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Two-dimensional pca: a new approach to appearance-based face representation and recognition
Open accessAbstract
In this paper, a new technique coined two-dimensional principal component analysis (2DPCA) is developed for image representation. As opposed to PCA, 2DPCA is based on 2D image matrices rather than 1D vectors so the image matrix does not need to be transformed into a vector prior to feature extraction. Instead, an image covariance matrix is constructed directly using the original image matrices, and its eigenvectors are derived for image feature extraction. To test 2DPCA and evaluate its performance, a series of experiments were performed on three face image databases: ORL, AR, and Yale face databases. The recognition rate across all trials was higher using 2DPCA than PCA. The experimental results also indicated that the extraction of image features is computationally more efficient using 2DPCA than PCA.
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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
Cited by
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Local Directional Number Pattern for Face Analysis: Face and Expression Recognition
Ramirez Rivera, A., Rojas Castillo, J., & Oksam Chae, O. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2235848 · Cited by 512
Principal Component Analysis: A Natural Approach to Data Exploration
Gewers, F. L., Ferreira, G. R., Arruda, H. F. D., Silva, F. N., Comin, C. H., Amancio, D. R., & Costa, L. D. F. (2022) · ACM Computing Surveys · doi:10.1145/3447755 · Cited by 508
Gumaei, A., Hassan, M. M., Hassan, M. R., Alelaiwi, A., & Fortino, G. (2019) · IEEE Access · doi:10.1109/access.2019.2904145 · Cited by 484
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
Metadata
- Authors
- Yang, J., Zhang, D., Frangi, A. F., & Yang, J.-Y.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2004-01
- Volume
- 26
- Issue
- 1
- Pages
- 131-137
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2102544846
- Cited by
- 3,563
- References
- 1
- FWCI
- 111.07
- Type
- journal article
- Language
- en
- Open access
- green
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- Yang, J., Zhang, D., Frangi, A. F., & Yang, J.-Y. (2004). Two-dimensional pca: a new approach to appearance-based face representation and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2004.1261097
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