On aggregated 2D gabor features for appearance-based face recognition

King Hong Cheung; Jia You; Qin Li; Prabir Bhattacharya

On aggregated 2D gabor features for appearance-based face recognition

King Hong Cheung, Jia You, Qin Li, Prabir Bhattacharya

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

Face recognition performed in a controlled environment can be reduced to classical image retrieval/pattern recognition of frontal 2D images of a person. Current holistic appearance based methods require a high dimension feature space to cope with the problem. We, therefore, proposed a relatively low feature dimension scheme for the reduced face recognition problem; aggregated Gabor filter responses is employed to represent face images. Experiments have been done on two testing sets of a face image database from which the preprocessing and size of image differ; each set contains over 3,000 images of the same 120 subjects.

Original language	English
Title of host publication	Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology
Subtitle of host publication	Computer Graphics, CISST'05
Pages	33-39
Number of pages	7
Publication status	Published - 1 Dec 2005
Event	2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05 - Las Vegas, NV, United States Duration: 27 Jun 2005 → 30 Jun 2005

Conference

Conference	2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05
Country/Territory	United States
City	Las Vegas, NV
Period	27/06/05 → 30/06/05

Keywords

Biometrics
Gabor features
Gabor filters
Holistic face recognition
Principal component analysis

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Vision and Pattern Recognition

Cite this

@inproceedings{592f069a7590480bb47a64a405ffc612,

title = "On aggregated 2D gabor features for appearance-based face recognition",

abstract = "Face recognition performed in a controlled environment can be reduced to classical image retrieval/pattern recognition of frontal 2D images of a person. Current holistic appearance based methods require a high dimension feature space to cope with the problem. We, therefore, proposed a relatively low feature dimension scheme for the reduced face recognition problem; aggregated Gabor filter responses is employed to represent face images. Experiments have been done on two testing sets of a face image database from which the preprocessing and size of image differ; each set contains over 3,000 images of the same 120 subjects.",

keywords = "Biometrics, Gabor features, Gabor filters, Holistic face recognition, Principal component analysis",

author = "Cheung, {King Hong} and Jia You and Qin Li and Prabir Bhattacharya",

year = "2005",

month = dec,

day = "1",

language = "English",

isbn = "9781932415643",

pages = "33--39",

booktitle = "Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology",

note = "2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05 ; Conference date: 27-06-2005 Through 30-06-2005",

}

Cheung, KH, You, J, Li, Q & Bhattacharya, P 2005, On aggregated 2D gabor features for appearance-based face recognition. in Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05. pp. 33-39, 2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05, Las Vegas, NV, United States, 27/06/05.

On aggregated 2D gabor features for appearance-based face recognition. / Cheung, King Hong; You, Jia; Li, Qin et al.
Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05. 2005. p. 33-39.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - On aggregated 2D gabor features for appearance-based face recognition

AU - Cheung, King Hong

AU - You, Jia

AU - Li, Qin

AU - Bhattacharya, Prabir

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Face recognition performed in a controlled environment can be reduced to classical image retrieval/pattern recognition of frontal 2D images of a person. Current holistic appearance based methods require a high dimension feature space to cope with the problem. We, therefore, proposed a relatively low feature dimension scheme for the reduced face recognition problem; aggregated Gabor filter responses is employed to represent face images. Experiments have been done on two testing sets of a face image database from which the preprocessing and size of image differ; each set contains over 3,000 images of the same 120 subjects.

AB - Face recognition performed in a controlled environment can be reduced to classical image retrieval/pattern recognition of frontal 2D images of a person. Current holistic appearance based methods require a high dimension feature space to cope with the problem. We, therefore, proposed a relatively low feature dimension scheme for the reduced face recognition problem; aggregated Gabor filter responses is employed to represent face images. Experiments have been done on two testing sets of a face image database from which the preprocessing and size of image differ; each set contains over 3,000 images of the same 120 subjects.

KW - Biometrics

KW - Gabor features

KW - Gabor filters

KW - Holistic face recognition

KW - Principal component analysis

UR - http://www.scopus.com/inward/record.url?scp=60649122055&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 9781932415643

SP - 33

EP - 39

BT - Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology

T2 - 2005 International Conference on Imaging Science, Systems, and Technology: Computer Graphics, CISST'05

Y2 - 27 June 2005 through 30 June 2005

ER -

On aggregated 2D gabor features for appearance-based face recognition

Abstract

Conference

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this