FACE IDENTIFICATION ALGORITHM BASED ON MESH-DERIVED SYNTHETIC LINEAR DESCRIPTORS
DOI:
https://doi.org/10.47839/ijc.4.3.361Keywords:
Appearance-based approach, face recognition, synthetic linear descriptors, discriminant functionAbstract
This paper presents appearance-based face identification algorithm by means of synthetic linear filters. The objective of our research is to construct facial descriptor in the form of linear filter, which should produce high and low outputs for intra- and inter-class recognition problem correspondingly. This filter can be synthesized from 2,5D sparse mesh derived from a given set of images of a person. As ever the filter is created it is then used as facial descriptor, i.e. serves as personal ID for face identification.References
R. Chellappa, C.L. Wilson, S. Sirohey. Human and machine recognition of faces: A survey, Proc. IEEE, 5 (83) (1995), pp. 705-740.
W.Y. Zhao, R. Chellappa, A. Rosenfeld, and P.J. Phillips,"Face recognition: A literature survey", UMD CfAR Technical Report CAR-TR-948, 2000
P. J. Phillips, H. Moon, D.M. Blackburn, E. Tabassi, and J.M. Bone. The FERET evaluation methodology for face recognition algorithms, IEEE Trans. on PAMI, 22 (10) (2000), pp.1090-1104.
P. J. Phillips, P. Grother, R.J. Micheals, D.M. Blackburn, E. Tabassi, and J.M. Bone. FRVT 2002: Evaluation Report, March 2003.
T. Papatheodorou, D. Rueckert. Evaluation of automatic 4D face recognition using surface and texture registration. Proc. of the Sixth IEEE International Conference on Face and gesture Recognition, FG'2004, Seoul, Korea 17-19 May 2004, pp.321-326.
M. Turk, A. Pentland. Eigenfaces for recognition, Jour. Cognitive Neuroscience, 1 (3) 1991.
P. Belhumeur, J. Hespanha, D. Kriegman. Eigenfaces vs. fisherfaces: recognition using class specific linear projection, IEEE Trans. on Pattern Recognition and Machine Intelligence, 7 (19) 1997, pp. 711-720.
C. Liu, H. Wechsler. Comparative assessment of independent component analysis, Proc. the 2nd Int. Conf. Audio- and Video-based Biometric Person Authentication, Washington D.C., 22-24 March 1999.
D. Dai, P. Yuen. Regularized discriminant analysis and its application to face recognition, Pattern Recognition, (36) (2003), pp. 845-847.
K. Etemad, R. Chellappa. Discriminant analysis for recognition of human face images, J. Opt. Soc. Am. A, (14) (1997), pp. 1724-1733.
M. Skurichina, R. Duin. Bagging, boosting and the random subspace method for linear classifiers, Pattern Analysis and Applications, 2 (5) (2002), pp. 121-135.
L. Breiman. Bagging predictors, Machine Learning, 24 (2) (1996), pp. 123-140.
T. Ho. The random subspace method for constructing decision forests, IEEE Trans. Pattern Analysis and Machine Intelligence, 8 (20) (1998), pp. 832-844.
D. Casasent. Unified synthetic discriminant function computational formulation, Appl. Opt., 23 (10) (1984), pp. 1620-1627.
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