Skip to main content
SpringerLink
Log in

3D Face Recognition Based on Local Shape Patterns and Sparse Representation Classifier

  • Conference paper
Advances in Multimedia Modeling (MMM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6523))

Included in the following conference series:

Abstract

In recent years, 3D face recognition has been considered as a major solution to deal with these unsolved issues of reliable 2D face recognition, i.e. illumination and pose variations. This paper focuses on two critical aspects of 3D face recognition: facial feature description and classifier design. To address the former one, a novel local descriptor, namely Local Shape Patterns (LSP), is proposed. Since LSP operator extracts both differential structure and orientation information, it can describe local shape attributes comprehensively. For the latter one, Sparse Representation Classifier (SRC) is applied to classify these 3D shape-based facial features. Recently, SRC has been attracting more and more attention of researchers for its powerful ability on 2D image-based face recognition. This paper continues to investigate its competency in shape-based face recognition. The proposed approach is evaluated on the IV2 3D face database containing rich facial expression variations, and promising experimental results are achieved which prove its effectiveness for 3D face recognition and insensitiveness to expression changes.

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

Access this chapter

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 99.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition: Special Issue on Image- and Video-based Biometrics. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 4–20 (2004)

    Article  Google Scholar 

  2. Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face Recognition: A Literature Survey. ACM Computing Survey 35(4), 399–458 (2003)

    Article  Google Scholar 

  3. Bowyer, K.W., Chang, K., Flynn, P.J.: A Survey of Approaches and Challenges in 3D and Multi-modal 3D+2D Face Recognition. Computer Vision and Image Understanding 101(1), 1–15 (2006)

    Article  Google Scholar 

  4. Abate, A.F., Nappi, M., Riccio, D., Sabatino, G.: 2D and 3D Face Recognition: A Survey. Pattern Recognition Letters 28(14), 1885–1906 (2007)

    Article  Google Scholar 

  5. Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face Recognition Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)

    Article  Google Scholar 

  6. Scheenstra, A., Ruifrok, A., Veltkamp, R.C.: A Survey of 3D Face Recognition Methods. In: International Conference on Audio- and Video- based Biometric Person Authentication (2005)

    Google Scholar 

  7. Hadid, A., Pietikäinen, M., Ahonen, T.: A Discriminative Feature Space for Detecting and Recognizing Faces. In: IEEE International Conference on Computer Vision and Pattern Recognition (2004)

    Google Scholar 

  8. Koenderink, J.J., Doorn, A.J.: Surface Shape and Curvature Scales. Image and Vision Computing 10(8), 557–565 (1992)

    Article  Google Scholar 

  9. Ojala, T., Pietikäinen, M., Maenpaa, T.: Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns. IEEE Trans. Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)

    Article  MATH  Google Scholar 

  10. Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Trans. Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  11. Lu, X., Jain, A.K., Colbry, D.: Matching 2. 5D Face Scans to 3D Models. IEEE Trans. Pattern Analysis and Machine Intelligence 28(1), 31–43 (2006)

    Article  Google Scholar 

  12. Kakadiaris, I.A., Passalis, G., Toderici, G., Murtuza, M.N., Lu, Y., Karampatziakis, N., Theoharis, T.: Three-dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach. IEEE Trans. Pattern Analysis and Machine Intelligence 29(4), 640–649 (2007)

    Article  Google Scholar 

  13. Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Three-dimensional Face Recognition. International Journal of Computer Vision 64(1), 5–30 (2005)

    Article  Google Scholar 

  14. Chua, C., Han, F., Ho, Y.K.: 3D Human Face Recognition using Point Signature. In: IEEE International Conference on Automatic Face and Gesture Recognition (2000)

    Google Scholar 

  15. Mian, A.S., Bennamoun, M., Owens, R.: Keypoint Detection and Local Feature Matching for Textured 3D Face Recognition. International Journal of Computer Vision 79(1), 1–12 (2008)

    Article  Google Scholar 

  16. Ouji, K., Amor, B.B., Ardabilian, M., Chen, L., Ghorbel, F.: 3D Face Recognition using Region-ICP and Geodesic Coupled Approach. In: Conference on International Multimedia Modeling (2009)

