The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Person-Specific SIFT Features for Face Recognition
Abstract
Scale invariant feature transform (SIFT) proposed by Lowe has been widely and successfully applied to object detection and recognition. However, the representation ability of SIFT features in face recognition has rarely been investigated systematically. In this paper, we proposed to use the person-specific SIFT features and a simple non-statistical matching strategy combined with local and global similarity on key-points clusters to solve face recognition problems. Large scale experiments on FERET and CAS-PEAL face databases using only one training sample per person have been carried out to compare it with other non person-specific features such as Gabor wavelet feature and local binary pattern feature. The experimental results demonstrate the robustness of SIFT features to expression, accessory and pose variations.
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
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
Cited by
Scale Invariant Feature Transform
Lindeberg, T. (2012) · Scholarpedia · doi:10.4249/scholarpedia.10491 · Cited by 621
Discriminative Multimanifold Analysis for Face Recognition from a Single Training Sample per Person
Lu, J., Tan, Y.-P., & Wang, G. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.70 · Cited by 334
Partial Face Recognition: Alignment-Free Approach
Liao, S., Jain, A. K., & Li, S. Z. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.191 · Cited by 313
Enabling task-level scheduling on heterogeneous platforms
Sun, E., Schaa, D., Bagley, R., Rubin, N., & Kaeli, D. (2012) · Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units · doi:10.1145/2159430.2159440 · Cited by 33
Metadata
- Authors
- Luo, J., Ma, Y., Takikawa, E., Lao, S., Kawade, M., & Lu, B.-L.
- Venue
- 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07
- Publisher
- IEEE
- Published
- 2007-04
- Pages
- II-593-II-596
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2009824857
- Cited by
- 187
- References
- 4
- FWCI
- 11.22
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Luo, J., Ma, Y., Takikawa, E., Lao, S., Kawade, M., & Lu, B.-L. (2007). Person-Specific SIFT Features for Face Recognition. 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07. https://doi.org/10.1109/icassp.2007.366305
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