Paper:
Spherical Spaces for Illumination Invariant Face Relighting
Amr Almaddah, Sadi Vural, Yasushi Mae,
Kenichi Ohara, and Tatsuo Arai
Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan
- [1] S. Pankanti, “On the individuality of fingerprints,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.24, No.8, pp. 1010-1025, 2002.
- [2] L. Ma, T. Tan, and D. Zhang, “Personal identification based on iris texture analysis,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.25, No.12, pp. 1519-1533, 2003.
- [3] P. Hallinan, “A low-dimensional representation of human faces for arbitrary lighting conditions,” In Proc. of IEEE Conf. on Computer Vision and Pattern Recogition, pp. 995-999, 1994.
- [4] A. Samil and P. Iyengar, “Automatic recognition and analysis of human faces and facial expressions: A survey,” J. of Foo, pp. 65-75, 1992.
- [5] L. Wiskott, J. Fellous, N. Kruger, and C. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.19, No.7, pp. 775-779, 1997.
- [6] M. Turk and A. Pentland, “Eigenfaces for recognition,” J. of Cognitive Neuroscience, Vol.3, No.1, pp. 71-96, 1991.
- [7] H. Murase and S. Nayar, “Visual recognition of 3-d objects from appearance,” Int. J. of Computer Vision, Vol.14, No.1, pp. 5-24, 1995.
- [8] Y. Adini, Y. Moses, and S. Ullman, “Face recognition: The problem of compensating for changes in illumination directions,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.19, No.3, pp. 721-732, 1997.
- [9] A. Shashua and T. Riklin, “The quotient image: Class-based re-rendering and recognition with varying illuminations,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.23, No.2, pp. 129-139, 2001.
- [10] P. Belhumeur, “What is the set of images of an object under all possible lighting conditions?,” IEEE Conf. on Computer Vision and Pattern Recognition, 1996.
- [11] A. Georghiades and D. Kriegman, “From few to many: illumination cone models for face recognition under variable lighting and pose,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.23, No.6, pp. 643-660, 2001.
- [12] R. Basri and D. Jacobs, “Lambertian reflectance and linear subspaces,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.25, No.2, 2003.
- [13] K. Lee, J. Ho, and D. Kriegman, “Nine points of light: Acquiring subspaces for face recognition under variable lighting,” IEEE Conf. on Vision and Pattern Recognition, pp. 519-525, 2001.
- [14] L. Zhang and D. Samaras, “Face recognition from a single training image under arbitrary unknown lighting using spherical harmonics,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.28, No.3, pp. 351-363, 2006.
- [15] D. Samaras and D. Metaxas, “Coupled lighting direction and shape estimation from single images,” IEEE Int. Conf. on Computer Vision, Vol.2, pp. 868-874, 1999.
- [16] C. Liu and H. Wechsler, “Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition,” IEEE Trans. on Image Processing, Vol.11, No.4, pp. 467-476, 2002.
- [17] J. Yang, D. Zhang, and A. Frangi, “Two-dimensional pca: a new approach to appearance-based face representation and recognition,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.26, No.1, pp. 131-137, 2004.
- [18] K. Kim, K. Jung, and H. J. Kim, “Face recognition using kernel principal component analysis,” IEEE Signal Processing Letters, Vol.9, No.2, pp. 40-42, 2002.
- [19] J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma, “Robust face recognition via sparse representation,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.31, No.2, pp. 210-227, 2009.
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