The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Eigenfeature Regularization and Extraction in Face Recognition
Abstract
This work proposes a subspace approach that regularizes and extracts eigenfeatures from the face image. Eigenspace of the within-class scatter matrix is decomposed into three subspaces: a reliable subspace spanned mainly by the facial variation, an unstable subspace due to noise and finite number of training samples and a null subspace. Eigenfeatures are regularized differently in these three subspaces based on an eigenspectrum model to alleviate problems of instability, over-fitting or poor generalization. This also enables the discriminant evaluation performed in the whole space. Feature extraction or dimensionality reduction occurs only at the final stage after the discriminant assessment. These efforts facilitate a discriminative and stable low-dimensional feature representation of the face image. Experiments comparing the proposed approach with some other popular subspace methods on the FERET, ORL, AR and GT databases show that our method consistently outperforms others.
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Cites
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
Belhumeur, P. N., Hespanha, J. P., & Kriegman, D. J. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.598228 · Cited by 11,707
Face recognition: A literature survey
Zhao, W., Chellappa, R., Phillips, P. J., & Rosenfeld, A. (2003) · ACM Computing Surveys · doi:10.1145/954339.954342 · Cited by 6,163
The FERET evaluation methodology for face-recognition algorithms
Phillips, P. J., Moon, H., Rizvi, S. A., & Rauss, P. J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.879790 · Cited by 3,692
Face recognition using Laplacianfaces
He, X., Yan, S., Hu, Y., Niyogi, P., & Zhang, H.-J. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.55 · Cited by 3,264
Martinez, A. M., & Kak, A. C. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.908974 · Cited by 3,249
Parameterisation of a stochastic model for human face identification
Samaria, F. S., & Harter, A. C. (2002) · Proceedings of 1994 IEEE Workshop on Applications of Computer Vision · doi:10.1109/acv.1994.341300 · Cited by 2,593
Application of the Karhunen-Loeve procedure for the characterization of human faces
Kirby, M., & Sirovich, L. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.41390 · Cited by 2,448
Overview of the Face Recognition Grand Challenge
Phillips, P. J., Flynn, P. J., Scruggs, T., Bowyer, K. W., Chang, J., Hoffman, K., Marques, J., Min, J., & Worek, W. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.268 · Cited by 2,438
Regularized Discriminant Analysis
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Cited by
Linear Regression for Face Recognition
Naseem, I., Togneri, R., & Bennamoun, M. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.128 · Cited by 1,012
Face Recognition Performance: Role of Demographic Information
Klare, B. F., Burge, M. J., Klontz, J. C., Vorder Bruegge, R. W., & Jain, A. K. (2012) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2214212 · Cited by 516
“While 4SF is intended to be representative of learningbased methods in face recognition, it could be the case that other learning-based algorithms (such as [20], [21], [22], [23]) exhibit different amounts of sensitivity to the demographic distribution of the training data.”
Linear discriminant analysis for the small sample size problem: an overview
Sharma, A., & Paliwal, K. K. (2015) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-013-0226-9 · Cited by 279
Metadata
- Authors
- Jiang, X., Mandal, B., & Kot, A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2008-03
- Volume
- 30
- Issue
- 3
- Pages
- 383-394
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2165554381
- Cited by
- 310
- References
- 35
- FWCI
- 44.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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