Abstract

In this work, we propose a novel technique for face recognition with ±90° pose variations in image sequences using a cellular simultaneous recurrent network (CSRN). We formulate the recognition prob lem with such large-pose variations as an implicit temporal prediction task for CSRN. We exploit a face extraction algorithm based on the scale-space method and facial structural knowledge as a preprocessing step. Further, to reduce computational cost, we obtain eigenfaces for a set of image sequences for each person and use these reduced pattern vectors as the input to CSRN. CSRN learns how to associate each face class/person in the training phase. A modified distance metric between successive frames of test and training output pattern vectors indicate either a match or mismatch between the two corresponding face classes. We extensively evaluate our CSRN-based face recognition technique using the publicly available VidTIMIT Audio-Video face dataset. Our simulation shows that for this dataset with large-scale pose variations, we can obtain an overall 77% face recognition rate.

© 2010 Optical Society of America

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  1. W. Zhao, “Face recognition: a literature survey,” ACM Comput. Surv. 35, 399-458 (2003).
    [CrossRef]
  2. P. J. Phillips and P. Grother, “Face Recognition Vendor Test 2002: evaluation report,” www.frvt.org/DLs/FRVT_2002_Evaluation_Report.pdf.
  3. L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
    [CrossRef]
  4. A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
    [CrossRef]
  5. T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
    [CrossRef]
  6. S. Zhou and R. Chellappa, “Image-based face recognition under illumination and pose variations,” J. Opt. Soc. Am. A 22, 217-229 (2005).
    [CrossRef]
  7. S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).
  8. J. Elman, “Finding structure in time,” Cogn. Sci. 14, 179-211(1990).
    [CrossRef]
  9. P. J. Werbos and X. Pang, “Generalized maze navigation: SRN critics solve what feedforward or Hebbian cannot,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (IEEE, 1996).
  10. R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
    [CrossRef] [PubMed]
  11. Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.
  12. K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
    [CrossRef] [PubMed]
  13. Y. Ren, K. Iftekharuddin, E. White. “Recurrent network-based face recognition using image sequences,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 41-46.
    [CrossRef]
  14. F. Jiao and W. Gao. “A face recognition method based on local feature analysis,” in ACCV2002: Proceedings of the Fifth Asian Conference on Computer Vision (ACCV, 2002), pp. 188-192.
  15. Z. Liposcak and S. Loncaric “A scale-space approach to face recognition from profile,” International Conference on Computer Analysis of Images and Patterns, Ljubljana, Slovenia, 1-3 September 1999.
  16. P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).
  17. M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
    [CrossRef]
  18. I. Craw, H. Ellis, and J. Lishman, “Automatic extraction of face features,” Pattern Recogn. Lett. 5, 183-187 (1987).
    [CrossRef]
  19. A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and tracking of human face with synthesized templates,” in Proceedings of the First Asian Conference on Computer Vision (ACCV, 1993), pp. 183-186.
  20. A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and pose estimation of human face with synthesized image models,” in Proceedings of the International Conference on Pattern Recognition (IEEE, 1994), pp. 754-757.
    [CrossRef]
  21. M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71-86 (1991).
    [CrossRef]
  22. K. Etemad and R. Chellappa, “Discriminant analysis for recognition of human face images,” J. Opt. Soc. Am. A 14, 1724-1733 (1997).
    [CrossRef]
  23. S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
    [CrossRef]
  24. H. Ling and David W. Jacobs, “Deformation invariant image matching,” in Proceedings of the International Conference on Computer Vision (IEEE, 2005), Vol. 2, pp. 1466-1473.
  25. A. P. Witkin, “Scale-space filtering,” in Proceedings of the Eighth International Joint Conference on Artificial Intelligence (IJCAI, 1983), pp. 1019-1022
  26. C. Sanderson, Biometric Person Recognition: Face, Speech and Fusion (VDM-Verlag, 2008).
  27. D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

2008 (1)

R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
[CrossRef] [PubMed]

2005 (1)

2003 (1)

W. Zhao, “Face recognition: a literature survey,” ACM Comput. Surv. 35, 399-458 (2003).
[CrossRef]

2002 (1)

M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
[CrossRef]

2001 (1)

T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
[CrossRef]

1997 (3)

K. Etemad and R. Chellappa, “Discriminant analysis for recognition of human face images,” J. Opt. Soc. Am. A 14, 1724-1733 (1997).
[CrossRef]

S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
[CrossRef]

L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
[CrossRef]

1995 (1)

A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
[CrossRef]

1991 (1)

M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71-86 (1991).
[CrossRef]

1990 (1)

J. Elman, “Finding structure in time,” Cogn. Sci. 14, 179-211(1990).
[CrossRef]

Ahuja, N.

