FACE RECOGNITION FROM SKETCHES USING ADVANCED CORRELATION FILTERS USING HYBRID EIGENANALYSIS FOR FACE SYNTHESIS

Yung-hui Li, Marios Savvides, Vijayakumar Bhagavatula

Abstract

Most face recognition systems focus on photo-based (or video) face recognition, but there are many law-enforcement applications where a police sketch artist composes a face sketch of the criminal and that is used by the officers to look for the criminal. Currently state-of-the-art research approach transforms all test face images into sketches then perform recognition in the sketch domain using the sketch composite, however there is one flaw in such approach which hinders it from being deployed fully automatic in the field, due to the fact that generating a sketch image from a surveillance footage will vary greatly due to illumination variations of the face in the footage under different lighting conditions. This will result imprecise sketches for real time recognition. In our approach we propose the opposite which is a better approach; we propose to generate a realistic face image from the composite sketch using a Hybrid subspace method and then build an illumination tolerant correlation filter which can recognize the person under different illumination variations. We show experimental results on our approach on the CMU PIE (Pose Illumination and Expression) database on the effectiveness of our novel approach.

References

  1. W. Zhao, R. Chellappa, A. Rosenfeld and P. J. Phillips, “Face Recognition: A Literature Survey”, CS-Tech Report-4167, University of Maryland, 2000.
  2. X. Tang and X. Wang, “Face Photo Recognition Using Sketch”, Proc. of Int. Conf. Image Processing, 2002.
  3. X. Tang and X. Wang, “Face Sketch Recognition”, IEEE Trans. on Circuit System and Video Technology, Vol.14, pp.50-57, 2004.
  4. X. Tang and X. Wang, “Face Sketch Synthesis and Recognition”, Proc. of Int. Conf. Computer Vision, 2003.
  5. Q. Liu, X. Tang, H, Jin, H. Lu, and S. Ma, “A Nonlinear Approach for Face Sketch Synthesis and Recognition”, Proc. Of. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005.
  6. M.A. Turk and A. P. Pentland, “Face recognition using eigenfaces”, presented at Computer Vision and Pattern Recognition, 1991. Proceeding CVPR 7891., IEEE Computer Society Conference on, 1991.
  7. B.V.K. Vijaya Kumar, “Tutorial Survey of Composite Filter designs for Optical Correlators,” Applied Optics, vol. 31, pp. 4773-4801, 1992
  8. A. Mahalanobis, B.V.K. Vijaya Kumar, and D. Casasent, “Minimum average correlation energy filters,” Applied Optics, vol. 26:3633-3640, 1987.
  9. A. Mahalanobis, B.V.K. Vijaya Kumar, S. Song, S.R.F. Sims, and J.F. Epperson, “Unconstrained correlation filters,” Applied Optics, vol. 33:3751-3759, 1994.
  10. B. V. K. V. Kumar, D. Carlson, and A. Mahalanobis, “Optimal tradeoff synthetic discriminant function (OTSDF) filters for arbitrary devices,” Opt. Lett., vol. 19, pp. 1556-1558, 1994.
  11. P. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi, "The FERET evaluation methodology for face recognition algorithms", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, October 2000.
  12. P. J. Phillips, P. J. Rauss, and S. Z. Der, " FERET (Face Recognition Technology) Recognition Algorithm Development and Test Results", October 1996. Army Research Lab technical report 995.
  13. P. J. Phillips, “Face Recognition Grand Challenge”, presented at Biometric Consortium Conference, 2004
  14. T. Sim, S. Baker, and M. Bsat “The CMU Pose, Illumination, and Expression (PIE) Database of Human faces,” Tech. Report CMU-RI-TR-01-02, Robotics Institute, Carnegie Mellon University, January (2001)
  15. M. Savvides, B.V.K. Vijaya Kumar and P.K. Khosla, "Robust, Shift-Invariant Biometric Identification from Partial Face Images", Biometric Technologies for Human Identification (OR51) 2004.
  16. M. Savvides, B.V.K. Vijaya Kumar and P.K. Khosla, “Face verification using correlation filters”, Proc. Of the Third IEEE Automatic Identification Advanced Technologies, 56-61, Tarrytown, NY, March 2002.
  17. M. Savvides, C.Xie, N. Chu, B.V.K.Vijaya Kumar, C. Podilchuk, A. Patel, A. Harthattu, R. Mammone, “Robust Face Recognition using Advanced Correlation Filters with Bijective-Mapping Preprocessing”, Audio-Video Based Biometric Person Authentication (AVBPA), July 2005.
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Paper Citation


in Harvard Style

Li Y., Savvides M. and Bhagavatula V. (2006). FACE RECOGNITION FROM SKETCHES USING ADVANCED CORRELATION FILTERS USING HYBRID EIGENANALYSIS FOR FACE SYNTHESIS . In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 5: ICEIS, ISBN 978-972-8865-45-0, pages 11-18. DOI: 10.5220/0002457400110018


in Bibtex Style

@conference{iceis06,
author={Yung-hui Li and Marios Savvides and Vijayakumar Bhagavatula},
title={FACE RECOGNITION FROM SKETCHES USING ADVANCED CORRELATION FILTERS USING HYBRID EIGENANALYSIS FOR FACE SYNTHESIS},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 5: ICEIS,},
year={2006},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002457400110018},
isbn={978-972-8865-45-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 5: ICEIS,
TI - FACE RECOGNITION FROM SKETCHES USING ADVANCED CORRELATION FILTERS USING HYBRID EIGENANALYSIS FOR FACE SYNTHESIS
SN - 978-972-8865-45-0
AU - Li Y.
AU - Savvides M.
AU - Bhagavatula V.
PY - 2006
SP - 11
EP - 18
DO - 10.5220/0002457400110018