Face recognition with accessories using Eigenfaces
This study uses a dataset of unoccluded faces for training to examine the effectiveness of using an eigenface approach to identify faces covered by accessories, particularly sunglasses. The robustness of the eigenface method against partial face occlusion is assessed using principal component analys...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1769492024-05-24T15:44:16Z Face recognition with accessories using Eigenfaces Toh, Safarudin Wilyam Anamitra Makur School of Electrical and Electronic Engineering EAMakur@ntu.edu.sg Engineering Eigenfaces This study uses a dataset of unoccluded faces for training to examine the effectiveness of using an eigenface approach to identify faces covered by accessories, particularly sunglasses. The robustness of the eigenface method against partial face occlusion is assessed using principal component analysis, a method often employed in the field of computer vision to perform successful human face detection. This project intends to show that the suggested face recognition system can correctly identify a person regardless of the presence of accessories, for people who are part of the training set. In contrast, it should be able to classify faces that are absent from the training set as unauthorized with reasonable accuracy. Bachelor's degree 2024-05-23T07:53:48Z 2024-05-23T07:53:48Z 2024 Final Year Project (FYP) Toh, S. W. (2024). Face recognition with accessories using Eigenfaces. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176949 https://hdl.handle.net/10356/176949 en A3008-231 application/pdf Nanyang Technological University |
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Engineering Eigenfaces Toh, Safarudin Wilyam Face recognition with accessories using Eigenfaces |
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This study uses a dataset of unoccluded faces for training to examine the effectiveness of using an eigenface approach to identify faces covered by accessories, particularly sunglasses. The robustness of the eigenface method against partial face occlusion is assessed using principal component analysis, a method often employed in the field of computer vision to perform successful human face detection.
This project intends to show that the suggested face recognition system can correctly identify a person regardless of the presence of accessories, for people who are part of the training set. In contrast, it should be able to classify faces that are absent from the training set as unauthorized with reasonable accuracy. |
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Anamitra Makur |
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Anamitra Makur Toh, Safarudin Wilyam |
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Final Year Project |
author |
Toh, Safarudin Wilyam |
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Toh, Safarudin Wilyam |
title |
Face recognition with accessories using Eigenfaces |
title_short |
Face recognition with accessories using Eigenfaces |
title_full |
Face recognition with accessories using Eigenfaces |
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Face recognition with accessories using Eigenfaces |
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Face recognition with accessories using Eigenfaces |
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face recognition with accessories using eigenfaces |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/176949 |
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