Local relation map : a novel illumination invariant face recognition approach
In this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete...
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sg-ntu-dr.10356-1062372019-12-06T22:07:07Z Local relation map : a novel illumination invariant face recognition approach Lian, Zhichao Er, Meng Joo School of Electrical and Electronic Engineering DRNTU::Engineering::Systems engineering In this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete Cosine Transform (DCT) are discarded to eliminate the effect caused by noise. Based on the local characteristics of the human face, a simple but effective illumination invariant feature local relation map is proposed. Experimental results on the Yale B, Extended Yale B and CMU PIE demonstrate the outperformance and lower computational burden of the proposed method compared to other existing methods. The results also demonstrate the validity of the proposed face model and the assumption on noise. Published version 2014-10-07T03:13:01Z 2019-12-06T22:07:07Z 2014-10-07T03:13:01Z 2019-12-06T22:07:07Z 2012 2012 Journal Article Lian, Z., & Er, M. J. (2012). Local relation map : a novel illumination invariant face recognition approach. International journal of advanced robotic systems, 9, 128-. 1729-8806 https://hdl.handle.net/10356/106237 http://hdl.handle.net/10220/23968 http://dx.doi.org/10.5772/51667 en International journal of advanced robotic systems © 2012 Zhichao et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf |
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DRNTU::Engineering::Systems engineering Lian, Zhichao Er, Meng Joo Local relation map : a novel illumination invariant face recognition approach |
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In this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete Cosine Transform (DCT) are discarded to eliminate the effect caused by noise. Based on the local characteristics of the human face, a simple but effective illumination invariant feature local relation map is proposed. Experimental results on the Yale B, Extended Yale B and CMU PIE demonstrate the outperformance and lower computational burden of the proposed method compared to other existing methods. The results also demonstrate the validity of the proposed face model and the assumption on noise. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Lian, Zhichao Er, Meng Joo |
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Article |
author |
Lian, Zhichao Er, Meng Joo |
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Lian, Zhichao |
title |
Local relation map : a novel illumination invariant face recognition approach |
title_short |
Local relation map : a novel illumination invariant face recognition approach |
title_full |
Local relation map : a novel illumination invariant face recognition approach |
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Local relation map : a novel illumination invariant face recognition approach |
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Local relation map : a novel illumination invariant face recognition approach |
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local relation map : a novel illumination invariant face recognition approach |
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2014 |
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https://hdl.handle.net/10356/106237 http://hdl.handle.net/10220/23968 http://dx.doi.org/10.5772/51667 |
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