Facial recognition with eigenfaces
This final year report conducts a study of a few different facial recognition experiments using PyCharm and OpenCV platforms in the first half. The programming language used is Python. For the second half of the report, it is mainly focused on Eigenfaces implementation using Google Collaboration pl...
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Nanyang Technological University
2020
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sg-ntu-dr.10356-1449672020-12-07T04:03:21Z Facial recognition with eigenfaces Foo, Kai Xiang Qian Kemao School of Computer Science and Engineering MKMQian@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision This final year report conducts a study of a few different facial recognition experiments using PyCharm and OpenCV platforms in the first half. The programming language used is Python. For the second half of the report, it is mainly focused on Eigenfaces implementation using Google Collaboration platform and the execution of recognising human faces using the Principle Component Analysis (PCA). The report will also be covering on the procedures of Eigenfaces approach with step-by-step illustrations in detail, and to evaluate the results of any given training-based face images only from Yale Face Database. Bachelor of Engineering (Computer Engineering) 2020-12-07T04:03:21Z 2020-12-07T04:03:21Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/144967 en SCSE19-0885 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Foo, Kai Xiang Facial recognition with eigenfaces |
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This final year report conducts a study of a few different facial recognition experiments using PyCharm and OpenCV platforms in the first half. The programming language used is Python. For the second half of the report, it is mainly focused on Eigenfaces implementation using Google Collaboration platform and the execution of recognising human faces using the Principle Component Analysis (PCA). The report will also be covering on the procedures of Eigenfaces approach with step-by-step illustrations in detail, and to evaluate the results of any given training-based face images only from Yale Face Database. |
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Qian Kemao |
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Qian Kemao Foo, Kai Xiang |
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Final Year Project |
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Foo, Kai Xiang |
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Foo, Kai Xiang |
title |
Facial recognition with eigenfaces |
title_short |
Facial recognition with eigenfaces |
title_full |
Facial recognition with eigenfaces |
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Facial recognition with eigenfaces |
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Facial recognition with eigenfaces |
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facial recognition with eigenfaces |
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Nanyang Technological University |
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2020 |
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https://hdl.handle.net/10356/144967 |
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