M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
[CrossRef]

Anderson, K.

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
[CrossRef] [PubMed]

Beveridge, R.

D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

Bolme, D.

D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

Bowyer, K. W.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Chellappa, R.

Cootes, T. F.

T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
[CrossRef]

A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
[CrossRef]

Craw, I.

I. Craw, H. Ellis, and J. Lishman, “Automatic extraction of face features,” Pattern Recogn. Lett. 5, 183-187 (1987).
[CrossRef]

Draper, B.

D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

Edwards, G. J.

T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
[CrossRef]

Ellis, H.

I. Craw, H. Ellis, and J. Lishman, “Automatic extraction of face features,” Pattern Recogn. Lett. 5, 183-187 (1987).
[CrossRef]

Elman, J.

J. Elman, “Finding structure in time,” Cogn. Sci. 14, 179-211(1990).
[CrossRef]

Etemad, K.

Fellous, J. M.

L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
[CrossRef]

Flynn, P. J.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Gao, W.

F. Jiao and W. Gao. “A face recognition method based on local feature analysis,” in ACCV2002: Proceedings of the Fifth Asian Conference on Computer Vision (ACCV, 2002), pp. 188-192.

Gongy, S.

S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).

Grother, P.

P. J. Phillips and P. Grother, “Face Recognition Vendor Test 2002: evaluation report,” www.frvt.org/DLs/FRVT_2002_Evaluation_Report.pdf.

Iftekharuddin, K.

K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
[CrossRef] [PubMed]

Y. Ren, K. Iftekharuddin, E. White. “Recurrent network-based face recognition using image sequences,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 41-46.
[CrossRef]

Iftekharuddin, K. M.

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

Ilin, R.

R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
[CrossRef] [PubMed]

Jacobs, David W.

H. Ling and David W. Jacobs, “Deformation invariant image matching,” in Proceedings of the International Conference on Computer Vision (IEEE, 2005), Vol. 2, pp. 1466-1473.

Jiao, F.

F. Jiao and W. Gao. “A face recognition method based on local feature analysis,” in ACCV2002: Proceedings of the Fifth Asian Conference on Computer Vision (ACCV, 2002), pp. 188-192.

Katsoulisy, I.

S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).

Kim, P.

K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
[CrossRef] [PubMed]

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

Kozma, R.

R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
[CrossRef] [PubMed]

Kriegman, D.

M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
[CrossRef]

Kung, S. Y.

S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
[CrossRef]

Lanitis, A.

A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
[CrossRef]

Lee, C.-W.

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and tracking of human face with synthesized templates,” in Proceedings of the First Asian Conference on Computer Vision (ACCV, 1993), pp. 183-186.

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and pose estimation of human face with synthesized image models,” in Proceedings of the International Conference on Pattern Recognition (IEEE, 1994), pp. 754-757.
[CrossRef]

Lin, L. J.

S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
[CrossRef]

Lin, S. H.

S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
[CrossRef]

Ling, H.

H. Ling and David W. Jacobs, “Deformation invariant image matching,” in Proceedings of the International Conference on Computer Vision (IEEE, 2005), Vol. 2, pp. 1466-1473.

Liposcak, Z.

Z. Liposcak and S. Loncaric “A scale-space approach to face recognition from profile,” International Conference on Computer Analysis of Images and Patterns, Ljubljana, Slovenia, 1-3 September 1999.

Lishman, J.

I. Craw, H. Ellis, and J. Lishman, “Automatic extraction of face features,” Pattern Recogn. Lett. 5, 183-187 (1987).
[CrossRef]

Loncaric, S.

Z. Liposcak and S. Loncaric “A scale-space approach to face recognition from profile,” International Conference on Computer Analysis of Images and Patterns, Ljubljana, Slovenia, 1-3 September 1999.

Malsburg, C. v. D.

L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
[CrossRef]

O'Toole, A. J.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Palavouzisy, P.

S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).

Pang, X.

P. J. Werbos and X. Pang, “Generalized maze navigation: SRN critics solve what feedforward or Hebbian cannot,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (IEEE, 1996).

Pentland, A.

M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71-86 (1991).
[CrossRef]

Phillips, P. J.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

P. J. Phillips and P. Grother, “Face Recognition Vendor Test 2002: evaluation report,” www.frvt.org/DLs/FRVT_2002_Evaluation_Report.pdf.

Psarrouz, A.

S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).

Ren, Y.

Y. Ren, K. Iftekharuddin, E. White. “Recurrent network-based face recognition using image sequences,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 41-46.
[CrossRef]

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

Sanderson, C.

C. Sanderson, Biometric Person Recognition: Face, Speech and Fusion (VDM-Verlag, 2008).

Schott, C. L.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Scruggs, W. T.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Sharpe, M.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

Taylor, C. J.

