Face detection using SVM trained in independent space

Quan Xue Gao; Quan Pan; Hong Cai Zhang; Yong Mei Cheng; Qi Chuan Tian

doi:10.1109/ICMLC.2004.1380445

Face detection using SVM trained in independent space

Quan Xue Gao
, Quan Pan
, Hong Cai Zhang
, Yong Mei Cheng
, Qi Chuan Tian

School of Automation

Northwestern Polytechnical University Xian
Tai Yuan Heavy Machinery Institute

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

3 Scopus citations

Abstract

The classical face representation method, such as eigenface, extracts covariance based on low-order statistics feature of image. However, high-order information represents image details, which are necessary for pattern recognition. Hence, PCA is first used to reduce its dimension; then the Independent Component Analysis (ICA) is applied to further obtain independent feature vector instead of low-order statistics; finally support vector machine is used as a classifier that has demonstrated high generalization capabilities for face detection. The feasibility and correctness of this new face detection method are shown in CBCL Face Dataset.

Original language	English
Title of host publication	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3674-3677
Number of pages	4
ISBN (Print)	0780384032, 9780780384033
DOIs	https://doi.org/10.1109/ICMLC.2004.1380445
State	Published - 2004
Event	3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004 - Shanghai, China Duration: 26 Aug 2004 → 29 Aug 2004

Publication series

Name	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume	6

Conference

Conference	3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004
Country/Territory	China
City	Shanghai
Period	26/08/04 → 29/08/04

Keywords

Face detection
ICA
PCA
SVM

Access to Document

10.1109/ICMLC.2004.1380445

Cite this

Gao, Q. X., Pan, Q., Zhang, H. C., Cheng, Y. M., & Tian, Q. C. (2004). Face detection using SVM trained in independent space. In Proceedings of 2004 International Conference on Machine Learning and Cybernetics (pp. 3674-3677). (Proceedings of 2004 International Conference on Machine Learning and Cybernetics; Vol. 6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMLC.2004.1380445

@inproceedings{9f16f66b3369411f885a4c53e113372b,

title = "Face detection using SVM trained in independent space",

abstract = "The classical face representation method, such as eigenface, extracts covariance based on low-order statistics feature of image. However, high-order information represents image details, which are necessary for pattern recognition. Hence, PCA is first used to reduce its dimension; then the Independent Component Analysis (ICA) is applied to further obtain independent feature vector instead of low-order statistics; finally support vector machine is used as a classifier that has demonstrated high generalization capabilities for face detection. The feasibility and correctness of this new face detection method are shown in CBCL Face Dataset.",

keywords = "Face detection, ICA, PCA, SVM",

author = "Gao, \{Quan Xue\} and Quan Pan and Zhang, \{Hong Cai\} and Cheng, \{Yong Mei\} and Tian, \{Qi Chuan\}",

year = "2004",

doi = "10.1109/ICMLC.2004.1380445",

language = "英语",

isbn = "0780384032",

series = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3674--3677",

booktitle = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

note = "3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004 ; Conference date: 26-08-2004 Through 29-08-2004",

}

Gao, QX, Pan, Q, Zhang, HC, Cheng, YM & Tian, QC 2004, Face detection using SVM trained in independent space. in Proceedings of 2004 International Conference on Machine Learning and Cybernetics. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, vol. 6, Institute of Electrical and Electronics Engineers Inc., pp. 3674-3677, 3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004, Shanghai, China, 26/08/04. https://doi.org/10.1109/ICMLC.2004.1380445

Face detection using SVM trained in independent space. / Gao, Quan Xue; Pan, Quan; Zhang, Hong Cai et al.
Proceedings of 2004 International Conference on Machine Learning and Cybernetics. Institute of Electrical and Electronics Engineers Inc., 2004. p. 3674-3677 (Proceedings of 2004 International Conference on Machine Learning and Cybernetics; Vol. 6).

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

TY - GEN

T1 - Face detection using SVM trained in independent space

AU - Gao, Quan Xue

AU - Pan, Quan

AU - Zhang, Hong Cai

AU - Cheng, Yong Mei

AU - Tian, Qi Chuan

PY - 2004

Y1 - 2004

N2 - The classical face representation method, such as eigenface, extracts covariance based on low-order statistics feature of image. However, high-order information represents image details, which are necessary for pattern recognition. Hence, PCA is first used to reduce its dimension; then the Independent Component Analysis (ICA) is applied to further obtain independent feature vector instead of low-order statistics; finally support vector machine is used as a classifier that has demonstrated high generalization capabilities for face detection. The feasibility and correctness of this new face detection method are shown in CBCL Face Dataset.

AB - The classical face representation method, such as eigenface, extracts covariance based on low-order statistics feature of image. However, high-order information represents image details, which are necessary for pattern recognition. Hence, PCA is first used to reduce its dimension; then the Independent Component Analysis (ICA) is applied to further obtain independent feature vector instead of low-order statistics; finally support vector machine is used as a classifier that has demonstrated high generalization capabilities for face detection. The feasibility and correctness of this new face detection method are shown in CBCL Face Dataset.

KW - Face detection

KW - ICA

KW - PCA

KW - SVM

UR - https://www.scopus.com/pages/publications/6344239049

U2 - 10.1109/ICMLC.2004.1380445

DO - 10.1109/ICMLC.2004.1380445

M3 - 会议稿件

AN - SCOPUS:6344239049

SN - 0780384032

SN - 9780780384033

T3 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

SP - 3674

EP - 3677

BT - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004

Y2 - 26 August 2004 through 29 August 2004

ER -

Gao QX, Pan Q, Zhang HC, Cheng YM, Tian QC. Face detection using SVM trained in independent space. In Proceedings of 2004 International Conference on Machine Learning and Cybernetics. Institute of Electrical and Electronics Engineers Inc. 2004. p. 3674-3677. (Proceedings of 2004 International Conference on Machine Learning and Cybernetics). doi: 10.1109/ICMLC.2004.1380445

Face detection using SVM trained in independent space

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Keywords

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