Confidence-based Rank-level Fusion for Audio-visual Person Identification System

Mohammad Rafiqul Alam, Mohammed Bennamoun, Roberto Togneri, Ferdous Sohel

Abstract

A multibiometric identification system establishes the identity of a person based on the biometric data presented to its sub-systems. Each sub-system compares the features extracted from the input against the templates of all identities stored in its gallery. In rank-level fusion, ranked lists from different sub-systems are combined to reach the final decision about an identity. However, the state-of-art rank-level fusion methods consider that all sub-systems perform equally well in any conditions. In practice, the probe data may be affected by different degradations (e.g., illumination and pose variation on the face image, environmental noise etc.) and thus affect the overall recognition accuracy. In this paper, robust confidence-based rank-level fusion methods are proposed by using confidence measures for all participating sub-systems. Experimental results show that the confidence-based approach of rank-level fusion achieves higher recognition rates than the state-of-art.

References

  1. Abaza, A. and Ross, A. (2009). Quality based rank-level fusion in multibiometric systems. In Biometrics: Theory, Applications, and Systems, 2009. BTAS'09. IEEE 3rd International Conference on, pages 1-6. IEEE.
  2. Alam, M. R., Bennamoun, M., Togneri, R., and Sohel, F. (2013a). An efficient reliability estimation technique for audio-visual person identification. In Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on, pages 1631-1635. IEEE.
  3. Alam, M. R., Togneri, R., Sohel, F., Bennamoun, M., and Naseem, I. (2013b). Linear regression-based classifier for audio visual person identification. In Communications, Signal Processing, and their Applications (ICCSPA), 2013 1st International Conference on, pages 1- 5. IEEE.
  4. Basak, J., Kate, K., Tyagi, V., and Ratha, N. (2010). A gradient descent approach for multi-modal biometric identification. In Pattern Recognition (ICPR), 2010 20th International Conference on, pages 1322-1325. IEEE.
  5. Burnham, D., Estival, D., Fazio, S., Viethen, J., Cox, F., Dale, R., Cassidy, S., Epps, J., Togneri, R., Wagner, M., et al. (2011). Building an audio-visual corpus of australian english: large corpus collection with an economical portable and replicable black box. In Twelfth Annual Conference of the International Speech Communication Association.
  6. Castrill'on-Santana, M., D'eniz-Su'arez, O., Ant'onCanal'is, L., and Lorenzo-Navarro, J. (2008). Face and facial feature detection evaluation performance evaluation of public domain haar detectors for face and facial feature detection.
  7. Chetty, G. and Wagner, M. (2008). Robust face-voice based speaker identity verification using multilevel fusion. Image and Vision Computing, 26(9):1249-1260.
  8. Fakhar, K., El Aroussi, M., Saidi, M. N., and Aboutajdine, D. (2012). Score fusion in multibiometric identification based on fuzzy set theory. In Image and Signal Processing, pages 261-268. Springer.
  9. Fishburn, P. (1990). A note on a note on nanson's rule. Public Choice, 64(1):101-102.
  10. Ho, T. K., Hull, J. J., and Srihari, S. N. (1994). Decision combination in multiple classifier systems. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 16(1):66-75.
  11. Kumar, A. and Shekhar, S. (2011). Personal identification using multibiometrics rank-level fusion. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 41(5):743-752.
  12. Marasco, E., Ross, A., and Sansone, C. (2010). Predicting identification errors in a multibiometric system based on ranks and scores. In Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, pages 1-6. IEEE.
  13. Marasco, E. and Sansone, C. (2011). An experimental comparison of different methods for combining biometric identification systems. In Image Analysis and Processing-ICIAP 2011, pages 255-264. Springer.
  14. Monwar, M. M. and Gavrilova, M. L. (2009). Multimodal biometric system using rank-level fusion approach. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 39(4):867-878.
  15. Murakami, T. and Takahashi, K. (2009). Accuracy improvement with high convenience in biometric identification using multihypothesis sequential probability ratio test. In Information Forensics and Security, 2009. WIFS 2009. First IEEE International Workshop on, pages 66-70. IEEE.
  16. Murakami, T. and Takahashi, K. (2011). Fast and accurate biometric identification using score level indexing and fusion. In Biometrics (IJCB), 2011 International Joint Conference on, pages 1-8. IEEE.
  17. Nakamura, J. (2005). Image sensors and signal processing for digital still cameras. CRC Press.
  18. Nandakumar, K., Jain, A. K., and Ross, A. (2009). Fusion in multibiometric identification systems: What about the missing data? In Advances in Biometrics, pages 743-752. Springer.
  19. Naseem, I., Togneri, R., and Bennamoun, M. (2010). Linear regression for face recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 32(11):2106-2112.
  20. Naseem, I., Togneri, R., and Bennamoun, M. (2012). Robust regression for face recognition. Pattern Recognition, 45(1):104-118.
  21. Ross, A., Nandakumar, K., and Jain, A. (2006). Handbook of multibiometrics, volume 6. Springer.
  22. Saranli, A. and Demirekler, M. (2001). A statistical unified framework for rank-based multiple classifier decision combination. Pattern Recognition, 34(4):865-884.
  23. Togneri, R. and Pullella, D. (2011). An overview of speaker identification: Accuracy and robustness issues. Circuits and Systems Magazine, IEEE, 11(2):23-61.
Download


Paper Citation


in Harvard Style

Rafiqul Alam M., Bennamoun M., Togneri R. and Sohel F. (2014). Confidence-based Rank-level Fusion for Audio-visual Person Identification System . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 608-615. DOI: 10.5220/0004819806080615


in Bibtex Style

@conference{icpram14,
author={Mohammad Rafiqul Alam and Mohammed Bennamoun and Roberto Togneri and Ferdous Sohel},
title={Confidence-based Rank-level Fusion for Audio-visual Person Identification System},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={608-615},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004819806080615},
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 - Confidence-based Rank-level Fusion for Audio-visual Person Identification System
SN - 978-989-758-018-5
AU - Rafiqul Alam M.
AU - Bennamoun M.
AU - Togneri R.
AU - Sohel F.
PY - 2014
SP - 608
EP - 615
DO - 10.5220/0004819806080615