Skip to main content
SpringerLink
Log in
Book cover

Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions pp 291–305Cite as

Behavioral Consistency Extraction for Face Verification

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5641))

Abstract

In this paper we investigate how the use of computational statistical models, derived from moving images, can take part in the face recognition process. As a counterpart to psychological experimental results showing a significant beneficial effect of facial non-rigid movement, two features obtained from face sequences, the central tendency and type of movement variation, are associated to improve face verification compared with single static images. By using General Group-wise Registration algorithm, the correspondences across the sequences are captured to build a combined shape and appearance model, parameterizing the face sequences. The parameters are projected to an identity-only space to find the central tendency of each subject. In addition, facial movement consistencies across different behaviors exhibited by the same subjects are recorded. These two features are fused by a confidence-based decision system for authentication applications. Using the BANCA video database, the results show that the extra information extracted from moving images significantly and efficiently improves performance.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Turk, M., Pentland, A.: Face recognition using eigenfaces. In: Computer Vision and Pattern Recognition Conference, pp. 586–591 (1991)

    Google Scholar 

  2. Wiskott, L., Fellous, J.M., Knueuger, N., Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Transations on Pattern Analysis and Machine Intelligence 19(7), 775–779 (1997)

    Article  Google Scholar 

  3. Bartlett, M., Movellan, J., Sejnowski, T.: Face recognition by independent component analysis. IEEE Transations on Neural Networks 13(6), 1450–1464 (2002)

    Article  Google Scholar 

  4. Lu, J., Plataniotis, K., Venetsanopoulos, A.: Face recognition using kernel direct discriminant analysis algorithms. IEEE Transations on Neural Networks 14(1), 117–126 (2003)

    Article  Google Scholar 

  5. Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Transations on Pattern Analysis and Machine Intelligence 19, 711–720 (1997)

    Article  Google Scholar 

  6. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Transations on Pattern Analysis and Machine Intelligence 23(6), 681–685 (2001)

    Article  Google Scholar 

  7. Phillips, P., Moon, H., Rizvi, S., Rauss, P.: The feret evaluation methodology for face recognition algorithms. IEEE Transations on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)

    Article  Google Scholar 

  8. Phillips, P., Flynn, P., Scruggs, T., Bowyer, K., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the face recognition grand challenge. In: Computer Vision and Pattern Recognition Conference, pp. 947–954 (2005)

    Google Scholar 

  9. Bailly-Bailliere, E., Bengio, S., Bimbot, F., et al.: The banca database and evaluation protocol. In: International Conference on Audio- and Video-Based Biometric Person Authentication, pp. 625–638 (2003)

    Google Scholar 

  10. Jenkins, R., Burton, A.M.: 100% accuracy in automatic face recognition. Science 319(5862), 435 (2008)

    Article  Google Scholar 

  11. O’Toole, A., Roark, D., Abdi, H.: Recognizing moving faces: A psychological and neural synthesis. Trends in Cognitive Sciences 6(6), 261–266 (2002)

    Article  Google Scholar 

  12. Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. International Journal of Computer Vision 9(2), 137–154 (1992)

    Article  Google Scholar 

  13. Torresani, L., Hertzmann, A., Bregler, C.: Learning non-rigid 3D shape from 2D motion. In: Neural Information Processing Systems, pp. 1555–1562 (2003)

    Google Scholar 

  14. Xiao, J., Chai, J.X., Kanade, T.: A closed-form solution to non-rigid shape and motion recovery. International Journal of Computer Vision 67(2), 233–246 (2006)

    Article  MATH  Google Scholar 

  15. Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE Transations on Pattern Analysis and Machine Intelligence 25(9), 1–12 (2003)

    Article  Google Scholar 

  16. Craw, I.G., Costen, N.P., Kato, T.: How should we represent face for automatic recognition? IEEE Transactions on Pattern Analysis and machine Inteligence 21(8), 725–736 (1999)

    Article  Google Scholar 

  17. Lander, K., Chuang, L.: Why are moving faces easier to recognize? Visual Cognition 23(3), 429–442 (2005)

    Article  Google Scholar 

  18. Zhou, S., Krueger, V., Chellappa, R.: Probabilistic recognition of human faces from video. Computer Vision and Image Understanding 91, 214–245 (2003)

