Part-Based And Multispace Random Mapping For Face Recognition

In this thesis, we studied several part-based approaches for face recognition. Our objective is to reduce the dimensionality of the raw image while retaining as many salient features as possible. Non-Negative Matrix Factorization (NMF) is recently a proposed method to obtain a part-based linear repr...

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Bibliographic Details
Main Author: Neo, Han Foon
Format: Thesis
Published: 2005
Subjects:
Online Access:http://shdl.mmu.edu.my/883/
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author Neo, Han Foon
author_facet Neo, Han Foon
author_sort Neo, Han Foon
building MMU Institutional Repository
collection Online Access
description In this thesis, we studied several part-based approaches for face recognition. Our objective is to reduce the dimensionality of the raw image while retaining as many salient features as possible. Non-Negative Matrix Factorization (NMF) is recently a proposed method to obtain a part-based linear representation of facial image. However, the bases learned by NMF do not display perfectly the local characteristics as there are still some non-zero weight values in the features. These values appear as noise and contribute to the degradation of the recognition performance. In this thesis, we have proposed a novel part-based feature extractor based on NMF.
first_indexed 2025-11-14T17:59:44Z
format Thesis
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institution Multimedia University
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last_indexed 2025-11-14T17:59:44Z
publishDate 2005
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spelling mmu-8832021-09-21T08:04:16Z http://shdl.mmu.edu.my/883/ Part-Based And Multispace Random Mapping For Face Recognition Neo, Han Foon TA Engineering (General). Civil engineering (General) In this thesis, we studied several part-based approaches for face recognition. Our objective is to reduce the dimensionality of the raw image while retaining as many salient features as possible. Non-Negative Matrix Factorization (NMF) is recently a proposed method to obtain a part-based linear representation of facial image. However, the bases learned by NMF do not display perfectly the local characteristics as there are still some non-zero weight values in the features. These values appear as noise and contribute to the degradation of the recognition performance. In this thesis, we have proposed a novel part-based feature extractor based on NMF. 2005-09 Thesis NonPeerReviewed Neo, Han Foon (2005) Part-Based And Multispace Random Mapping For Face Recognition. Masters thesis, Multimedia University. https://proxyvlib.mmu.edu.my/login?url=http://library.mmu.edu.my/library2/diglib/mmuetd/
spellingShingle TA Engineering (General). Civil engineering (General)
Neo, Han Foon
Part-Based And Multispace Random Mapping For Face Recognition
title Part-Based And Multispace Random Mapping For Face Recognition
title_full Part-Based And Multispace Random Mapping For Face Recognition
title_fullStr Part-Based And Multispace Random Mapping For Face Recognition
title_full_unstemmed Part-Based And Multispace Random Mapping For Face Recognition
title_short Part-Based And Multispace Random Mapping For Face Recognition
title_sort part-based and multispace random mapping for face recognition
topic TA Engineering (General). Civil engineering (General)
url http://shdl.mmu.edu.my/883/
http://shdl.mmu.edu.my/883/