An a-contrario Approach for Face Matching

Luis D. Di Martino, Javier Preciozzi, Federico Lecumberry, Alicia Fernández

2014

Abstract

In this work we focus on the matching stage of a face recognition system. These systems are used to identify an unknown person or to validate a claimed identity. In the face recognition field it is very common to innovate in the extracted features of a face and use a simple threshold on the distance between samples in order to perform the validation of a claimed identity. In this work we present a novel strategy based in the a-contrario framework in order to improve the matching stage. This approach results in a validation threshold that is automatically adapted to the data and allows to predict the performance of the system in advance. We perform several experiments in order to validate this novel strategy using different databases and show its advantages over using a simple threshold over the distances.

References

  1. Ahonen, T., Hadid, A., and Pietikäinen, M. (2006). Face description with local binary patterns: application to face recognition. IEEE transactions on pattern analysis and machine intelligence, 28(12):2037-41.
  2. Desolneux, a., Moisan, L., and Morel, J. (2003a). A grouping principle and four applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(4):508-513.
  3. Desolneux, A., Moisan, L., and Morel, J. (2003b). Maximal meaningful events and applications to image analysis. The Annals of Statistics, 31(6):1822-1851.
  4. Gioi, R. V. and Jakubowicz, J. (2010). LSD: A fast line segment detector with a false detection control. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 32:722-732.
  5. Huang, D., Shan, C., Ardabilian, M., Yunhong, W., and Liming, C. (2011). Local Binary Patterns and Its Application to Facial Image Analysis: A Survey. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 41(6):765-781.
  6. Kan, M., Xu, D., Shan, S., Li, W., and Chen, X. (2013). Learning Prototype Hyperplanes for Face Verification in the Wild. Image Processing, IEEE Transactions on, 22:3310-3316.
  7. Lanitis, A., Taylor, C., and Cootes, T. (2002). Toward automatic simulation of aging effects on face images. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(4):442-455.
  8. Ling, H. and Soatto, S. (2010). Face verification across age progression using discriminative methods. Information Forensics and Security, IEEE Transactions on, 5(1):82-91.
  9. Marsico, M. D., Nappi, M., Riccio, D., and Wechsler, H. (2013). Robust Face Recognition for Uncontrolled Pose and Illumination Changes. IEEE Transactions on Systems, Man, and Cybernetics, 43(1):149-163.
  10. Masi, I., Lisanti, G., Bagdanov, A., Pala, P., and Bimbo, A. D. (2013). Using 3D Models to Recognize 2D Faces in the Wild. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on, pages 775-780.
  11. Milborrow, S. and Nicolls, F. (2008). Locating facial features with an extended active shape model. Computer VisionECCV 2008, pages 504 - 513.
  12. Mottalli, M., Tepper, M., and Mejail, M. (2010). A contrario detection of false matches in iris recognition, volume 6419. Springer Berlin Heidelberg.
  13. Musé, P., Sur, F., Cao, F., Gousseau, Y., and Morel, J.-M. (2006). An A Contrario Decision Method for Shape Element Recognition. International Journal of Computer Vision, 69(3):295-315.
  14. Park, U., Tong, Y., and Jain, A. K. (2010). Age-invariant face recognition. IEEE transactions on pattern analysis and machine intelligence, 32(5):947-54.
  15. Phillips, P. J., Wechsler, H., Huang, J., and Rauss, P. J. (1998). The FERET database and evaluation procedure for face-recognition algorithms. Image and Vision Computing, 16(5):295-306.
  16. Rabin, J., Delon, J., and Gousseau, Y. (2008). A contrario matching of SIFT-like descriptors. 2008 19th International Conference on Pattern Recognition, pages 1-4.
  17. Zhang, B., Gao, Y., Zhao, S., and Liu, J. (2010). Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 19(2):533-44.
  18. Zhang, B., Shan, S., Chen, X., and Gao, W. (2007). Histogram of Gabor phase patterns (HGPP): a novel object representation approach for face recognition. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 16(1):57- 68.
  19. Zhang, W., Shan, S., Gao, W., Chen, X., and Zhang, H. (2005). Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition. Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pages 786-791 Vol. 1.
  20. Zhu, X. and Ramanan, D. (2012). Face detection, pose estimation, and landmark localization in the wild. Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, pages 2879-2886.
Download


Paper Citation


in Harvard Style

D. Di Martino L., Preciozzi J., Lecumberry F. and Fernández A. (2014). An a-contrario Approach for Face Matching . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 377-384. DOI: 10.5220/0004758003770384


in Bibtex Style

@conference{icpram14,
author={Luis D. Di Martino and Javier Preciozzi and Federico Lecumberry and Alicia Fernández},
title={An a-contrario Approach for Face Matching},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={377-384},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004758003770384},
isbn={978-989-758-018-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - An a-contrario Approach for Face Matching
SN - 978-989-758-018-5
AU - D. Di Martino L.
AU - Preciozzi J.
AU - Lecumberry F.
AU - Fernández A.
PY - 2014
SP - 377
EP - 384
DO - 10.5220/0004758003770384