The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Hierarchical Ensemble of Global and Local Classifiers for Face Recognition
Abstract
In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which exploits both global and local discriminative features. In this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of Fourier transform, which we believe encodes the holistic facial information, such as facial contour. For local feature extraction, Gabor wavelets are exploited considering their biological relevance. After that, Fisher's linear discriminant (FLD) is separately applied to the global Fourier features and each local patch of Gabor features. Thus, multiple FLD classifiers are obtained, each embodying different facial evidences for face recognition. Finally, all these classifiers are combined to form a hierarchical ensemble classifier. We evaluate the proposed method using two large-scale face databases: FERET and FRGC version 2.0. Experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.
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Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
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
Wrappers for feature subset selection
Kohavi, R., & John, G. H. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00043-x · Cited by 8,947
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
Daugman, J. G. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.001160 · Cited by 3,219
Face recognition by elastic bunch graph matching
Wiskott, L., Fellous, J.-M., Kuiger, N., & von der Malsburg, C. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.598235 · Cited by 2,883
Face Recognition with Local Binary Patterns
Ahonen, T., Hadid, A., & Pietikäinen, M. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24670-1_36 · Cited by 2,462
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
The FERET database and evaluation procedure for face-recognition algorithms
Phillips, P. J., Wechsler, H., Huang, J., & Rauss, P. J. (1998) · Image and Vision Computing · doi:10.1016/s0262-8856(97)00070-x · Cited by 2,431
Cited by
Dong, X., Yu, Z., Cao, W., Shi, Y., & Ma, Q. (2020) · Frontiers of Computer Science · doi:10.1007/s11704-019-8208-z · Cited by 1,928
Ensembles for feature selection: A review and future trends
Bolón-Canedo, V., & Alonso-Betanzos, A. (2019) · Information Fusion · doi:10.1016/j.inffus.2018.11.008 · Cited by 541
Gabor Feature Based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary
Yang, M., & Zhang, L. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15567-3_33 · Cited by 437
Fusing local patterns of Gabor magnitude and phase for face recognition
Xie, S., Shan, S., Chen, X., & Chen, J. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2041397 · Cited by 395
Self-citationMulti-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition
Ding, C., Choi, J., Tao, D., & Davis, L. S. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2462338 · Cited by 381
Metadata
- Authors
- Su, Y., Shan, S., Chen, X., & Gao, W.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2009-08
- Volume
- 18
- Issue
- 8
- Pages
- 1885-1896
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2119077463
- Cited by
- 309
- References
- 35
- FWCI
- 28.95
- Type
- journal article
- Language
- en
- Open access
- closed
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