T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
[CrossRef]

A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
[CrossRef]

Teixeira, M.

D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

Tsuji, S.

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and pose estimation of human face with synthesized image models,” in Proceedings of the International Conference on Pattern Recognition (IEEE, 1994), pp. 754-757.
[CrossRef]

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and tracking of human face with synthesized templates,” in Proceedings of the First Asian Conference on Computer Vision (ACCV, 1993), pp. 183-186.

Tsukamoto, A.

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and pose estimation of human face with synthesized image models,” in Proceedings of the International Conference on Pattern Recognition (IEEE, 1994), pp. 754-757.
[CrossRef]

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and tracking of human face with synthesized templates,” in Proceedings of the First Asian Conference on Computer Vision (ACCV, 1993), pp. 183-186.

Turk, M.

M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71-86 (1991).
[CrossRef]

Werbos, P. J.

R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
[CrossRef] [PubMed]

P. J. Werbos and X. Pang, “Generalized maze navigation: SRN critics solve what feedforward or Hebbian cannot,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (IEEE, 1996).

White, E.

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
[CrossRef] [PubMed]

Y. Ren, K. Iftekharuddin, E. White. “Recurrent network-based face recognition using image sequences,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 41-46.
[CrossRef]

Wiskott, L.

L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
[CrossRef]

Witkin, A. P.

A. P. Witkin, “Scale-space filtering,” in Proceedings of the Eighth International Joint Conference on Artificial Intelligence (IJCAI, 1983), pp. 1019-1022

Yang, M.

M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
[CrossRef]

Zhao, W.

W. Zhao, “Face recognition: a literature survey,” ACM Comput. Surv. 35, 399-458 (2003).
[CrossRef]

Zhou, S.

ACM Comput. Surv. (1)

W. Zhao, “Face recognition: a literature survey,” ACM Comput. Surv. 35, 399-458 (2003).
[CrossRef]

Cogn. Sci. (1)

J. Elman, “Finding structure in time,” Cogn. Sci. 14, 179-211(1990).
[CrossRef]

IEEE Trans. Neur. Netw. (1)

S. H. Lin, S. Y. Kung, and L. J. Lin, “Face recognition/detection by probabilistic decision based neural network,” IEEE Trans. Neur. Netw. 8, 114-132 (1997).
[CrossRef]

IEEE Trans. Neural Netw. (1)

R. Ilin, R. Kozma, and P. J. Werbos, “Beyond backpropagation and feedforward models: a practical training tool for a more efficient universal approximator,” IEEE Trans. Neural Netw. 19, 929-937(2008).
[CrossRef] [PubMed]

IEEE Trans. Pattern Anal. Machine Intell. (3)

M. Yang, D. Kriegman, and N. Ahuja, “Detecting face in images: a survey,” IEEE Trans. Pattern Anal. Machine Intell. 24, 34-58 (2002).
[CrossRef]

T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,” IEEE Trans. Pattern Anal. Machine Intell. 23, 681-685 (2001).
[CrossRef]

L. Wiskott, J. M. Fellous, and C. v. D. Malsburg, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Anal. Machine Intell. 19, 775-779 (1997).
[CrossRef]

Image Vis. Comput. (1)

A. Lanitis, C. J. Taylor, and T. F. Cootes, “Automatic face identification system using flexible appearance models,” Image Vis. Comput. 13, 393-401 (1995).
[CrossRef]

J. Cogn. Neurosci. (1)

M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cogn. Neurosci. 3, 71-86 (1991).
[CrossRef]

J. Opt. Soc. Am. A (2)

Other (16)

S. Gongy, A. Psarrouz, I. Katsoulisy, and P. Palavouzisy, “Tracking and recognition of face sequences,” in Proceedings of the European Workshop on Combined Real and Synthetic Image Processing for Broadcast and Video Production (Springer, 1994).

P. J. Werbos and X. Pang, “Generalized maze navigation: SRN critics solve what feedforward or Hebbian cannot,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (IEEE, 1996).

P. J. Phillips and P. Grother, “Face Recognition Vendor Test 2002: evaluation report,” www.frvt.org/DLs/FRVT_2002_Evaluation_Report.pdf.

I. Craw, H. Ellis, and J. Lishman, “Automatic extraction of face features,” Pattern Recogn. Lett. 5, 183-187 (1987).
[CrossRef]

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and tracking of human face with synthesized templates,” in Proceedings of the First Asian Conference on Computer Vision (ACCV, 1993), pp. 183-186.

