Abstract

We propose an algorithm for face verification through tracking facial features by using sequential importance sampling. Specifically, we first formulate tracking as a Bayesian inference problem and propose to use Markov chain Monte Carlo techniques for obtaining an empirical solution. A reparameterization is introduced under parametric motion assumption, which facilitates the empirical estimation and also allows verification to be addressed along with tracking. The facial features to be tracked are defined on a grid with Gabor attributes (jets). The motion of facial feature points is modeled as a global two-dimensional (2-D) affine transformation (accounting for head motion) plus a local deformation (accounting for residual motion that is due to inaccuracies in 2-D affine modeling and other factors such as facial expression). Motion of both types is processed simultaneously by the tracker: The global motion is estimated by importance sampling, and the residual motion is handled by incorporating local deformation into the measurement likelihood in computing the weight of a sample. Experiments with a real database of face image sequences are presented.

© 2001 Optical Society of America

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  1. M. Turk, A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 72–86 (1991).
    [CrossRef]
  2. A. J. Howell, H. Buxton, “Towards unconstrained face recognition from image sequences,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1996), pp. 224–229.
  3. H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.
  4. S. J. McKenna, S. Gong, “Non-intrusive person authentication for access control by visual tracking and face recognition,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 177–184.
  5. M. Seibert, A. M. Waxman, “Combining evidence from multiple views of 3-D objects,” in Sensor Fusion IV: Control Paradigms and Data Structures, P. S. Schenker, ed., Proc. SPIE1611, 178–189 (1991).
  6. J. Steffens, E. Elagin, H. Neven, “PersonSpotter—fast and robust system for human detection, tracking and recognition,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 516–521.
  7. M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
    [CrossRef]
  8. S. Geman, D. Geman, “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, 721–741 (1984).
    [CrossRef]
  9. G. Kitagawa, “Monte Carlo filter and smoother for non-Gaussian nonlinear state space models,” J. Comput. Graph. Stat. 5, 1–25 (1996).
  10. J. Hammersley, D. Handscomb, Monte Carlo Methods (Wiley, New York, 1964).
  11. M. H. Kalos, P. A. Whitlock, Monte Carlo Methods (Wiley, New York, 1986).
  12. J. Liu, R. Chen, “Sequential Monte Carlo methodsfor dynamic systems,” J. Am. Stat. Assoc. 93, 1031–1041 (1998).
    [CrossRef]
  13. N. Gordon, D. Salmond, A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Trans. Radar Signal Process. 140, 107–113 (1993).
    [CrossRef]
  14. A. Kong, J. Liu, W. Wong, “Sequential imputations and Bayesian missing data problems,” J. Am. Stat. Assoc. 89, 278–288 (1994).
    [CrossRef]
  15. M. Isard, A. Blake, “Contour tracking by stochastic propagation of conditional density,” in Proceedings of the European Conference on Computer Vision (Springer-Verlag, Cambridge, UK, 1996), Vol. I, pp. 343–356.
  16. B. S. Manjunath, R. Chellappa, “A feature based approach to face recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1992), pp. 373–378.
  17. K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).
  18. B. Li, R. Chellappa, “Simultaneous tracking and verification via sequential importance sampling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 110–117.
  19. D. Kendall, “Shape manifolds, procrustean metrics and complex projective spaces,” Bull. London Math. Soc. 16, 81–121 (1983).
    [CrossRef]
  20. D. Kendall, “Further developments and applications of the statistical theory of shape,” Theory Probab. It. Appl. 31, 407–412 (1986).
    [CrossRef]
  21. D. Kendall, “A survey of the statistical theory of shape,” Stat. Sci. 4, 87–120 (1989).
    [CrossRef]
  22. F. L. Bookstein, “Size and shape spaces for landmark data in two dimensions,” Stat. Sci. 1, 181–242 (1986).
    [CrossRef]
  23. I. L. Dryden, K. V. Mardia, “General shape distribution in a plane,” Adv. Appl. Probab. 23, 259–276 (1989).
    [CrossRef]
  24. K. V. Mardia, I. L. Dryden, “Shape distribution for landmark data,” Adv. Appl. Probab. 21, 742–255 (1989).
    [CrossRef]
  25. C. R. Goodall, K. V. Mardia, “Multivariate aspects of shape theory,” Ann. Stat. 21, 259–276 (1993).
    [CrossRef]
  26. R. Berthilsson, “A statistic theory of shape,” (Department of Mathematics, Lund Institute of Technology, Lund, The Netherlands, 1997).
  27. W. Grimson, D. Huttenlocher, D. Jacobs, “A study of affine matching with bounded sensor error,” in Proceedings of the European Conference on Computer Vision, Vol. 588 of Lecture Notes in Computer Science (Springer, New York, 1992), pp. 291–306.
  28. M. C. Burl, T. K. Leung, P. Perona, “Face localization via shape statistics,” in Proceedings of the Workshop on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1995), pp. 194–199.
  29. T. K. Leung, M. C. Burl, P. Perona, “Probabilistic affine invariants for recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 678–684.
  30. M. Weber, M. Welling, P. Perona, “Towards automatic discovery of object categories,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 101–106.
  31. M. Black, Y. Yacoob, “Tracking and recognizing facial expressions in image sequences, using local parametrized models of image motion,” (Center for Automation Research, University of Maryland, College Park, Md., 1995).
  32. S. J. McKenna, S. Gong, R. P. Wurtz, J. Tanner, “Tracking facial feature points with Gabor wavelets and shape models,” in Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication (Springer, New York, 1997), pp. 35–43.
  33. D. Freedman, M. Brandstein, “A subset approach to contour tracking in clutter,” in Proceedings of the International Conference on Computer Vision (IEEE Computer Society, Los Alamitos, Calif., (1999), pp. 99–104.

