Skip to main content
SpringerLink
Log in

Joint Face Detection and Initialization for Face Alignment

  • Conference paper
  • First Online:
MultiMedia Modeling (MMM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10132))

Included in the following conference series:

  • 3294 Accesses

Abstract

This paper presents a joint face detection and initialization method for cascaded face alignment. Unlike existing methods which consider face detection and initialization as separate steps, we concurrently obtain a bounding box and initial facial landmarks (i.e. shape) in one step, yielding better accuracy and efficiency. Specifically, each image region is represented using shape-indexed features [6] derived from different head poses. A multipose face detector is trained: regions whose shapes are roughly aligned with faces can have a good feature representation and are utilized as positive samples, otherwise are considered as negative samples. During the face detection phase, initial landmarks can be explicitly placed on the detected faces according to the corresponding shape-indexed features. To accelerate our method, an ultrafast face proposal method based on face probability map (FPM) and boosted classifiers. Experimental results on public datasets demonstrate superior efficiency and robustness to existing initialization schemes and great accuracy improvement for the cascaded face alignment.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Asthana, A., Zafeiriou, S., Cheng, S., Pantic, M.: Robust discriminative response map fitting with constrained local models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3444–3451 (2013)

    Google Scholar 

  2. Asthana, A., Zafeiriou, S., Cheng, S., Pantic, M.: Incremental face alignment in the wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1859–1866 (2014)

    Google Scholar 

  3. Baltrušaitis, T., Robinson, P., Morency, L.-P.: Continuous conditional neural fields for structured regression. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8692, pp. 593–608. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10593-2_39

    Google Scholar 

  4. Burgos-Artizzu, X., Perona, P., Dollár, P.: Robust face landmark estimation under occlusion. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1513–1520 (2013)

    Google Scholar 

  5. Cao, C., Weng, Y., Lin, S., Zhou, K.: 3D shape regression for real-time facial animation. ACM Trans. Graph. (TOG) 32(4), 41 (2013)

    Article  MATH  Google Scholar 

  6. Cao, X., Wei, Y., Wen, F., Sun, J.: Face alignment by explicit shape regression. Int. J. Comput. Vis. 107(2), 177–190 (2014)

    Article  MathSciNet  Google Scholar 

  7. Chen, C., Dantcheva, A., Ross, A.: Automatic facial makeup detection with application in face recognition. In: 2013 International Conference on Biometrics (ICB), pp. 1–8. IEEE (2013)

    Google Scholar 

  8. Chen, D., Ren, S., Wei, Y., Cao, X., Sun, J.: Joint cascade face detection and alignment. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 109–122. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10599-4_8

    Google Scholar 

  9. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 6, 681–685 (2001)

    Article  Google Scholar 

  10. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models-their training and application. Comput. Vis. Image Underst. 61(1), 38–59 (1995)

    Article  Google Scholar 

  11. Huang, C., Ai, H., Li, Y., Lao, S.: High-performance rotation invariant multiview face detection. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 671–686 (2007)

    Article  Google Scholar 

  12. Huttenlocher, D.P., Klanderman, G.A., Rucklidge, W.J.: Comparing images using the hausdorff distance. IEEE Trans. Pattern Anal. Mach. Intell. 15(9), 850–863 (1993)

    Article  Google Scholar 

  13. Jones, M., Viola, P.: Fast multi-view face detection. Mitsubishi Electr. Res. Lab TR-20003-96 3, 14 (2003)

    Google Scholar 

  14. Kemelmacher-Shlizerman, I., Suwajanakorn, S., Seitz, S.M.: Illumination-aware age progression. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3334–3341. IEEE (2014)

    Google Scholar 

  15. Li, S.Z., Zhu, L., Zhang, Z.Q., Blake, A., Zhang, H.J., Shum, H.: Statistical learning of multi-view face detection. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 67–81. Springer, Heidelberg (2002). doi:10.1007/3-540-47979-1_5

    Chapter  Google Scholar 

  16. Liang, L., Xiao, R., Wen, F., Sun, J.: Face alignment via component-based discriminative search. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008. LNCS, vol. 5303, pp. 72–85. Springer, Heidelberg (2008). doi:10.1007/978-3-540-88688-4_6

