Abstract
We address the problem of pose and illumination invariance in face recognition and propose to use explicit 3D model and variants of existing algorithms for both pose [Fit01, MSCA04] and illumination normalization [ZS04] prior to applying 2D face recognition algorithm. However, contrary to prior work we will use person specific, rather than general 3D face models. The proposed solution is realistic as for many applications the additional cost of acquiring 3D face images during enrolment of the subjects is acceptable. 3D sensing is not required during normal operation of the face recognition system. The proposed methodology achieves illumination invariance by estimating the illumination sources using the 3D face model. By-product of this process is the recovery of the face skin albedo which can be used as a photometrically normalised face image. Standard face recognition techniques can then be applied to such illumination corrected images.
Keywords
- Face Recognition
- Face Image
- Face Skin
- Normalise Face
- Face Recognition System
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Bajaj, C., Xu, G.: Local Interpolation and Approximation using G k-Continuous Piecewise Real Algebraic Curves. Computer Aided Geometric Desing 16, 557–578 (1999)
Bajaj, C., Xu, G.: Regular algebraic curve sections (III) - Applications in interactive design and data fitting. Computer Aided Geometric Desing 18, 149–173 (2001)
Behar, S., Hernández, V., Alvarez, L., Estrada, J.: Computing a revolution shell using a G 2-continuous A-spline and a semidiscrete method for the EDPs. In: Proceedings IV, ITLA, 2001, pp. 241–250 (2001) ISBN: 959-7056-13-5
Estrada, J., Martínez, D., León, D., Theisel, H.: Solving Geometric Problems using Subdivision Methods and Range Analysis. In: Daehlen, M., Morken, K., Shumaker, L.L. (eds.) Mathematical Methods for Curves and Surfaces: Tromso 2004, pp. 101–114. Nashboro Press, Brentwood (2005)
Hernández, V., Martínez, D., Estrada, J.: Fitting a conic A-spline to contour image data. Revista Investigación Operacional 29, 55–64 (2002)
Hernández, V., Behar, S., Estrada, J.: Geometric design by means of a G 2 continuous A-spline, Approximation, Optimization and Mathematical Economics, pp. 133–145. Physica-Verlag, Heidelberg (2001)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. International. J. Comput. Vision, 321–331 (1988)
Paluszny, M., Patterson, R.: G 2-continuous cubic algebraic splines and their efficient display. In: Laurent, P.J., Le Méhauté, A., Schumacker, L.L. (eds.) Curves and Surfaces II, pp. 353–359 (1994)
Paluszny, M., Patterson, R.: Geometric control of G 2-cubic A-splines. Computer Aided Geometric Design 15, 261–287 (1998)
Ray, B., Ray, K.: A non-parametric sequential method for polygonal approximation of digital curves. Pattern Recognition Letters 15, 161–167 (1994)
Sethian, J.A.: Level Set Methods. Cambridge Univ. Press, Cambridge (1996)
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Kittler, J., Hamouz, M., Tena, J.R., Hilton, A., Illingworth, J., Ruiz, M. (2005). 3D Assisted 2D Face Recognition: Methodology. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_108
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DOI: https://doi.org/10.1007/11578079_108
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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