1998 (1)

J. Liu, R. Chen, “Sequential Monte Carlo methodsfor dynamic systems,” J. Am. Stat. Assoc. 93, 1031–1041 (1998).
[CrossRef]

1996 (1)

G. Kitagawa, “Monte Carlo filter and smoother for non-Gaussian nonlinear state space models,” J. Comput. Graph. Stat. 5, 1–25 (1996).

1994 (1)

A. Kong, J. Liu, W. Wong, “Sequential imputations and Bayesian missing data problems,” J. Am. Stat. Assoc. 89, 278–288 (1994).
[CrossRef]

1993 (3)

N. Gordon, D. Salmond, A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Trans. Radar Signal Process. 140, 107–113 (1993).
[CrossRef]

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

C. R. Goodall, K. V. Mardia, “Multivariate aspects of shape theory,” Ann. Stat. 21, 259–276 (1993).
[CrossRef]

1991 (1)

M. Turk, A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 72–86 (1991).
[CrossRef]

1989 (3)

D. Kendall, “A survey of the statistical theory of shape,” Stat. Sci. 4, 87–120 (1989).
[CrossRef]

I. L. Dryden, K. V. Mardia, “General shape distribution in a plane,” Adv. Appl. Probab. 23, 259–276 (1989).
[CrossRef]

K. V. Mardia, I. L. Dryden, “Shape distribution for landmark data,” Adv. Appl. Probab. 21, 742–255 (1989).
[CrossRef]

1986 (2)

F. L. Bookstein, “Size and shape spaces for landmark data in two dimensions,” Stat. Sci. 1, 181–242 (1986).
[CrossRef]

D. Kendall, “Further developments and applications of the statistical theory of shape,” Theory Probab. It. Appl. 31, 407–412 (1986).
[CrossRef]

1984 (1)

S. Geman, D. Geman, “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, 721–741 (1984).
[CrossRef]

1983 (1)

D. Kendall, “Shape manifolds, procrustean metrics and complex projective spaces,” Bull. London Math. Soc. 16, 81–121 (1983).
[CrossRef]

Berthilsson, R.

R. Berthilsson, “A statistic theory of shape,” (Department of Mathematics, Lund Institute of Technology, Lund, The Netherlands, 1997).

Black, M.

