Enhancing local binary patterns distinctiveness for face representation
The Local Binary pattern (LBP) is a well-known feature and has been widely used for human identification. However, the amount of information extracted is limited which reduces the LBP discriminative power. Recently, some enhancements have been proposed by adding preprocessing stages or considering m...
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sg-ntu-dr.10356-1006462020-03-07T13:24:50Z Enhancing local binary patterns distinctiveness for face representation Ghahramani, Mohammad Yau, Wei-Yun Teoh, Eam Khwang School of Electrical and Electronic Engineering IEEE International Symposium on Multimedia (2011 : Dana point, California, US) A*STAR Institute for Infocomm Research DRNTU::Engineering::Electrical and electronic engineering The Local Binary pattern (LBP) is a well-known feature and has been widely used for human identification. However, the amount of information extracted is limited which reduces the LBP discriminative power. Recently, some enhancements have been proposed by adding preprocessing stages or considering more neighbor pixels to enrich the extracted feature. In this paper, we propose Uniformly-sampled Thresholds for LBP (UTLBP) operator that increases the richness of information derived from the LBP feature. It outperforms other features in various probe sets of the large CAS-PEAL database for face recognition. Moreover, we collected a database of 25 families to verify the superiority of the proposed feature in the family verification. Results show that using the UTLBP, the total error in face recognition and family verification is reduced up to 8% and 3% respectively comparing to the state of the art LBP. It improves the missing family member verification performance up to 3% where, contrary to expectation, increasing the LBP operator radius worsens the performance by 2%. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2013-12-04T03:30:54Z 2019-12-06T20:25:52Z 2013-12-04T03:30:54Z 2019-12-06T20:25:52Z 2011 2011 Conference Paper Ghahramani, M., Yau, W. Y., & Teoh, E. K. (2011). Enhancing local binary patterns distinctiveness for face representation. IEEE International Symposium on Multimedia (ISM), 440-445. https://hdl.handle.net/10356/100646 http://hdl.handle.net/10220/18009 10.1109/ISM.2011.78 en © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ISM.2011.78]. 6 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Ghahramani, Mohammad Yau, Wei-Yun Teoh, Eam Khwang Enhancing local binary patterns distinctiveness for face representation |
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The Local Binary pattern (LBP) is a well-known feature and has been widely used for human identification. However, the amount of information extracted is limited which reduces the LBP discriminative power. Recently, some enhancements have been proposed by adding preprocessing stages or considering more neighbor pixels to enrich the extracted feature. In this paper, we propose Uniformly-sampled Thresholds for LBP (UTLBP) operator that increases the richness of information derived from the LBP feature. It outperforms other features in various probe sets of the large CAS-PEAL database for face recognition. Moreover, we collected a database of 25 families to verify the superiority of the proposed feature in the family verification. Results show that using the UTLBP, the total error in face recognition and family verification is reduced up to 8% and 3% respectively comparing to the state of the art LBP. It improves the missing family member verification performance up to 3% where, contrary to expectation, increasing the LBP operator radius worsens the performance by 2%. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Ghahramani, Mohammad Yau, Wei-Yun Teoh, Eam Khwang |
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Conference or Workshop Item |
author |
Ghahramani, Mohammad Yau, Wei-Yun Teoh, Eam Khwang |
author_sort |
Ghahramani, Mohammad |
title |
Enhancing local binary patterns distinctiveness for face representation |
title_short |
Enhancing local binary patterns distinctiveness for face representation |
title_full |
Enhancing local binary patterns distinctiveness for face representation |
title_fullStr |
Enhancing local binary patterns distinctiveness for face representation |
title_full_unstemmed |
Enhancing local binary patterns distinctiveness for face representation |
title_sort |
enhancing local binary patterns distinctiveness for face representation |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/100646 http://hdl.handle.net/10220/18009 |
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1681047559594835968 |