Neighbourhood discriminant embedding in face recognition

Neighborhood Preserving Embedding (NPE) is a linear approximate of Locally Linear Embedding with local geometry preserving property. An efficient face recognition method requires a mapping to separate within-class structure from between-class structure. But, NPE is not in the case since it is unsupe...

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Main Authors: Pang, Ying Han, Teoh, Andrew Ben Jin, Wong, Eng Kiong
Format: Article
Language:English
Published: The Institute of Electronics, Information and Communication Engineers 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/1944/
http://shdl.mmu.edu.my/1944/1/Neighbourhood%20discriminant%20embedding%20in%20face%20recognition.pdf
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author Pang, Ying Han
Teoh, Andrew Ben Jin
Wong, Eng Kiong
author_facet Pang, Ying Han
Teoh, Andrew Ben Jin
Wong, Eng Kiong
author_sort Pang, Ying Han
building MMU Institutional Repository
collection Online Access
description Neighborhood Preserving Embedding (NPE) is a linear approximate of Locally Linear Embedding with local geometry preserving property. An efficient face recognition method requires a mapping to separate within-class structure from between-class structure. But, NPE is not in the case since it is unsupervised. Hence, we improved NPE-utilizing the neighbor and class relations of face data. The proposed technique, Neighborhood Discriminant Embedding (NDE), takes into account the local neighboring and the between-class neighboring information. NDE seeks a projection in such that the projected samples of different classes are far apart. Experimental results show that NDE achieves superior results to NPE in face authentication with error reduction at least 20%.
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spelling mmu-19442017-01-05T04:21:46Z http://shdl.mmu.edu.my/1944/ Neighbourhood discriminant embedding in face recognition Pang, Ying Han Teoh, Andrew Ben Jin Wong, Eng Kiong T Technology (General) Neighborhood Preserving Embedding (NPE) is a linear approximate of Locally Linear Embedding with local geometry preserving property. An efficient face recognition method requires a mapping to separate within-class structure from between-class structure. But, NPE is not in the case since it is unsupervised. Hence, we improved NPE-utilizing the neighbor and class relations of face data. The proposed technique, Neighborhood Discriminant Embedding (NDE), takes into account the local neighboring and the between-class neighboring information. NDE seeks a projection in such that the projected samples of different classes are far apart. Experimental results show that NDE achieves superior results to NPE in face authentication with error reduction at least 20%. The Institute of Electronics, Information and Communication Engineers 2008-12 Article NonPeerReviewed text en http://shdl.mmu.edu.my/1944/1/Neighbourhood%20discriminant%20embedding%20in%20face%20recognition.pdf Pang, Ying Han and Teoh, Andrew Ben Jin and Wong, Eng Kiong (2008) Neighbourhood discriminant embedding in face recognition. IEICE Electronics Express, 5 (24). pp. 1036-1041. ISSN 1349-2543 http://dx.doi.org/10.1587/elex.5.1036 doi:10.1587/elex.5.1036 doi:10.1587/elex.5.1036
spellingShingle T Technology (General)
Pang, Ying Han
Teoh, Andrew Ben Jin
Wong, Eng Kiong
Neighbourhood discriminant embedding in face recognition
title Neighbourhood discriminant embedding in face recognition
title_full Neighbourhood discriminant embedding in face recognition
title_fullStr Neighbourhood discriminant embedding in face recognition
title_full_unstemmed Neighbourhood discriminant embedding in face recognition
title_short Neighbourhood discriminant embedding in face recognition
title_sort neighbourhood discriminant embedding in face recognition
topic T Technology (General)
url http://shdl.mmu.edu.my/1944/
http://shdl.mmu.edu.my/1944/
http://shdl.mmu.edu.my/1944/
http://shdl.mmu.edu.my/1944/1/Neighbourhood%20discriminant%20embedding%20in%20face%20recognition.pdf