M. Black, Y. Yacoob, “Tracking and recognizing facial expressions in image sequences, using local parametrized models of image motion,” (Center for Automation Research, University of Maryland, College Park, Md., 1995).

Blake, A.

M. Isard, A. Blake, “Contour tracking by stochastic propagation of conditional density,” in Proceedings of the European Conference on Computer Vision (Springer-Verlag, Cambridge, UK, 1996), Vol. I, pp. 343–356.

Bookstein, F. L.

F. L. Bookstein, “Size and shape spaces for landmark data in two dimensions,” Stat. Sci. 1, 181–242 (1986).
[CrossRef]

Brandstein, M.

D. Freedman, M. Brandstein, “A subset approach to contour tracking in clutter,” in Proceedings of the International Conference on Computer Vision (IEEE Computer Society, Los Alamitos, Calif., (1999), pp. 99–104.

Buhmann, J.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

Burl, M. C.

M. C. Burl, T. K. Leung, P. Perona, “Face localization via shape statistics,” in Proceedings of the Workshop on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1995), pp. 194–199.

T. K. Leung, M. C. Burl, P. Perona, “Probabilistic affine invariants for recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 678–684.

Buxton, H.

A. J. Howell, H. Buxton, “Towards unconstrained face recognition from image sequences,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1996), pp. 224–229.

Chellappa, R.

B. S. Manjunath, R. Chellappa, “A feature based approach to face recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1992), pp. 373–378.

B. Li, R. Chellappa, “Simultaneous tracking and verification via sequential importance sampling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 110–117.

Chen, R.

J. Liu, R. Chen, “Sequential Monte Carlo methodsfor dynamic systems,” J. Am. Stat. Assoc. 93, 1031–1041 (1998).
[CrossRef]

Chen, V.

H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.

Dryden, I. L.

K. V. Mardia, I. L. Dryden, “Shape distribution for landmark data,” Adv. Appl. Probab. 21, 742–255 (1989).
[CrossRef]

I. L. Dryden, K. V. Mardia, “General shape distribution in a plane,” Adv. Appl. Probab. 23, 259–276 (1989).
[CrossRef]

Elagin, E.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

J. Steffens, E. Elagin, H. Neven, “PersonSpotter—fast and robust system for human detection, tracking and recognition,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 516–521.

Freedman, D.

D. Freedman, M. Brandstein, “A subset approach to contour tracking in clutter,” in Proceedings of the International Conference on Computer Vision (IEEE Computer Society, Los Alamitos, Calif., (1999), pp. 99–104.

Geman, D.

S. Geman, D. Geman, “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, 721–741 (1984).
[CrossRef]

Geman, S.

S. Geman, D. Geman, “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images,” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-6, 721–741 (1984).
[CrossRef]

Gong, S.

S. J. McKenna, S. Gong, “Non-intrusive person authentication for access control by visual tracking and face recognition,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 177–184.

S. J. McKenna, S. Gong, R. P. Wurtz, J. Tanner, “Tracking facial feature points with Gabor wavelets and shape models,” in Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication (Springer, New York, 1997), pp. 35–43.

Goodall, C. R.

C. R. Goodall, K. V. Mardia, “Multivariate aspects of shape theory,” Ann. Stat. 21, 259–276 (1993).
[CrossRef]

Gordon, N.

N. Gordon, D. Salmond, A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Trans. Radar Signal Process. 140, 107–113 (1993).
[CrossRef]

Grimson, W.

W. Grimson, D. Huttenlocher, D. Jacobs, “A study of affine matching with bounded sensor error,” in Proceedings of the European Conference on Computer Vision, Vol. 588 of Lecture Notes in Computer Science (Springer, New York, 1992), pp. 291–306.

Gutta, S.

H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.

Hammersley, J.

J. Hammersley, D. Handscomb, Monte Carlo Methods (Wiley, New York, 1964).

Handscomb, D.

J. Hammersley, D. Handscomb, Monte Carlo Methods (Wiley, New York, 1964).

Hong, H.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

Howell, A. J.