    Google Scholar 

  17. Mian, A.S., Bennamoun, M., Owens, R.: Region-based Matching for Robust 3D Face Recognition. In: Conference on British Machine Vision (2005)

    Google Scholar 

  18. Huang, J., Heisele, B., Blanz, V.: Component-based Face Recognition with 3D Morphable Models. In: International Conference on Audio- and Video- Based Biometric Person Authentication (2003)

    Google Scholar 

  19. Amor, B.B., Ardabilian, M., Chen, L.: Enhancing 3D Face Recognition by Mimic Segmentation. In: International Conference on Intelligent Systems Design and Applications (2006)

    Google Scholar 

  20. Li, S.Z., Zhao, C., Ao, M., Lei, Z.: Learning to Fuse 3D+2D based Face Recognition at Both Feature and Decision Levels. In: International Workshop on Analysis and Modeling of Faces and Gesture (2005)

    Google Scholar 

  21. Huang, Y., Wang, Y., Tan, T.: Combining Statistics of Geometrical and Correlative Features for 3D Face Recognition. In: Conference on British Machine Vision (2006)

    Google Scholar 

  22. Ahonen, T., Hadid, A., Pietikäinen, M.: Face Recognition with Local Binary Patterns. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 469–481. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  23. Chen, J., Shan, S., Zhao, G., Chen, X., Gao, W., Pietikäinen, M.: A Robust Descriptor based on Weber’s Law. In: IEEE International Conference on Computer Vision and Pattern Recognition (2008)

    Google Scholar 

  24. Huang, K., Aviyente, S.: Sparse Representation for Signal Classification. In: Annual Conference on Neural Information Processing Systems (2006)

    Google Scholar 

  25. Wright, J., Yang, A., Ganesh, A., Sastry, S., Ma, Y.: Robust Face Recognition via Sparse Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(2), 210–227 (2009)

    Article  Google Scholar 

  26. Colineau, J., D’Hose, J., Amor, B.B., Ardabilian, M., Chen, L., Dorizzi, B.: 3D Face Recognition Evaluation on Expressive Faces using the IV2 Database. In: International Conference on Advanced Concepts for Intelligent Vision Systems (2008)

    Google Scholar 

  27. Samir, C., Srivastava, A., Daoudi, M.: Three-dimensional Face Recognition using Shapes of Facial Curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(11), 1858–1863 (2006)

    Article  Google Scholar 

  28. Tanaka, H.T., Ikeda, M., Chiaki, H.: Curvature-based Face Surface Recognition using Spherical Correlation — Principal Directions for Curved Object Recognition. In: IEEE International Conference on Automatic Face and Gesture Recognition (1998)

    Google Scholar 

  29. Xu, C., Li, S.Z., Tan, T., Quan, L.: Automatic 3D Face Recognition from Depth and Intensity Gabor Features. Pattern Recognition 42(9), 1895–1905 (2009)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LIRIS Laboratory, CNRS 5205, Ecole Centrale Lyon, 69134, Lyon, France

    Di Huang, Karima Ouji, Mohsen Ardabilian & Liming Chen

  2. School of Computer Science and Engineering, Beihang University, 100091, Beijing, China

    Yunhong Wang

Authors
  1. Di Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karima Ouji
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohsen Ardabilian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yunhong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liming Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. National Taiwan Ocean University, Keelung, Taiwan

    Kuo-Tien Lee  & Jun-Wei Hsieh  & 

  2. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Hsiang Tsai

  3. Academia Sinica, Taipei, Taiwan

    Hong-Yuan Mark Liao

  4. Cornell University, Ithaca, NY, USA

    Tsuhan Chen

  5. National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan

    Chien-Cheng Tseng

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Huang, D., Ouji, K., Ardabilian, M., Wang, Y., Chen, L. (2011). 3D Face Recognition Based on Local Shape Patterns and Sparse Representation Classifier. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17832-0_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17831-3

  • Online ISBN: 978-3-642-17832-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation