Attire insensitive person re-identification
Person re-identification (re-ID) has emerged as a critical discipline within the realm of computer vision. The goal of person re-ID is to accurately identify and track individuals across multiple video feeds from surveillance cameras. Many traditional person re-ID models focus primarily on cap...
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2024
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sg-ntu-dr.10356-1765882024-05-24T15:49:49Z Attire insensitive person re-identification Loh, Leonard Wei Ting Alex Chichung Kot School of Electrical and Electronic Engineering EACKOT@ntu.edu.sg Engineering Person re-identification (re-ID) has emerged as a critical discipline within the realm of computer vision. The goal of person re-ID is to accurately identify and track individuals across multiple video feeds from surveillance cameras. Many traditional person re-ID models focus primarily on capturing attire features. As a result, most attire-focused re-ID methods have difficulty tracking individuals when they change attire or blend into a crowd of people wearing similar attire. To overcome these issues, more research on person re-ID is focusing on shifting the emphasis away from clothing to more permanent and distinct physical features such as body shape, skin colour and other soft biometrics. This report explores different attire-insensitive person re-ID approaches and addresses the challenges associated with the traditional approaches, particularly in the clothes-changing scenario. Through the consolidation and evaluation of various attire-insensitive methodologies, the project seeks to bridge the existing research gap and improve the accuracy of re-ID algorithms. By investigating techniques to perform re-ID on individuals who have changed clothing, this research contributes to advancing the reliability and effectiveness of person re-identification methods, thereby addressing key concerns in security and public safety. Bachelor's degree 2024-05-18T10:52:20Z 2024-05-18T10:52:20Z 2024 Final Year Project (FYP) Loh, L. W. T. (2024). Attire insensitive person re-identification. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176588 https://hdl.handle.net/10356/176588 en A3082-231 application/pdf Nanyang Technological University |
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Person re-identification (re-ID) has emerged as a critical discipline within the realm of
computer vision. The goal of person re-ID is to accurately identify and track individuals across
multiple video feeds from surveillance cameras. Many traditional person re-ID models focus
primarily on capturing attire features. As a result, most attire-focused re-ID methods have
difficulty tracking individuals when they change attire or blend into a crowd of people wearing
similar attire. To overcome these issues, more research on person re-ID is focusing on shifting
the emphasis away from clothing to more permanent and distinct physical features such as body
shape, skin colour and other soft biometrics. This report explores different attire-insensitive
person re-ID approaches and addresses the challenges associated with the traditional
approaches, particularly in the clothes-changing scenario.
Through the consolidation and evaluation of various attire-insensitive methodologies, the
project seeks to bridge the existing research gap and improve the accuracy of re-ID algorithms.
By investigating techniques to perform re-ID on individuals who have changed clothing, this
research contributes to advancing the reliability and effectiveness of person re-identification
methods, thereby addressing key concerns in security and public safety. |
author2 |
Alex Chichung Kot |
author_facet |
Alex Chichung Kot Loh, Leonard Wei Ting |
format |
Final Year Project |
author |
Loh, Leonard Wei Ting |
author_sort |
Loh, Leonard Wei Ting |
title |
Attire insensitive person re-identification |
title_short |
Attire insensitive person re-identification |
title_full |
Attire insensitive person re-identification |
title_fullStr |
Attire insensitive person re-identification |
title_full_unstemmed |
Attire insensitive person re-identification |
title_sort |
attire insensitive person re-identification |
publisher |
Nanyang Technological University |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/176588 |
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1806059863362502656 |