A. J. Howell, H. Buxton, “Towards unconstrained face recognition from image sequences,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1996), pp. 224–229.

Huang, J.

H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.

Huttenlocher, D.

W. Grimson, D. Huttenlocher, D. Jacobs, “A study of affine matching with bounded sensor error,” in Proceedings of the European Conference on Computer Vision, Vol. 588 of Lecture Notes in Computer Science (Springer, New York, 1992), pp. 291–306.

Isard, M.

M. Isard, A. Blake, “Contour tracking by stochastic propagation of conditional density,” in Proceedings of the European Conference on Computer Vision (Springer-Verlag, Cambridge, UK, 1996), Vol. I, pp. 343–356.

Jacobs, D.

W. Grimson, D. Huttenlocher, D. Jacobs, “A study of affine matching with bounded sensor error,” in Proceedings of the European Conference on Computer Vision, Vol. 588 of Lecture Notes in Computer Science (Springer, New York, 1992), pp. 291–306.

Kakkad, V.

H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.

Kalos, M. H.

M. H. Kalos, P. A. Whitlock, Monte Carlo Methods (Wiley, New York, 1986).

Kendall, D.

D. Kendall, “A survey of the statistical theory of shape,” Stat. Sci. 4, 87–120 (1989).
[CrossRef]

D. Kendall, “Further developments and applications of the statistical theory of shape,” Theory Probab. It. Appl. 31, 407–412 (1986).
[CrossRef]

D. Kendall, “Shape manifolds, procrustean metrics and complex projective spaces,” Bull. London Math. Soc. 16, 81–121 (1983).
[CrossRef]

Kitagawa, G.

G. Kitagawa, “Monte Carlo filter and smoother for non-Gaussian nonlinear state space models,” J. Comput. Graph. Stat. 5, 1–25 (1996).

Konen, W.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

Kong, A.

A. Kong, J. Liu, W. Wong, “Sequential imputations and Bayesian missing data problems,” J. Am. Stat. Assoc. 89, 278–288 (1994).
[CrossRef]

Lades, M.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

Lange, J.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

Leung, T. K.

M. C. Burl, T. K. Leung, P. Perona, “Face localization via shape statistics,” in Proceedings of the Workshop on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1995), pp. 194–199.

T. K. Leung, M. C. Burl, P. Perona, “Probabilistic affine invariants for recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 678–684.

Li, B.

B. Li, R. Chellappa, “Simultaneous tracking and verification via sequential importance sampling,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 110–117.

Liu, J.

J. Liu, R. Chen, “Sequential Monte Carlo methodsfor dynamic systems,” J. Am. Stat. Assoc. 93, 1031–1041 (1998).
[CrossRef]

A. Kong, J. Liu, W. Wong, “Sequential imputations and Bayesian missing data problems,” J. Am. Stat. Assoc. 89, 278–288 (1994).
[CrossRef]

Malsburg, C. v.d.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

Manjunath, B. S.

B. S. Manjunath, R. Chellappa, “A feature based approach to face recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1992), pp. 373–378.

Mardia, K. V.

C. R. Goodall, K. V. Mardia, “Multivariate aspects of shape theory,” Ann. Stat. 21, 259–276 (1993).
[CrossRef]

I. L. Dryden, K. V. Mardia, “General shape distribution in a plane,” Adv. Appl. Probab. 23, 259–276 (1989).
[CrossRef]

K. V. Mardia, I. L. Dryden, “Shape distribution for landmark data,” Adv. Appl. Probab. 21, 742–255 (1989).
[CrossRef]

Maurer, T.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

McKenna, S. J.

S. J. McKenna, S. Gong, “Non-intrusive person authentication for access control by visual tracking and face recognition,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 177–184.

S. J. McKenna, S. Gong, R. P. Wurtz, J. Tanner, “Tracking facial feature points with Gabor wavelets and shape models,” in Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication (Springer, New York, 1997), pp. 35–43.

Neven, H.

J. Steffens, E. Elagin, H. Neven, “PersonSpotter—fast and robust system for human detection, tracking and recognition,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 516–521.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

Okada, K.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

Pentland, A.

