Independent Component Regularisation Analysis on Face Verification

Face verification system is one of the biometrics technologies which has gained considerable attention since the past decades. It uses human’s unique characteristic which is face to authenticate one’s identity. Contactless verification from users to the device and avoiding using expensive devices ar...

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Main Author:	Liew, Yee Ping
Format:	Thesis
Published:	2015
Subjects:	TA1501-1820 Applied optics Photonics
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id	my-mmu-ep.6890
record_format	uketd_dc
spelling	my-mmu-ep.68902022-12-08T05:01:31Z Independent Component Regularisation Analysis on Face Verification 2015-07 Liew, Yee Ping TA1501-1820 Applied optics. Photonics Face verification system is one of the biometrics technologies which has gained considerable attention since the past decades. It uses human’s unique characteristic which is face to authenticate one’s identity. Contactless verification from users to the device and avoiding using expensive devices are two main reasons for the popularity of face verification application. Illumination, pose and facial expressions variations always resulting in performance degradation. Resolving these intra-class variations for promising performance is still a challenge in nowadays. Dimensionality reduction is one of the main tasks in face verification. Instead of using high dimensionality facial images, subspace approach has been introduced whereby each image dimension is reduced while redundant features are eliminated. This approach attempts to seek the most appropriate representation of the face data and extract features without sacrificing its discriminant information. 2015-07 Thesis http://shdl.mmu.edu.my/6890/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php masters Multimedia University Faculty of Information Science and Technology
institution	Multimedia University
collection	MMU Institutional Repository
topic	TA1501-1820 Applied optics Photonics
spellingShingle	TA1501-1820 Applied optics Photonics Liew, Yee Ping Independent Component Regularisation Analysis on Face Verification
description	Face verification system is one of the biometrics technologies which has gained considerable attention since the past decades. It uses human’s unique characteristic which is face to authenticate one’s identity. Contactless verification from users to the device and avoiding using expensive devices are two main reasons for the popularity of face verification application. Illumination, pose and facial expressions variations always resulting in performance degradation. Resolving these intra-class variations for promising performance is still a challenge in nowadays. Dimensionality reduction is one of the main tasks in face verification. Instead of using high dimensionality facial images, subspace approach has been introduced whereby each image dimension is reduced while redundant features are eliminated. This approach attempts to seek the most appropriate representation of the face data and extract features without sacrificing its discriminant information.
format	Thesis
qualification_level	Master's degree
author	Liew, Yee Ping
author_facet	Liew, Yee Ping
author_sort	Liew, Yee Ping
title	Independent Component Regularisation Analysis on Face Verification
title_short	Independent Component Regularisation Analysis on Face Verification
title_full	Independent Component Regularisation Analysis on Face Verification
title_fullStr	Independent Component Regularisation Analysis on Face Verification
title_full_unstemmed	Independent Component Regularisation Analysis on Face Verification
title_sort	independent component regularisation analysis on face verification
granting_institution	Multimedia University
granting_department	Faculty of Information Science and Technology
publishDate	2015
_version_	1776101414411436032

Independent Component Regularisation Analysis on Face Verification

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