A comparison of genetic feature selection and weighting techniques for multi-biometric recognition

Khary Popplewell; Aniesha Alford; Gerry Dozier; Kelvin Bryant; John Kelly; Josh Adams; Tamirat Abegaz; Kamiliah Purrington; Joseph Shelton

doi:10.1145/2016039.2016094

A comparison of genetic feature selection and weighting techniques for multi-biometric recognition

Khary Popplewell
, Aniesha Alford
, Gerry Dozier
, Kelvin Bryant
, John Kelly
, Josh Adams
, Tamirat Abegaz
, Kamiliah Purrington
, Joseph Shelton

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we compare genetic-based feature selection (GEFeS) and weighting (GEFeW) techniques for multi-biometric recognition using face and periocular biometric modalities. Our results show that fusing face and periocular features outperforms face-only and periocular-only biometric recognition. Of the two genetic-based approaches, GEFeW outperforms GEFeS. © 2011 ACM.

Original language	English
Title of host publication	49th Annual Association for Computing Machinery Southeast Conference, ACMSE'11
DOIs	https://doi.org/10.1145/2016039.2016094
State	Published - 2011

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@inproceedings{e4304ccac53b41a288eae7d5620dc6c1,

title = "A comparison of genetic feature selection and weighting techniques for multi-biometric recognition",

abstract = "In this paper, we compare genetic-based feature selection (GEFeS) and weighting (GEFeW) techniques for multi-biometric recognition using face and periocular biometric modalities. Our results show that fusing face and periocular features outperforms face-only and periocular-only biometric recognition. Of the two genetic-based approaches, GEFeW outperforms GEFeS. {\textcopyright} 2011 ACM.",

author = "Khary Popplewell and Aniesha Alford and Gerry Dozier and Kelvin Bryant and John Kelly and Josh Adams and Tamirat Abegaz and Kamiliah Purrington and Joseph Shelton",

year = "2011",

doi = "10.1145/2016039.2016094",

language = "English",

booktitle = "49th Annual Association for Computing Machinery Southeast Conference, ACMSE'11",

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T1 - A comparison of genetic feature selection and weighting techniques for multi-biometric recognition

AU - Popplewell, Khary

AU - Alford, Aniesha

AU - Dozier, Gerry

AU - Bryant, Kelvin

AU - Kelly, John

AU - Adams, Josh

AU - Abegaz, Tamirat

AU - Purrington, Kamiliah

AU - Shelton, Joseph

PY - 2011

Y1 - 2011

N2 - In this paper, we compare genetic-based feature selection (GEFeS) and weighting (GEFeW) techniques for multi-biometric recognition using face and periocular biometric modalities. Our results show that fusing face and periocular features outperforms face-only and periocular-only biometric recognition. Of the two genetic-based approaches, GEFeW outperforms GEFeS. © 2011 ACM.

AB - In this paper, we compare genetic-based feature selection (GEFeS) and weighting (GEFeW) techniques for multi-biometric recognition using face and periocular biometric modalities. Our results show that fusing face and periocular features outperforms face-only and periocular-only biometric recognition. Of the two genetic-based approaches, GEFeW outperforms GEFeS. © 2011 ACM.

UR - https://dx.doi.org/10.1145/2016039.2016094

U2 - 10.1145/2016039.2016094

DO - 10.1145/2016039.2016094

M3 - Conference contribution

BT - 49th Annual Association for Computing Machinery Southeast Conference, ACMSE'11

ER -

A comparison of genetic feature selection and weighting techniques for multi-biometric recognition

Abstract

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