The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
On the Use of SIFT Features for Face Authentication
Open accessAbstract
Several pattern recognition and classification techniques have been applied to the biometrics domain. Among them, an interesting technique is the Scale Invariant Feature Transform (SIFT), originally devised for object recognition. Even if SIFT features have emerged as a very powerful image descriptors, their employment in face analysis context has never been systematically investigated. This paper investigates the application of the SIFT approach in the context of face authentication. In order to determine the real potential and applicability of the method, different matching schemes are proposed and tested using the BANCA database and protocol, showing promising results.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
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
Digital Image Processing: PIKS Inside
Pratt, W. K. (2002) · Wiley eBooks · doi:10.1002/0471221325 · Cited by 4,340
PCA-SIFT: a more distinctive representation for local image descriptors
Ke, Y., & Sukthankar, R. (2004) · Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. · doi:10.1109/cvpr.2004.1315206 · Cited by 3,237
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 by Elastic Bunch Graph Matching*†
Wiskott, L., Fellous, J.-M., Krüger, N., & von der Malsburg, C. (2022) · INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION · doi:10.1201/9780203750520-11 · Cited by 1,781
Brown, & Lowe (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238630 · Cited by 934
Ill-posed problems in early vision
Bertero, M., Poggio, T. A., & Torre, V. (1988) · Proceedings of the IEEE · doi:10.1109/5.5962 · Cited by 723
Object recognition by computer: the role of geometric constraints
(1992) · Choice Reviews Online · doi:10.5860/choice.29-2747 · Cited by 654
Human image understanding: Recent research and a theory
Biederman, I. (1985) · Computer Vision, Graphics, and Image Processing · doi:10.1016/0734-189x(85)90002-7 · Cited by 606
Local feature view clustering for 3D object recognition
Lowe, D. G. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990541 · Cited by 482
The BANCA Database and Evaluation Protocol
Bailly-Bailliére, E., Bengio, S., Bimbot, F., Hamouz, M., Kittler, J., Mariéthoz, J., Matas, J., Messer, K., Popovici, V., Porée, F., et al. (2003) · Lecture Notes in Computer Science · doi:10.1007/3-540-44887-x_74 · Cited by 423
Boosting Local Binary Pattern (LBP)-Based Face Recognition
Zhang, G., Huang, X., Li, S. Z., Wang, Y., & Wu, X. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30548-4_21 · Cited by 271
A guided tour of computer vision
Nalwa, V. S. (1993) · Medical Entomology and Zoology · Cited by 205
Shakhnarovich, G., & Moghaddam, B. (2011) · Handbook of Face Recognition · doi:10.1007/978-0-85729-932-1_2 · Cited by 201
Local Binary Patterns as an Image Preprocessing for Face Authentication
Heusch, G., Rodriguez, Y., & Marcel, S. (2006) · 7th International Conference on Automatic Face and Gesture Recognition (FGR06) · doi:10.1109/fgr.2006.72 · Cited by 190
Nahm, F. K. D., Perret, A., Amaral, D. G., & Albright, T. D. (1997) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1997.9.5.611 · Cited by 131
Retinal vision applied to facial features detection and face authentication
Smeraldi, F., & Bigün, J. (2002) · Pattern Recognition Letters · doi:10.1016/s0167-8655(01)00178-7 · Cited by 113
Biederman, I. (1989) · doi:10.21236/ada204490 · Cited by 28
Active/space-variant object recognition
Massimo Tistarelli, A. (1995) · Image and Vision Computing · doi:10.1016/0262-8856(95)90841-u · Cited by 28
Fiducial point localization in color images of face foregrounds
Campadelli, P., & Lanzarotti, R. (2004) · Image and Vision Computing · doi:10.1016/j.imavis.2003.07.006 · Cited by 25
Knothe, R., Amberg, B., Romdhani, S., et al. (2011) · Springer eBooks · doi:10.1007/978-0-85729-932-1_6 · Cited by 9
Cited by
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
Huang, D., Shan, C., Ardabilian, M., Wang, Y., & Chen, L. (2011) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2118750 · Cited by 905
Scale Invariant Feature Transform
Lindeberg, T. (2012) · Scholarpedia · doi:10.4249/scholarpedia.10491 · Cited by 621
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
Metadata
- Authors
- Bicego, M., Lagorio, A., Grosso, E., & Tistarelli, M.
- Venue
- 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)
- Publisher
- IEEE
- Published
- 2006-07-10
- Pages
- 35-35
- OpenAlex
- W2164294799
- Cited by
- 371
- References
- 23
- FWCI
- 19.51
- Type
- conference paper
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
