Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

A neural network-based point registration method for 3D rigid face image

  • Published:
World Wide Web Aims and scope Submit manuscript

Abstract

Intelligent detection of human face image combined with the real-time video monitoring has been applied to improve the secure and protective possibility. The registration is an indispensible step before distinguishing the variation among the images. Neural network (NN) has a strong learning ability from a mass unstructured point cloud even containing noisy data. Neural network has been applied to register 3D reconstructed ear data and 3D surface of bunny and to achieve the better results. Motivated by this idea, NN-based registration method for 3D rigid face image is proposed. This paper presented the proof process of obtaining rotation matrix and translation vector according to the training process of neural network. Then the measure index of registration performance was provided. The elaborate experiments were conducted on the 3D USF face database (provided by the University of South Florida) to verify the effectiveness of neural network as a registration method. Next, two comparisons were performed, one group was NN-based and ICP-based registration methods and the other group was our proposed NN-based and other NN-based registration methods. The experimental results showed that neural network is a robust and potential registration method for rigid face image registration. Furthermore, our proposed NN-based registration method is extended easily to do 2D-to-3D registration and non-rigid face registration.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Abche, A.B., Yaacoub, F., Maalouf, A., Karam, E.: Image registration based on neural network and Fourier transform. In: The 28th IEEE EMBS Annual International Conference, New York City, USA 2006, pp. 4803–4806

  2. Alyüz, N., Gökberk, B., Dibeklioglu, H., Akarun, L.: Component-based registration with curvature descriptors for expression insensitive 3d face recognition. In: The 8th IEEE International Conference on Automatic Face & Gesture Recognition, pp. 1–6 (2008)

  3. Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Transaction Pattern Analysis & Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  4. Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: The 26th annual conference on Computer graphics and interactive techniques, pp. 187–194 (1999)

  5. Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE Transactions Pattern Analysis & Machine Intelligence 25(9), 1063–1074 (2003)

    Article  Google Scholar 

  6. Cui, Y., Pei, J., Tang, G., Luk, W.-S., Jiang, D., Hua, M.: Finding email correspondents in online social networks. World Wide Web 16(2), 195–218 (2013)

    Google Scholar 

  7. Dahm, N., Gao, Y.: A Novel Pose Invariant Face Recognition Approach Using a 2D-3D Searching Strategy. In: The 20th International Conference on Pattern Recognition, pp. 3967–3970 (2010)

  8. Duffner, S.: Face image analysis with Convolutional neural networks. Doctoral dissertation, Albert-Ludwigs University of Freiburg (2007)

  9. Duffner, S., Garcia, C.: Robust Face Alignment Using Convolutional Neural Networks. In: The 3th International Conference on Computer Vision Theory and Applications, vol. 2, pp. 30–37 (2008)

  10. Gökberk, B., İrfanoğlu, M.O., Akarun, L.: 3D shape-based face representation and feature extraction for face recognition. Image and Vision Computing 24(8), 857–869 (2006)

    Article  Google Scholar 

  11. Horaud, R., Forbes, F., Yguel, M., Dewaele, G., Zhang, J.: Rigid and articulated point registration with expectation conditional maxinization. IEEE Transactions Pattern Analysis & Machine Intelligence 33(3), 587–602 (2011)

    Article  Google Scholar 

  12. Jian, B., Vemuri, B.C.: Robust point set registration using Gaussian mixture models. IEEE Transactions Pattern Analysis & Machine Intelligence 33(8), 1633–1645 (2011)

    Article  Google Scholar 

  13. Kumar, S.: Neural Networks: A Classroom Approach. Tata McGraw-Hill Education, (2004)

  14. Liu, L., Tang, W., Buttler, D., Pu, C.: Information monitoring on the web: a scalable solution. World Wide Web 5(4), 263–304 (2002)

    Article  Google Scholar 

  15. Liu, H., Yan, J., Zhang, D.: Three-dimensional surface registration: a neural network strategy. Neurocomputing 70(1–3), 597–602 (2006)

    Article  Google Scholar 

  16. Liu, H., Yan, J., Zhang, D.: A neural network strategy for 3d surface registration. In: The 6th international conference on Computational Science and Its Applications - Volume Part I, pp. 528-536 (2006)

  17. Mostafa, M.G., Farag, A.A., Essock, E.: Multimodality image registration and fusion using neural network. In: The Third International Conference on Information Fusion 2000, pp. WeD3-3-WeD3-9

  18. Padia, C., Pears, N.: A review and characterization of ICP-based symmetry plane localisation in 3D face data. In: Technical Report, pp. 1–27 (2011)

  19. Pan, G., Han, S., Wu, Z., Wang, Y.: Super-resolution of 3d face. In: The 9th European conference on Computer Vision (ECCV), pp. 389–401 (2006)

