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Temporal analysis of adaptive face recognition

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Aging has profound effects on facial biometrics as it causes change in shape and texture. However, aging remains an under-studied problem in comparison to facial variations due to pose, illumination and expression changes. A commonly adopted solution in the state-of-the-art is the virtual template synthesis for aging and de-aging transformations involving complex 3D modelling techniques. These methods are also prone to estimation errors in the synthesis. Another viable solution is to continuously adapt the template to the temporal variation (ageing) of the query data. Though efficacy of template update procedures has been proven for expression, lightning and pose variations, the use of template update for facial aging has not received much attention so far. Therefore, this paper first analyzes the performance of existing baseline facial representations, based on local features, under ageing effect then investigates the use of template update procedures for temporal variance due to the facial age progression process. Experimental results on FGNET and MORPH aging database using commercial VeriLook face recognition engine demonstrate that continuous template updating is an effective and simple way to adapt to variations due to the aging process.
Rocznik
Strony
43--255
Opis fizyczny
Bibliogr. 42 poz., rys.
Twórcy
autor
  • Dept. of Mathematics and Computer Science, University of Udine, Italy
autor
  • Dept. of Computer Science and Electrical Engineering, University of Missouri at Kansas City, USA
  • Dept. of Mathematics and Computer Science, University of Udine, Italy
Bibliografia
  • [1] Zahid Akhtar, Security of Multimodal Biometric Systems against Spoof Attacks, PhD thesis, University of Cagliari, Italy, 2012.
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  • [5] Z. Akhtar and N. Alfarid, Secure Learning Algorithm for Multimodal Biometric Systems against Spoof Attacks, Proc. Int’l Conference on Information and Network Technology (ICINT), pp. 52-57, 2011.
  • [6] Z. Akhtar, C. Micheloni and G. L. Foresti, Biometric Liveness Detection: Challenges and Open Research Opportunities, IEEE Security & Privacy, 2015.
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  • [9] Z. Akhtar, A. Rattani, A. Hadid and M. Tistarelli, Face Recognition under Ageing Effect: A Comparative Analysis, Proc. Int’l Conf. on Image Analysis and Processing (ICIAP), pp. 309-318, 2013.
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  • [12] A. Rattani, B. Freni, G. L. Marcialis and F. Roli, Template Update Methods in Adaptive Biometric Systems: A Critical Review, Proc. International Conference on Biometrics (ICB), pp. 847-857, 2009.
  • [13] Z. Akhtar, A. Ahmed, C. E. Erdem and G. L. Foresti, Biometric Template Update under Facial Aging, IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, 2014.
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  • [16] N. Ramanathan and R. Chellappa, Modeling age progression in young faces, Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), pp. 387-394, 2006.
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  • [18] FGNET Aging Database, http://www.fgnet.rsunit.com/
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  • [20] N. Nixon and P. Galassi, The brown sisters, thirtythree years, In The Museum of Modern Art, NY, USA, 2007.
  • [21] A. Rattani. Adaptive Biometric System based on Template Update Procedures, PhD thesis, University of Cagliari, Italy, 2010.
  • [22] N. Poh, A. Rattani and F. Roli, Critical Analysis of Adaptive Biometric Systems, IET Biometrics, 1(4):179-187, 2012.
  • [23] A. Rattani and A. Ross, Automatic Adaptation of Fingerprint Liveness Detector to New Spoof Materials, In Proc. IEEE International Joint Conference on Biometrics (IJCB), 2014.
  • [24] X. Liu, T. Chen, and S. M. Thornton, Eigenspace updating for non-stationary process and its application to face recognition, Pattern Recognition, pp. 1945-1959, 2003.
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  • [32] F. Roli and G.L Marcialis, Semi-supervised pcabased face recognition using self training, Proc. Int’l workshop on S+SSPR, 2006.
  • [33] Verilook: http://www.neurotechnology.com/
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  • [37] X. Tan and B. Triggs, Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions, IEEE Trans. on Image Processing, vol. 19, no. 6, pp. 1635-1650, 2010.
  • [38] L. Wiskott, J.M. Fellous, N. Kruger and C. Malsburg, Face recognition by elastic bunch graph matching, IEEE Trans. on PAMI, vol. 19, no. 7, pp. 775-780, 1997.
  • [39] D. R. Kisku, A. Rattani, E. Grosso and M. Tistarelli, Face Identification by SIFT-based Complete Graph Topology, In Proc. of 5th IEEE Int’l Workshop on Automatic Identification Advanced Technologies, pp. 63-68, 2007.
  • [40] P. Dreuw, P. Steingrube and H. Hanselmann and H. Ney, SURF-Face: Face Recognition Under Viewpoint Consistency Constraints, In Proc. BMVC, pp. 1-11, 2009.
  • [41] A. Rattani, G. L. Marcialis, F. Roli, An Experimental Analysis of the Relationship between Biometric Template Update and the Doddington’s Zoo in Face Verification, In Proc. of 14th Int’l Conference on Image Analysis and Processing, 2009.
  • [42] Z. Akhtar, G. Fumera, G. L. Marcialis and F. Roli, Evaluation of Multimodal Biometric Score Fusion Rules under Spoof Attacks, 5th IAPR Int’l Conference on Biometrics (ICB), pp. 402-407, 2012
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4cd19dc7-e6d5-458f-a640-9e3d919a15fd
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