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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| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2024
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/176588 |
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| 總結: | 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. |
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