Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance

Wei Zhou, Alireza Ahrary, Seiichiro Kamata

研究成果: Conference contribution

3 引用 (Scopus)

抄録

This paper presents a novel algorithm for face recognition. Local Quaternion Patters (LQP) is proposed for presenting the feature parts in the face. To keep the spatial feature of the face, an asymmetric similarity measure Weighted Spatially constrained Earth Mover's Distance (WSEMD) is studied for classification. In this step, the source image is partitioned into non overlapping local patches while the destination image is represented as a set of overlapping local patches at different positions and Gaussian Kernel is used. Finally, local and global weighting is applied to get a more accurate classifier. To evaluate the proposed method and its performance, three well-known and challenge face databases - ORL, Yale and FERET are used in our study. The experimental results show that the proposed method has higher accuracy than some other classic methods.

元の言語English
ホスト出版物のタイトルDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ページ285-289
ページ数5
DOI
出版物ステータスPublished - 2009
イベント2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009 - Kyoto
継続期間: 2009 5 252009 5 28

Other

Other2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009
Kyoto
期間09/5/2509/5/28

Fingerprint

Face recognition
Classifiers
Earth (planet)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

これを引用

Zhou, W., Ahrary, A., & Kamata, S. (2009). Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance. : Digest of Technical Papers - IEEE International Conference on Consumer Electronics (pp. 285-289). [5156971] https://doi.org/10.1109/ISCE.2009.5156971

Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance. / Zhou, Wei; Ahrary, Alireza; Kamata, Seiichiro.

Digest of Technical Papers - IEEE International Conference on Consumer Electronics. 2009. p. 285-289 5156971.

研究成果: Conference contribution

Zhou, W, Ahrary, A & Kamata, S 2009, Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance. : Digest of Technical Papers - IEEE International Conference on Consumer Electronics., 5156971, pp. 285-289, 2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009, Kyoto, 09/5/25. https://doi.org/10.1109/ISCE.2009.5156971
Zhou W, Ahrary A, Kamata S. Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance. : Digest of Technical Papers - IEEE International Conference on Consumer Electronics. 2009. p. 285-289. 5156971 https://doi.org/10.1109/ISCE.2009.5156971
Zhou, Wei ; Ahrary, Alireza ; Kamata, Seiichiro. / Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance. Digest of Technical Papers - IEEE International Conference on Consumer Electronics. 2009. pp. 285-289
@inproceedings{17305d5a2baa4779bc44df7782240b68,
title = "Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance",
abstract = "This paper presents a novel algorithm for face recognition. Local Quaternion Patters (LQP) is proposed for presenting the feature parts in the face. To keep the spatial feature of the face, an asymmetric similarity measure Weighted Spatially constrained Earth Mover's Distance (WSEMD) is studied for classification. In this step, the source image is partitioned into non overlapping local patches while the destination image is represented as a set of overlapping local patches at different positions and Gaussian Kernel is used. Finally, local and global weighting is applied to get a more accurate classifier. To evaluate the proposed method and its performance, three well-known and challenge face databases - ORL, Yale and FERET are used in our study. The experimental results show that the proposed method has higher accuracy than some other classic methods.",
keywords = "Face recognition, Feature extraction, Local quaternion patterns (LQP), WSEMD",
author = "Wei Zhou and Alireza Ahrary and Seiichiro Kamata",
year = "2009",
doi = "10.1109/ISCE.2009.5156971",
language = "English",
isbn = "9781424429769",
pages = "285--289",
booktitle = "Digest of Technical Papers - IEEE International Conference on Consumer Electronics",

}

TY - GEN

T1 - Face recognition using local quaternion patters and weighted spatially constrained earth mover's distance

AU - Zhou, Wei

AU - Ahrary, Alireza

AU - Kamata, Seiichiro

PY - 2009

Y1 - 2009

N2 - This paper presents a novel algorithm for face recognition. Local Quaternion Patters (LQP) is proposed for presenting the feature parts in the face. To keep the spatial feature of the face, an asymmetric similarity measure Weighted Spatially constrained Earth Mover's Distance (WSEMD) is studied for classification. In this step, the source image is partitioned into non overlapping local patches while the destination image is represented as a set of overlapping local patches at different positions and Gaussian Kernel is used. Finally, local and global weighting is applied to get a more accurate classifier. To evaluate the proposed method and its performance, three well-known and challenge face databases - ORL, Yale and FERET are used in our study. The experimental results show that the proposed method has higher accuracy than some other classic methods.

AB - This paper presents a novel algorithm for face recognition. Local Quaternion Patters (LQP) is proposed for presenting the feature parts in the face. To keep the spatial feature of the face, an asymmetric similarity measure Weighted Spatially constrained Earth Mover's Distance (WSEMD) is studied for classification. In this step, the source image is partitioned into non overlapping local patches while the destination image is represented as a set of overlapping local patches at different positions and Gaussian Kernel is used. Finally, local and global weighting is applied to get a more accurate classifier. To evaluate the proposed method and its performance, three well-known and challenge face databases - ORL, Yale and FERET are used in our study. The experimental results show that the proposed method has higher accuracy than some other classic methods.

KW - Face recognition

KW - Feature extraction

KW - Local quaternion patterns (LQP)

KW - WSEMD

UR - http://www.scopus.com/inward/record.url?scp=70350244987&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350244987&partnerID=8YFLogxK

U2 - 10.1109/ISCE.2009.5156971

DO - 10.1109/ISCE.2009.5156971

M3 - Conference contribution

AN - SCOPUS:70350244987

SN - 9781424429769

SP - 285

EP - 289

BT - Digest of Technical Papers - IEEE International Conference on Consumer Electronics

ER -