    Article  Google Scholar 

  19. Benedikt, L., Kajic, V., Cosker, D., Rosin, P.L., Marshall, D.: Facial dynamics in biomedtric identification. In: British Machine Vision Conference, pp. 1065–1075 (2008)

    Google Scholar 

  20. Liu, X., Chen, T.: Video-based face recognition using adaptive hidden markov models. In: Computer Vision and Pattern Recognition Conference, pp. 26–33 (2003)

    Google Scholar 

  21. Bettinger, F., Cootes, T., Taylor, C.: Modelling facial behaviours. In: British Machine Vision Conference, pp. 797–806 (2002)

    Google Scholar 

  22. Edwards, G., Taylor, C., Cootes, T.: Improving identification performance by integrating evidence from sequences. In: Computer Vision and Pattern Recognition Conference, pp. 1486–1491 (1999)

    Google Scholar 

  23. Yamaguchi, O., Fukui, K., Maeda, K.: Face recognition using temporal sequence. In: IEEE International Conference on Automatic Face and Gesture Recognition, vol. 10, pp. 318–323 (1998)

    Google Scholar 

  24. Arandjelović, O., Cipolla, R.: An information-theoretic approach to face recognition from face motion manifolds. Image and Vision Computing 24, 639–647 (2006)

    Article  Google Scholar 

  25. Knappmeyer, B., Thornton, I.M., Bülthoff, H.H.: The use of facial motion and facial form during the processing of identity. Vision Research 43, 1921–1936 (2003)

    Article  Google Scholar 

  26. Baker, S., Matthews, I., Schneider, J.: Automatic construction of active appearance models as an image coding problem. IEEE Transations on Pattern Analysis and Machine Intelligence 26(10), 1380–1384 (2004)

    Article  Google Scholar 

  27. Cootes, T.F., Marsland, S., Twining, C.J., Smith, K., Taylor, C.J.: Groupwise diffeomorphic non-rigid registration for automatic model building. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 316–327. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  28. Cootes, T.F., Twining, C.J., Petrovic, V., Schestowitz, R., Taylor, C.J.: Groupwise construction of appearance model using piece-wise affine deformations. In: British Machine Vision Conference, pp. 879–888 (2005)

    Google Scholar 

  29. Fang, H., Costen, N.P.: Tracking face localization with a hierarchical progressive face model. In: Gonzàliz, J., Moeslund, T.B., Wang, L. (eds.) Tracking Humans for the Evaluation of their Motion in Image Sequences, pp. 89–99 (2008)

    Google Scholar 

  30. Edwards, G.J., Lanitis, A., Taylor, C., Cootes, T.F.: Modelling the variability in face images. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 328–333 (1996)

    Google Scholar 

  31. Poh, N., Bengio, S.: Improving fusion with margin-derived confidence in biometric authentication tasks. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 474–483. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  32. Hanley, J.A., McNeil, B.J.: A method for comparing the areas under Receiver Operating Characteristic curves derived from the same cases. Radiology 148, 839–843 (1983)

    Article  Google Scholar 

  33. Hill, H., Johnston, A.: Categorizing sex and identity from the biological motion of faces. Current Biology 11, 880–885 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, U.K.

    Hui Fang & Nicholas Costen

Authors
  1. Hui Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nicholas Costen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Psychology, Second University of Naples, and IIASS, Via G. Pellegrino 19, 84019, Vietri sul Mare, (SA), Italy

    Anna Esposito

  2. Institute of Photonics and Electronics, Academy of Sciences of the Czech Republic, Chaberská 57, 182 52, Prague 8, Czech Republic

    Robert Vích

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fang, H., Costen, N. (2009). Behavioral Consistency Extraction for Face Verification. In: Esposito, A., Vích, R. (eds) Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions. Lecture Notes in Computer Science(), vol 5641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03320-9_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03320-9_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03319-3

  • Online ISBN: 978-3-642-03320-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation