Abstract
This paper proposes a new method to compare similarities of candidate models that are fitted to different areas of a query image. This method extracts the discriminant features that are changed due to the varying pose/lighting condition of given query image, and the confidence of each model-fitting is evaluated based on how much of the discriminant features is captured in each foreground. The confidence is fused with the similarity to enhance the face-identification performance. In an experiment using 7,000 images of 200 subjects taken under largely varying pose and lighting conditions, our proposed method reduced the recognition errors by more than 25% compared to the conventional method.
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References
Abate, F., Nappi, M., Riccio, D., Sabatino, G.: 2D and 3D face recognition: A survey. Pattern Recognition Letters 28(14), 1885–1906 (2007)
Basri, R., Jacobs, D.: Lambertian Reflectance and Linear Subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(2), 218–233 (2003)
Chen, H.F., Belhumeur, P.N., Jacobs, D.W.: In Search of Illumination Invariants. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2000), vol. 1, p. 1254 (2000)
Georghiades, A.S., Belhumeur, P.N., Kriegman, D.J.: From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 643–660 (2001)
Phillips, P.J., Grother, P., Michaels, R.J., Blackburn, D.M., Tabassi, E., Bone, M.: Face Recognition Vendor Test 2002: Evaluation Report NISTIR 6965. Nat’l Inst. of Standards and Technology (2003)
Ishiyama, R., Hamanaka, M., Sakamoto, S.: An Appearance Model Constructed on 3D Surface for Robust Face Recognition against Pose and Illumination Variations. IEEE Trans. Systems, Man, and Cybernetics-Part C 35(3), 326–334 (2005)
Ishiyama, R., Sakamoto, S.: Fast and Accurate Facial Pose Estimation by Aligning a 3D Appearance Model. In: Proceedings of 17th International Conference on Pattern Recognition (ICPR 2004), vol. 4, pp. 388–391 (2004)
Romdhani, S., Ho, J., Vetter, T., Kriegman, D.J.: Face Recognition Using 3-D Models: Pose and Illumination. Proceedings of the IEEE 94(11), 1977–1999 (2006)
Zhang, L., Samaras, D.: Face Recognition from a Single Training Image under Arbitrary Unknown Lighting Using Spherical Harmonics. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(3), 351–363 (2006)
Zhao, W., Chellappa, R., Phillips, P., Rosenfeld, A.: Face recognition: A literature survey. ACM Computing Surveys 35(4), 399–458 (2003)
Zhao, W., Chellappa, R.: Face Processing. Academic Press, London (2006)
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Ishiyama, R., Yasukawa, N. (2011). Extracting Scene-Dependent Discriminant Features for Enhancing Face Recognition under Severe Conditions. In: Koch, R., Huang, F. (eds) Computer Vision – ACCV 2010 Workshops. ACCV 2010. Lecture Notes in Computer Science, vol 6469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22819-3_43
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DOI: https://doi.org/10.1007/978-3-642-22819-3_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22818-6
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