-03209 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Zhou,Wenbo Cross perspective person re-identification (drone and ground cameras) |
description |
Person Re-Identification(Re-ID) is a task to identify the same individual shown
up in different camera video streams. It is getting more useful as the development
of guard surveillance and camera technology. In the meanwhile, UAVs
are also getting more and more frequently used, so combining Re-ID and Unmanned
Aerial Vehicles (UAV) is a new area. Normally,the difficulties of person
Re-ID is occlusion and background difference, low resolution, illumination
changes, and viewpoint variations.
In this project, different cameras at different perspectives are used to collect our
own dataset(NTU-Drone). We use our ResNet baseline model to train Market-
1501, MSMT17-V2, DukeMTMC-ReID dataset, PRAI-1518, P-DRSTRE, and UAVHuman
dataset and then test on UAV-Human, P-Destre, PRAI-1518 datasets, and
NTU-Drone datasets. We are able to achieve the state of the art or at least idea
accuracy. We classified our NTU-Drone dataset by the camera height to find the
suitable big datasets to train before the test.
Keywords: Person Re-Identification, UAV, Computer vision. |
author2 |
Alex Chichung Kot |
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Alex Chichung Kot Zhou,Wenbo |
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Thesis-Master by Coursework |
author |
Zhou,Wenbo |
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Zhou,Wenbo |
title |
Cross perspective person re-identification (drone and ground cameras) |
title_short |
Cross perspective person re-identification (drone and ground cameras) |
title_full |
Cross perspective person re-identification (drone and ground cameras) |
title_fullStr |
Cross perspective person re-identification (drone and ground cameras) |
title_full_unstemmed |
Cross perspective person re-identification (drone and ground cameras) |
title_sort |
cross perspective person re-identification (drone and ground cameras) |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/168708 |
_version_ |
1772826495468699648 |