M. Turk, A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 72–86 (1991).
[CrossRef]

Perona, P.

M. C. Burl, T. K. Leung, P. Perona, “Face localization via shape statistics,” in Proceedings of the Workshop on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1995), pp. 194–199.

T. K. Leung, M. C. Burl, P. Perona, “Probabilistic affine invariants for recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 678–684.

M. Weber, M. Welling, P. Perona, “Towards automatic discovery of object categories,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 101–106.

Salmond, D.

N. Gordon, D. Salmond, A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Trans. Radar Signal Process. 140, 107–113 (1993).
[CrossRef]

Seibert, M.

M. Seibert, A. M. Waxman, “Combining evidence from multiple views of 3-D objects,” in Sensor Fusion IV: Control Paradigms and Data Structures, P. S. Schenker, ed., Proc. SPIE1611, 178–189 (1991).

Smith, A.

N. Gordon, D. Salmond, A. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Trans. Radar Signal Process. 140, 107–113 (1993).
[CrossRef]

Steffens, J.

J. Steffens, E. Elagin, H. Neven, “PersonSpotter—fast and robust system for human detection, tracking and recognition,” in Proceedings of the International Conference on Automatic Face and Gesture Recognition (IEEE Computer Society, Los Alamitos, Calif., 1998), pp. 516–521.

K. Okada, J. Steffens, T. Maurer, H. Hong, E. Elagin, H. Neven, C. v.d. Malsburg, “The Bochum/USC face recognition system,” in Face Recognition: From Theory to Applications, H. Wechsler, P. J. Phillips, V. Bruce, F. Soulie, T. Huang, eds. (Springer-Verlag, New York, 1998).

Tanner, J.

S. J. McKenna, S. Gong, R. P. Wurtz, J. Tanner, “Tracking facial feature points with Gabor wavelets and shape models,” in Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication (Springer, New York, 1997), pp. 35–43.

Turk, M.

M. Turk, A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 72–86 (1991).
[CrossRef]

Vorbruggen, J.

M. Lades, J. Vorbruggen, J. Buhmann, J. Lange, C. v.d. Malsburg, W. Konen, “Distortion invariant object recognition in the dynamic link architecture,” IEEE Trans. Comput. 42, 300–311 (1993).
[CrossRef]

Waxman, A. M.

M. Seibert, A. M. Waxman, “Combining evidence from multiple views of 3-D objects,” in Sensor Fusion IV: Control Paradigms and Data Structures, P. S. Schenker, ed., Proc. SPIE1611, 178–189 (1991).

Weber, M.

M. Weber, M. Welling, P. Perona, “Towards automatic discovery of object categories,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 101–106.

Wechsler, H.

H. Wechsler, V. Kakkad, J. Huang, S. Gutta, V. Chen, “Automatic video-based person authentication using the RBF network,” in Proceedings of the International Conference on Audio- and Video-Based Person Authentication (Springer, New York, 1997), pp. 85–92.

Welling, M.

M. Weber, M. Welling, P. Perona, “Towards automatic discovery of object categories,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (IEEE Computer Society, Los Alamitos, Calif., 2000), Vol. II, pp. 101–106.

Whitlock, P. A.

M. H. Kalos, P. A. Whitlock, Monte Carlo Methods (Wiley, New York, 1986).

Wong, W.

A. Kong, J. Liu, W. Wong, “Sequential imputations and Bayesian missing data problems,” J. Am. Stat. Assoc. 89, 278–288 (1994).
[CrossRef]

Wurtz, R. P.

S. J. McKenna, S. Gong, R. P. Wurtz, J. Tanner, “Tracking facial feature points with Gabor wavelets and shape models,” in Proceedings of the International Conference on Audio- and Video-Based Biometric Person Authentication (Springer, New York, 1997), pp. 35–43.

Yacoob, Y.

M. Black, Y. Yacoob, “Tracking and recognizing facial expressions in image sequences, using local parametrized models of image motion,” (Center for Automation Research, University of Maryland, College Park, Md., 1995).

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