References
[1]. Mattew Turk and Alex Pentland, (1991). “Eigenfaces
for Recognition”. Journal of Cognitive Neuroscience,
Vol.3, No.1, pp.71-86.
[2]. Kirby and Sirovich, (1990). “Application of Karhunen-
Loeve procedure for the characterization of human
faces”. IEEE Trans. Pattern Analysis and Machine
Intelligence, Vol.12, No.1, pp.103-108.
[3]. Turk, M.A., and A.L. Pentland, (1991). “Face
recognition using Eigen faces”. Proc. IEEE Computer
Society Conference Computer Vision and Pattern
Recognition, pp.586-591.
[4]. Kyungim Baek, Bruce A. Draper, J. Ross Beveridge,
and Kai She, (2002). “PCA vs. ICA: A Comparison on the
FERET Data Set”. Proceedings of the 6th Joint Conference
on Information Science (JCIS), pp.824-827.
[5]. T. Chen, W. Yin, X.-S. Zhou, D. Comaniciu, and T.S.
Huang, (2006). “Total Variation Models for variable
Lighting Face Recognition and uneven Background
Correction”. IEEE Transactions on Pattern Analysis and
Machine Intelligence, Vol.28, No.9, pp.1519-1524.
[6]. Longin Jan Latecki, Venugopal Rajagopal, and Ari
Gross, (2005). “Image Retrieval and Reversible
Illumination Normalization”. Electronic Imaging 2005.
International Society for Optics and Photonics, pp.99-
110.
[7]. P.J.B. Hancock, V. Bruce, and A.M. Burton, (1997).
“Testing Principal Component Representations for Faces”. Proc. of 4th Neural Computation and Psychology
Workshop, Springer, London, pp.84-97.
[8]. Jonathon Shlens, (2005). “A tutorial on Principal
Component Analysis”. arXiv preprint arXiv:1404.1100.
Systems Neurobiology Laboratory, Vol.2.
[9]. Zhujie, and Y.L. Yu, (1994). “Face recognition with
Eigen faces”. Proc. IEEE Intl. Conf. Industrial Technol,
Guangzhou, pp.434-438.
[10]. Delipersad, S.C. and A.D Broadhurst, (1997). “Face
recognition using neural networks”. Proc. IEEE
Communication Signal Processing (COMSIG'97), pp.33-
36.
[11]. Nazish, et al., (2001). “Face recognition using neural
networks”. Proc. IEEE INMIC 2001, pp.277-281.
[12]. D.E Rumelhart, G.E. Hinton, and R.J. Williams,
(1985). “Learning internal representation by error
propagation”. In D.E. Rumelhart and J.L. Mcclelland, Eds,
Parallel Distributed Processing Exploration in
Microstructure in Cognition, pp.318-362.
[13]. Kilian Q. Weinberger, and Lawrence K. Saul, (2009).
“Distance metric learning for large margin nearest
neighbor classification”. Journal of Machine Learning
Research, Vol.10, pp.207-244.
[14]. T. Kanade, (1973). Picture Processing by Computer
Complex and Recognition of Human Faces. Doctoral
Dissertation, University of Kyoto, Japan.
[15]. D. Zhang, S. Li, and D. Gatica-Perez, (2004). “Realtime
face detection using boosting learning in
hierarchical feature spaces”. In Proceedings of the
International Conference on Pattern Recognition (ICPR),
Cambridge, UK, pp.411-414.
[16]. P. Viola and M. Jones (2001). “Rapid object
detection using a boosted cascade of simple features”.
In Proceedings of the IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), Kauai, HI, USA.
pp.511-518.
[17]. T. Ojala, M. Pietikäinen, and T. Mäenpää, (2002).
“Multiresolution gray-scale and rotation invariant texture
classification with local binary patterns”. IEEE Transactions
on Pattern Analysis and Machine intelligence, Vol.24, No.7, pp.971-987.
[18]. Y. Freund and R.E. Schapire, (1996). “Experiments
with a new boosting algorithm”. In Proceedings of the IEEE
International Conference on Machine Learning (ICML),
Vol.96, pp.148-156.
[19]. B. Fröba and A. Ernst, (2004). “Face detection with the modified census transform”. In Proceedings of the 6th
IEEE International Conference on Automatic Face and
Gesture Recognition (AFGR), pp.91-96.
[20]. H. Jin, Q. Liu, H. Lu, and X. Tong, (2004). “Face
detection using improved LBP under Bayesian
framework”. In Proc. Third International Conference on
Image and Graphics (ICIG), pp.306-309.
[21]. T. Ahonen, A. Hadid, and M. Pietikäinen, (2004).
“Face recognition with local binary patterns”. In Proc. 8th
European Conference on Computer Vision (ECCV),
Prague, Czech Republic, pp.469-481
[22]. G. Zhang, X. Huang, S.Z. Li, Y. Wang, and X. Wu,
(2004). “Boosting Local Binary Pattern (LBP) based face
recognition”. In Proc. Advances in Biometric Person
Authentication: 5th Chinese Conference on Biometric
Recognition, Guangzhou, China, pp.179-186.
[23]. M. Turtinen, M. Pietikäinen, and O. Silven, (2005).
“Visual characterization of paper using isomap and local
binary patterns”. IEICE Transactions on Information and
Systems, Vol.89, No.7, pp.2076-2083.
[24]. V. Takala, T. Ahonen, and M. Pietikäinen, (2005).
“Block-based methods for image retrieval using local
binary patterns”. In Proc. 14th Scandinavian Conference
on Image Analysis (SCIA), Joensuu, Finland, pp.882-891.
[25]. M. Heikkilä, M. Pietikäinen, and J. Heikkilä, (2004).
“A texture-based method for detecting moving objects”. In Proc. 15th British Machine Vision Conference (BMVC),
Vol.401, pp.187-196.
[26]. T. Ojala, M. Pietikäinen, and D. Harwood, (1996). “A
comparative study of texture measures with classification
based on feature distributions”. Pattern Recognition,
Vol.29, No.1, pp.51-59.
[27]. R. Zabih and J. Woodfill, (1994). “Non-parametric
local transforms for computing visual correspondence”.
In Proceedings of the Third European Conference on
Computer Vision, Springer Berlin Heidelberg, pp.151-158.
[28]. X. Huang, S.Z. Li, and Y. Wang, (2004). “Shape
localization based on statistical method using extended
local binary pattern”. In Proc. Third International
Conference on Image and Graphics (ICIG), pp.184-187.
[29]. Turk, M.A., and Pentland, A.P. (1991). “Face
recognition using eigenfaces”. In Computer Vision and
Pattern Recognition, 1991. Proceedings CVPR'91., IEEE
Computer Society Conference, pp.586-591.LNCS 3021,
pp.469-481.