  20. Poon, B., Amin, M.A., Yan, H.: Performance evaluation and comparison of PCA Based human face recognition methods for distorted images. Int. J. Mach. Learn. Cybern. 2(4), 245–259 (2011)

    Article  Google Scholar 

  21. Qian, J., Mitsa, T., Hoffman, E.A.: Contour/Surface Registration Using a Physically Deformable Model. In: The 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96), pp. 114–122 (1996)

  22. Ren, Y., Anderson, K., Iftekharuddin, K., Kim, P., White, E.: Pose invariant face recognition using Cellular Simultaneous Recurrent Networks In: International Joint Conference on Neural Networks, pp. 2634–2641 (2009)

  23. Rowley, H.A., Baluja, S., Kanade, T.: Neural network-based face detection. IEEE Transactions Pattern Analysis & Machine Intelligence 20(1), 23–38 (1998)

    Article  Google Scholar 

  24. Savran, A., Sankur, B.: Non-rigid registration of 3D surfaces by deformable 2D triangular meshes. 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2008)

  25. Shang, L., Lv, J.C., Yi, Z.: Rigid medical image registration using PCA neural network. Neurocompution 69(13–15), 1717–1722 (2006)

    Article  Google Scholar 

  26. Sidorov, K.A., Richmond, S., Marshall, D.: Efficient groupwise non-rigid registration of textured surfaces. In: CVPR ‘11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2401–2408 (2011)

  27. Szeptycki, P., Ardabilian, M., Chen, L.: A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking. In: The 3rd International Conference on Biometrics: Theory, Applications, and Systems ( BTAS ‘09), pp. 1–6 (2009)

  28. Tolba, A.S., El-Baz, A.H., El-Harby, A.A.: Face recognition: a literature review. International Journal of Information and Communication Engineering 2(2), 88–103 (2006)

    Google Scholar 

  29. Tong, D.L., Mintram, R.: Genetic Algorithm-Neural Network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection. Int. J. Mach. Learn. Cybern. 1(1–4), 75–87 (2010)

    Article  Google Scholar 

  30. Tsang, E.C.C., Wang, X.Z., Yeung, D.S.: Improving learning accuracy of fuzzy decision trees by hybrid neural networks. IEEE Trans. Fuzzy Syst. 8(5), 601–614 (2000)

    Article  Google Scholar 

  31. Wagner, A., Wright, J., Ganesh, A., Zhou, Z., Mobahi, H., Ma, Y.: Toward a practical face recognition system: robust alignment and illumination by sparse representation. IEEE Transactions Pattern Analysis & Machine Intelligence 34(2), 372–386 (2012)

    Article  Google Scholar 

  32. Wang, S., Lei, S., Chang, F.: Image registration based on neural network. In: International Conference on Information Technology and Applications in Biomedicine, 2008 (ITAB 2008). 2008, pp. 74–77

  33. Warfield, S.K., Rexilius, J., Huppi, P.S., etc.: A Binary Entropy Measure to Assess Nonrigid Registration Algorithms. In: The 4th International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 266–274 (2001)

  34. Xu, A., Guo, P.: Image registration with regularized neural network. In: The 13th international conference on Neural Information Processing, pp. 286–293 (2006)

  35. Xu, Y., Zhang, Y., Zhao, J.-M.: An Improved Face Recognition Method Using Global Filled Function. In: Fourth International Conference on Natural Computation, pp. 291-295 (2008)

  36. Yeung, D., Wing, N., Wang, D., Tsang, E., Wang, X.: Localized generalization error model and its application to architecture selection for radial basis function neural network. IEEE Transactions on Neural Networks 18(5), 1294–1305 (2007)

    Article  Google Scholar 

  37. Zeng, W., Gu, X.D.: Registration for 3D surfaces with large deformations using quasi-conformal curvature flow. In: Computer Vision and Pattern Recognition (CVPR), pp. 2457–2464 (2011)

  38. Zeng, W., Zeng, Y., Wang, Y., Yin, X., Gu, X., Samaras, D.: 3D non-rigid surface matching and registration based on holomorphic differentials. In: The 10th European Conference on Computer Vision (ECCV), pp. 1–14 (2008)

  39. Zhang, J., Ge, Y., Ong, S.H., Chui, C.K., Teoh, S.H., Yan, C.H.: Rapid surface registration of 3D volumes using a neural network approach. Image and Vision Computing 26(2), 201–210 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Sciences, Universiti Sains Malaysia, Penang, 11800, Malaysia

    Junfen Chen, Iman Yi Liao, Bahari Belaton & Munir Zaman

Authors
  1. Junfen Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Iman Yi Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bahari Belaton
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Munir Zaman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junfen Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, J., Liao, I.Y., Belaton, B. et al. A neural network-based point registration method for 3D rigid face image. World Wide Web 18, 197–214 (2015). https://doi.org/10.1007/s11280-013-0213-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-013-0213-9

Keywords

Search

Navigation