Person re-identification using part-based convolutional baseline
Person re-identification is the process of identifying of a person previously identified. This has become an area of increasingly popular research due to its application in the public security. In comparison to other machine learning that also involve searching for object, person re-identification i...
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2020
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sg-ntu-dr.10356-1397612023-07-07T18:38:08Z Person re-identification using part-based convolutional baseline Lau, Jia Quan Tay, Wee Peng School of Electrical and Electronic Engineering wptay@ntu.edu.sg Engineering::Electrical and electronic engineering Person re-identification is the process of identifying of a person previously identified. This has become an area of increasingly popular research due to its application in the public security. In comparison to other machine learning that also involve searching for object, person re-identification is of higher difficulty due to the various variation that can happened in real-world condition. The variation consists of brightness, image resolutions, the point of view and the obstruction of body parts during capture. With these variations in place, the project’s objective is to create a person re-identification system that can correctly predict the input image (query) from within a pool of data image. This project will focus on the Part-based Convolutional Baseline and refined part pooling. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-21T07:00:59Z 2020-05-21T07:00:59Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139761 en A3249-191 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Lau, Jia Quan Person re-identification using part-based convolutional baseline |
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Person re-identification is the process of identifying of a person previously identified. This has become an area of increasingly popular research due to its application in the public security. In comparison to other machine learning that also involve searching for object, person re-identification is of higher difficulty due to the various variation that can happened in real-world condition. The variation consists of brightness, image resolutions, the point of view and the obstruction of body parts during capture. With these variations in place, the project’s objective is to create a person re-identification system that can correctly predict the input image (query) from within a pool of data image. This project will focus on the Part-based Convolutional Baseline and refined part pooling. |
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Tay, Wee Peng |
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Tay, Wee Peng Lau, Jia Quan |
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Final Year Project |
author |
Lau, Jia Quan |
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Lau, Jia Quan |
title |
Person re-identification using part-based convolutional baseline |
title_short |
Person re-identification using part-based convolutional baseline |
title_full |
Person re-identification using part-based convolutional baseline |
title_fullStr |
Person re-identification using part-based convolutional baseline |
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Person re-identification using part-based convolutional baseline |
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person re-identification using part-based convolutional baseline |
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Nanyang Technological University |
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2020 |
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https://hdl.handle.net/10356/139761 |
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