A Composed Confidence Measure for Automatic Face Recognition in Uncontrolled Environment

Pavel Král, Ladislav Lenc

Abstract

This paper is focused on automatic face recognition in order to annotate people in photographs taken in completely uncontrolled environment. Recognition accuracy of the current approaches is not sufficient in this case and it is thus beneficial to improve the results. We would like to solve this issue by proposing a novel confidence measure method to identify the incorrectly classified examples at the output of our classifier. The proposed approach combines two measures based on the posterior probability and two ones based on the predictor features in a supervised way. The experiments show that the proposed approach is very efficient, because it detects almost all erroneous examples.

References

  1. Aly, M. (2006). Face recognition using sift features.
  2. Bartlett, M. S., Movellan, J. R., and Sejnowski, T. J. (2002). Face recognition by independent component analysis. IEEE Transactions on Neural Networks, pages 1450- 1464.
  3. Beham, M. P. and Roomi, S. M. M. (2013). A review of face recognition methods. International Journal of Pattern Recognition and Artificial Intelligence, 27(4).
  4. Belhumeur, P. N., Hespanha, J. a. P., and Kriegman, D. J. (1997). Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence.
  5. Bolme, D. S. (2003). Elastic Bunch Graph Matching. PhD thesis, Colorado State University.
  6. Brown, C. D. and Davis, H. T. (2006). Receiver operating characteristics curves and related decision measures: A tutorial. Chemometrics and Intelligent Laboratory Systems, 80(1):24-38.
  7. Deng, J. and Schuller, B. (2012). Confidence measures in speech emotion recognition based on semi-supervised learning. In INTERSPEECH.
  8. Eickeler, S., Jabs, M., and Rigoll, G. (2000). Comparison of confidence measures for face recognition. In FG, pages 257-263. IEEE Computer Society.
  9. Hu, X. and Mordohai, P. (2012). A quantitative evaluation of confidence measures for stereo vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11):2121-2133.
  10. Jiang, H. (2005). Confidence measures for speech recognition: a survey. Speech Communication, 45(4):455- 470.
  11. Kepenekci, B. (2001). Wavelet Transform. Technical University.
  12. Krizaj, J., Struc, V., and Pavesic, N. (2010). Adaptation of sift features for robust face recognition.
  13. Lenc, L. and Král, P. (2011). Confidence measure for automatic face recognition. In International Conference on Knowledge Discovery and Information Retrieval, Paris, France.
  14. Lenc, L. and Král, P. (2012). Novel matching methods for automatic face recognition using SIFT. In 8th AIAI (Artificial Intelligence Applications and Innovations) Confence, Halkidiki, Greece.
  15. Lenc, L. and Král, P. (2013). Face recognition under realworld conditions. In International Conference on Agents and Artificial Intelligence, Barcelona, Spain.
  16. Li, F. and Wechsler, H. (2003). Open world face recognition with credibility and confidence measures. In Audio-and Video-Based Biometric Person Authentication, pages 462-469. Springer.
  17. Marukatat, S., Artières, T., Gallinari, P., and Dorizzi, B. (2002). Rejection measures for handwriting sentence recognition. In Frontiers in Handwriting Recognition, 2002. Proceedings. Eighth International Workshop on, pages 24-29. IEEE.
  18. Poon, B., Amin, M. A., and Yan, H. (2011). Performance evaluation and comparison of pca based human face recognition methods for distorted images. International Journal of Machine Learning and Cybernetics, 2(4):245-259.
  19. Powers, D. (2011). Evaluation: From precision, recall and f-measure to roc., informedness, markedness & correlation. Journal of Machine Learning Technologies, 2(1):37-63.
  20. Proedrou, K., Nouretdinov, I., Vovk, V., and Gammerman, A. (2002). Transductive confidence machines for pattern recognition. In ECML'02, pages 381-390.
  21. Senay, G., Linares, G., and Lecouteux, B. (2011). A segment-level confidence measure for spoken document retrieval. In Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, pages 5548-5551. IEEE.
  22. Servin, B., de Givry, S., and Faraut, T. (2010). Statistical confidence measures for genome maps: application to the validation of genome assemblies. Bioinformatics, 26(24):3035-3042.
  23. Shen, L. (2005). Recognizing Faces - An Approach Based on Gabor Wavelets. PhD thesis, University of Nottingham.
  24. Shen, L. and Bai, L. (2006). A review on gabor wavelets for face recognition. Pattern Analysis & Applications.
  25. Sukkar, R. A. (1994). Rejection for connected digit recognition based on gpd segmental discrimination. In Acoustics, Speech, and Signal Processing, 1994. ICASSP94., 1994 IEEE International Conference on, volume 1, pages I-393. IEEE.
  26. Turk, M. A. and Pentland, A. P. (1991). Face recognition using eigenfaces. In IEEE Computer Society Conference on In Computer Vision and Pattern Recognition. Computer Vision and Pattern Recognition.
  27. Wessel, F., Schluter, R., Macherey, K., and Ney, H. (2001). Confidence measures for large vocabulary continuous speech recognition. Speech and Audio Processing, IEEE Transactions on, 9(3):288-298.
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Paper Citation


in Harvard Style

Král P. and Lenc L. (2014). A Composed Confidence Measure for Automatic Face Recognition in Uncontrolled Environment . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-015-4, pages 230-237. DOI: 10.5220/0004926202300237


in Bibtex Style

@conference{icaart14,
author={Pavel Král and Ladislav Lenc},
title={A Composed Confidence Measure for Automatic Face Recognition in Uncontrolled Environment},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2014},
pages={230-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004926202300237},
isbn={978-989-758-015-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A Composed Confidence Measure for Automatic Face Recognition in Uncontrolled Environment
SN - 978-989-758-015-4
AU - Král P.
AU - Lenc L.
PY - 2014
SP - 230
EP - 237
DO - 10.5220/0004926202300237