A. Tsukamoto, C.-W. Lee, and S. Tsuji, “Detection and pose estimation of human face with synthesized image models,” in Proceedings of the International Conference on Pattern Recognition (IEEE, 1994), pp. 754-757.
[CrossRef]

Y. Ren, K. Anderson, K. M. Iftekharuddin, P. Kim, and E. White, “Pose invariant face recognition using cellular simultaneous recurrent networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE, 2009), pp. 2634-2641.

K. Anderson, K. Iftekharuddin, E. White, and P. Kim, “Binary image registration using cellular simultaneous recurrent networks,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 61-67.
[CrossRef] [PubMed]

Y. Ren, K. Iftekharuddin, E. White. “Recurrent network-based face recognition using image sequences,” in IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, CIMSVP '09 (IEEE, 2009), pp. 41-46.
[CrossRef]

F. Jiao and W. Gao. “A face recognition method based on local feature analysis,” in ACCV2002: Proceedings of the Fifth Asian Conference on Computer Vision (ACCV, 2002), pp. 188-192.

Z. Liposcak and S. Loncaric “A scale-space approach to face recognition from profile,” International Conference on Computer Analysis of Images and Patterns, Ljubljana, Slovenia, 1-3 September 1999.

P. J. Phillips, W. T. Scruggs, A. J. O'Toole, P. J. Flynn, K. W. Bowyer, C. L. Schott, and M. Sharpe, “Face Recognition Vendor Test 2006: evaluation report,” http://www.frvt.org/FRVT2006/docs/FRVT2006andICE2006LargeScaleReport.pdf (March 2007).

H. Ling and David W. Jacobs, “Deformation invariant image matching,” in Proceedings of the International Conference on Computer Vision (IEEE, 2005), Vol. 2, pp. 1466-1473.

A. P. Witkin, “Scale-space filtering,” in Proceedings of the Eighth International Joint Conference on Artificial Intelligence (IJCAI, 1983), pp. 1019-1022

C. Sanderson, Biometric Person Recognition: Face, Speech and Fusion (VDM-Verlag, 2008).

D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, “The CSU face identification evaluation system: its purpose, features and structure,” presented at the International Conference on Vision Systems, Graz, Austria 1-3 April 2003.

Supplementary Material (1)

» Media 1: MOV (45 KB)     

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Figures (18)

Fig. 1
Fig. 1

Basic topology of the SRN.

Fig. 2
Fig. 2

CSRN architecture.

Fig. 3
Fig. 3

These two image sequences are taken from two subjects; each contains five frames and rotates from right to left.

Fig. 4
Fig. 4

Overall flow diagram of proposed face recognition system using CSRN.

Fig. 5
Fig. 5

Proposed flow diagram of face extraction.

Fig. 6
Fig. 6

Nose tip location.

Fig. 7
Fig. 7

Single-frame excerpts from video recordings of key point locations at eye edge (Media 1).

Fig. 8
Fig. 8

Improved algorithm for detection of key point location.

Fig. 9
Fig. 9

Example of key points that cannot be located correctly: (a) the profile line is too smooth, so that there is not enough extrema, and (b) the profile line is too twisted.

Fig. 10
Fig. 10

Algorithm for facial structural knowledge and GIH.

Fig. 11
Fig. 11

Euclidean distance of person 1, sequence 1.

Fig. 12
Fig. 12

Processing steps of scale-space method for face extraction.

Fig. 13
Fig. 13

(a) Original image and (b) the point moving to the correct position after GIH.

Fig. 14
Fig. 14

Input images and their corresponding targets.

Fig. 15
Fig. 15

Euclidean distance of person 1, sequence 1.

Fig. 16
Fig. 16

Eighth element of a sequence for person 2.

Fig. 17
Fig. 17

Training sequence in experiment 2.

Fig. 18
Fig. 18

Euclidean distance of person 1, sequence 1.

Tables (6)

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Table 1 Extraction Rate of Different Methods

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Table 2 Experiment Settings

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Table 3 Recognition Detail of CSRN in Experiment 1

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Table 4 Recognition Detail of CSRN in Experiment 2

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Table 5 Identification Rates of Two Experiments

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Table 6 Comparison of Different Methods

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

χ 2 ( p , q ) 1 2 k = 1 K m = 1 M [ H p ( k , m ) H q ( k , m ) ] 2 H p ( k , m ) + H q ( k , m ) .
F ( X , σ ) = f ( x ) * g ( x , σ ) = + f ( u ) ( 1 σ 2 π ) e ( x u ) 2 2 σ 2 d u ,
Γ t = C t K t C t T + R t ,
G t = K t C t T Γ t 1 ,
w ¯ t + 1 = w ¯ t G t α t ¯ ,
K t + 1 = K t K t C t G t + Q t .
ξ = 0.6 * dist 1 + 0.5 * dist 2 + 0.5 slope 1 + 0.2 * slope 1 0.2 * . conv .

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