    Chapter  Google Scholar 

  17. Liu, L., Xing, J., Liu, S., Xu, H., Zhou, X., Yan, S.: Wow! you are so beautiful today!. ACM Trans. Multimedia Comput. Commun. Appl. (TOMM) 11(1s), 20 (2014)

    Google Scholar 

  18. Matthews, I., Baker, S.: Active appearance models revisited. Int. J. Comput. Vis. 60(2), 135–164 (2004)

    Article  Google Scholar 

  19. Ren, S., Cao, X., Wei, Y., Sun, J.: Face alignment at 3000 FPS via regressing local binary features. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1685–1692 (2014)

    Google Scholar 

  20. Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., Pantic, M.: 300 faces in-the-wild challenge: the first facial landmark localization challenge. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 397–403 (2013)

    Google Scholar 

  21. Tzimiropoulos, G., Pantic, M.: Gauss-Newton deformable part models for face alignment in-the-wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1851–1858 (2014)

    Google Scholar 

  22. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)

    Article  Google Scholar 

  23. Wu, B., Ai, H., Huang, C., Lao, S.: Fast rotation invariant multi-view face detection based on real Adaboost. In: Proceedings of 2004 Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 79–84. IEEE (2004)

    Google Scholar 

  24. Xiong, X., Torre, F.: Supervised descent method and its applications to face alignment. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 532–539 (2013)

    Google Scholar 

  25. Yang, H., He, X., Jia, X., Patras, I.: Robust face alignment under occlusion via regional predictive power estimation. IEEE Trans. Image Process. 24(8), 2393–2403 (2015)

    Article  MathSciNet  Google Scholar 

  26. Yang, H., Mou, W., Zhang, Y., Patras, I., Gunes, H., Robinson, P.: Face alignment assisted by head pose estimation. In: Xie, X., Jones, M.W., Tam, G.K.L. (eds.) Proceedings of the British Machine Vision Conference (BMVC), pp. 130.1–130.13. BMVA Press. https://dx.doi.org/10.5244/C.29.130

  27. Zhang, J., Shan, S., Kan, M., Chen, X.: Coarse-to-fine auto-encoder networks (CFAN) for real-time face alignment. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8690, pp. 1–16. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10605-2_1

    Google Scholar 

  28. Zhang, Z., Luo, P., Loy, C.C., Tang, X.: Facial landmark detection by deep multi-task learning. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 94–108. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10599-4_7

    Google Scholar 

  29. Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: a literature survey. ACM Comput. Surv. (CSUR) 35(4), 399–458 (2003)

    Article  Google Scholar 

  30. Zhu, S., Li, C., Change Loy, C., Tang, X.: Face alignment by coarse-to-fine shape searching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4998–5006 (2015)

    Google Scholar 

  31. Zhu, X., Ramanan, D.: Face detection, pose estimation, and landmark localization in the wild. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2879–2886. IEEE (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

    Zhiwei Wang & Xin Yang

Authors
  1. Zhiwei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhiwei Wang .

Editor information

Editors and Affiliations

  1. CNRS–IRISA, Rennes, France

    Laurent Amsaleg

  2. Reykjavík University, Reykjavik, Iceland

    Gylfi Þór Guðmundsson

  3. Dublin City University, Dublin, Ireland

    Cathal Gurrin

  4. Reykjavik University, Reykjavik, Ireland

    Björn Þór Jónsson

  5. National Institute of Informatics, Tokyo, Japan

    Shin’ichi Satoh

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Wang, Z., Yang, X. (2017). Joint Face Detection and Initialization for Face Alignment. In: Amsaleg, L., Guðmundsson, G., Gurrin, C., Jónsson, B., Satoh, S. (eds) MultiMedia Modeling. MMM 2017. Lecture Notes in Computer Science(), vol 10132. Springer, Cham. https://doi.org/10.1007/978-3-319-51811-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-51811-4_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51810-7

  • Online ISBN: 978-3-319-51811-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation