Skip to main content
SpringerLink
Log in

An Expression Deformation Approach to Non-rigid 3D Face Recognition

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

The accuracy of non-rigid 3D face recognition approaches is highly influenced by their capacity to differentiate between the deformations caused by facial expressions from the distinctive geometric attributes that uniquely characterize a 3D face, interpersonal disparities. We present an automatic 3D face recognition approach which can accurately differentiate between expression deformations and interpersonal disparities and hence recognize faces under any facial expression. The patterns of expression deformations are first learnt from training data in PCA eigenvectors. These patterns are then used to morph out the expression deformations. Similarity measures are extracted by matching the morphed 3D faces. PCA is performed in such a way it models only the facial expressions leaving out the interpersonal disparities. The approach was applied on the FRGC v2.0 dataset and superior recognition performance was achieved. The verification rates at 0.001 FAR were 98.35% and 97.73% for scans under neutral and non-neutral expressions, respectively.

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

Access this article

Log in via an institution

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

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

    Article  Google Scholar 

  • Blanz, V., & Vetter, T. (1999). A morphable model for the synthesis of 3D faces. In Proceedings of siggraph.

  • Blanz, V., Basso, C., Poggio, T., & Vetter, T. (2003). Reanimating faces in images and video. In Computer graphics forum.

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

    Article  Google Scholar 

  • Bowyer, K., Chang, K., & Flynn, P. (2006). A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Journal of Computer Vision and Image Understanding, 101(1), 1–15.

    Article  Google Scholar 

  • Bronstein, A., Bronstein, M., & Kimmel, R. (2005). Three-dimensional face recognition. International Journal on Computer Vision, 64(1), 5–30.

    Article  Google Scholar 

  • Bronstein, A., Bronstein, M., & Kimmel, R. (2006a). Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching. Proceedings National Academy of Sciences (PNAS), 103(5), 1168–1172.

    Article  MATH  MathSciNet  Google Scholar 

  • Bronstein, A., Bronstein, M., & Kimmel, R. (2006b). Robust expression-invariant face recognition from partially missing data. In Proceedings of the European conference on computer vision.

  • Chang, K., Bowyer, K., & Flynn, P. (2005a). Adaptive rigid multi-region selection for handling expression variation in 3D face recognition. In IEEE conference on computer vision and pattern recognition.

  • Chang, K., Bowyer, K., & Flynn, P. (2005b). An evaluation of multimodal 2D + 3D face biometrics. IEEE Transaction on Pattern Analysis and Machine Intelligence, 27(4), 619–624.

    Article  Google Scholar 

  • Chang, K., Bowyer, K., & Flynn, P. (2006). Multiple nose region matching for 3D face recognition under varying facial expression. IEEE Transaction on Pattern Analysis and Machine Intelligence, 28(10), 1695–1700.

    Article  Google Scholar 

  • Chen, Y., & Medioni, G. (1991). Object modeling by registration of multiple range images. In IEEE international conference on robotics and automation (Vol. 3, pp. 2724–2729).

  • Chua, C., Han, F., & Ho, Y. (2000). 3D human face recognition using point signature. In IEEE conference on automatic face and gesture recognition.

  • Faltemier, T., Bowyer, K., & Flynn, P. (2007). Using a multi-instance enrollment representation to improve 3D face recognition. In IEEE conference on biometrics: theory, applications and systems (BTAS).

  • Gokberk, B., Salah, A., & Akarun, L. (2005). Rank-based decision fusion for 3D shape-based face recognition. In International conference on audio-based biometric person authentication.

  • Greenspan, M., & Yurick, M. (2003) Approximate K-D tree search for efficient ICP. In IEEE international conference on recent advances in 3D digital imaging and modeling.

  • Hesher, C., Srivastava, A., & Erlebacher, G. (2003). A novel technique for face recognition using range images. In International symposium on signal processing and its applications.

  • Husken, M., Brauckmann, M., Gehlen, S., & Malsburg, C. (2005). Strategies and benefits of fusion of 2D and 3D face recognition. In IEEE workshop on face recognition grand challenge experiments.

  • Jollife, I. (1986). Principal component analysis. Berlin: Springer.

    Google Scholar 

  • Kakadiaris, I., Passalis, G., Toderici, G., Murtuza, M., Lu, Y., Karampatziakis, N., & Theoharis, T. (2007). Three-dimensional face recognition in the presence of facial expressions: an annotated deformable model approach. IEEE Transaction on Pattern Analysis and Machine Intelligence, 29(4), 640–649.

    Article  Google Scholar 

  • Kirby, M., & Sirovich, L. (1990). Application of the KL procedure for characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(1), 103–108.

    Article  Google Scholar 

  • Li, X., & Zhang, H. (2007). Adapting geometric attributes for expression-invariant 3D face recognition. In IEEE conference on shape modeling and applications.

  • Lu, X., Hsu, R., Jain, A., Kamgar-Parsi, B., & Kamgar, B. (2004). Face recognition with 3D model-based synthesis. In Proceedings of the international conference on biometric authentication.

  • Lu, X., & Jain, A. (2008). Deformation modeling for robust 3D face matching. IEEE Transaction on Pattern Analysis and Machine Intelligence, 30(8), 1346–1357.

    Article  Google Scholar 

  • Lu, X., Jain, A., & Colbry, D. (2006). Matching 2.5D face scans to 3D models. IEEE Transaction on Pattern Analysis and Machine Intelligence, 28(1), 31–43.

    Article  Google Scholar 

  • Maurer, T., Guigonis, D., Maslov, I., Pesenti, B., Tsaregorodtev, A., West, D., & Medioni, G. (2005). Performance of geometrix activeID 3D face recognition engine on the FRGC data. In IEEE conference on computer vision and pattern recognition.

  • Mian, A., Bennamoun, M., & Owens, R. (2006). Automatic 3D face detection, normalization and recognition. In International symposium on 3D data processing, visualization and transmission (3DPVT).

  • Mian, A., Bennamoun, M., & Owens, R. (2007). An efficient multimodal 2D–3D hybrid approach to automatic face recognition. IEEE Transaction on Pattern Analysis and Machine Intelligence, 29(11), 1927–1943.

    Article  Google Scholar 

  • Mian, A., Bennamoun, M., & Owens, R. (2008). Keypoint detection and local feature matching for textured 3D face recognition. International Journal of Computer Vision.

  • Pan, G., Han, S., Wu, Z., & Wang, Y. (2005). 3D face recognition using mapped depth images. In IEEE workshop on face recognition grand challenge experiments.

  • Parke, P., & Waters, K. (1996). Computer facial animation. Natik: A.K. Peters Ltd.

    Google Scholar 

  • Passalis, G., Kakadiaris, I., & Theoharis, T. (2007). Intra-class retrieval of non-rigid 3D objects: application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(2), 218–229.

    Article  Google Scholar 

  • Passalis, G., Kakadiaris, I., Theoharis, T., Tederici, G., & Murtaza, N. (2005). Evaluation of 3D face recognition in the presence of facial expressions: an annotated deformable model approach. In FRGC workshop, in IEEE conference on computer vision and pattern recognition.

  • Phillips, P., Flynn, P., Scruggs, T., Bowyer, K., Chang, J., Hoffman, K., Marques, J., Min, J., & Worek, W. (2005). Overview of the face recognition grand challenge. In IEEE conference on computer vision and pattern recognition.

  • Ramachandran, M., Zhou, S., Jhalani, D., & Chellappa, R. (2005). A method for converting a smiling face to a neutral face with applications to face recognition. In IEEE conference on acoustics, speech, and signal processing.

  • Russ, T., Boehnen, C., & Peters, T. (2006). 3D face recognition using 3D alignment for PCA. In IEEE conference on computer vision and pattern recognition.

  • Rydfalk, M. (1987). CANDIDE, a parameterized face (Report No. LiTH-ISY-I-866). Consulting Psychologists Press Inc.

  • Samir, C., Srivastava, A., & Daoudi, M. (2006). Three-dimensional face recognition using shapes of facial curves. IEEE Transaction on Pattern Analysis and Machine Intelligence, 28(11), 1858–1863.

    Article  Google Scholar 

  • Sirovich, L., & Kirby, M. (1987). Low-dimensional procedure for characterization of human faces. Journal of the Optical Society of America, 2, 519–524.

    Google Scholar 

  • Turk, M., & Pentland, A. (1991). Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1), 71–86.

    Article  Google Scholar 

  • Wang, Y., Pan, G., & Wu, Z. (2007). 3D face recognition in the presence of expression: a guidance-based constraint deformation approach constraint deformation approach. In IEEE conference on computer vision and pattern recognition.

  • Zhao, W., Chellappa, R., Phillips, P., & Rosenfeld, A. (2003). Face recognition: a literature survey. ACM Computing Surveys, 35(4), 399–458.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Software Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia

    F. Al-Osaimi, M. Bennamoun & A. Mian

Authors
  1. F. Al-Osaimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Bennamoun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Mian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to F. Al-Osaimi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Al-Osaimi, F., Bennamoun, M. & Mian, A. An Expression Deformation Approach to Non-rigid 3D Face Recognition. Int J Comput Vis 81, 302–316 (2009). https://doi.org/10.1007/s11263-008-0174-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11263-008-0174-0

Keywords

Search

Navigation