Precise 3D Pose Estimation of Human Faces

Ákos Pernek, Levente Hajder

2014

Abstract

Robust human face recognition is one of the most important open tasks in computer vision. This study deals with a challenging subproblem of face recognition: the aim of the paper is to give a precise estimation for the 3D head pose. The main contribution of this study is a novel non-rigid Structure from Motion (SfM) algorithm which utilizes the fact that the human face is quasi-symmetric. The input of the proposed algorithm is a set of tracked feature points of the face. In order to increase the precision of the head pose estimation, we improved one of the best eye corner detectors and fused the results with the input set of feature points. The proposed methods were evaluated on real and synthetic face sequences. The real sequences were captured using regular (low-cost) web-cams.

References

  1. Arun, K. S., Huang, T. S., and Blostein, S. D. (1987). Leastsquares fitting of two 3-D point sets. PAMI, 9(5):698- 700.
  2. Cootes, T., Taylor, C., Cooper, D. H., and Graham, J. (1992). Training models of shape from sets of examples. In BMVC, pages 9-18.
  3. Cootes, T. F., Edwards, G. J., and Taylor, C. J. (1998). Active appearance models. In PAMI, pages 484-498. Springer.
  4. Cristinacce, D. and Cootes, T. F. (2006). Feature detection and tracking with constrained local models. In BMVC, pages 929-938.
  5. Hajder, L., Pernek, Í ., and Kazó, C. (2011). Weakperspective structure from motion by fast alternation. The Visual Computer, 27(5):387-399.
  6. Harris, C. and Stephens, M. (1988). A combined corner and edge detector. In Fourth Alvey Vision Conference, pages 147-151.
  7. Hartley, R. I. and Zisserman, A. (2003). Multiple View Geometry in Computer Vision. Cambridge University Press.
  8. He, Z., Tan, T., Sun, Z., and Qiu, X. (2009). Towards accurate and fast iris segmentation for iris biometrics. PAMI, 31(9):1670-1684.
  9. Jankó, Z. and Hajder, L. (2012). Improving humancomputer interaction by gaze tracking. In Cognitive Infocommunications, pages 155-160.
  10. Matthews, I. and Baker, S. (2004). Active appearance models revisited. IJCV, 60(2):135-164.
  11. P. Paysan and R. Knothe and B. Amberg and S. Romdhani and T. Vetter (2009). A 3D Face Model for Pose and Illumination Invariant Face Recognition. AVSS.
  12. Pernek, Í ., Hajder, L., and Kazó, C. (2008). Metric reconstruction with missing data under weak perspective. In BMVC. British Machine Vision Association.
  13. Santos, G. M. M. and Proenc¸a, H. (2011). A robust eyecorner detection method for real-world data. In IJCB, pages 1-7. IEEE.
  14. Saragih, J. M., Lucey, S., and Cohn, J. (2009). Face alignment through subspace constrained mean-shifts. In ICCV.
  15. Tan, T., He, Z., and Sun, Z. (2010). Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition. IVC, 28(2):223-230.
  16. Tomasi, C. and Kanade, T. (1992). Shape and Motion from Image Streams under orthography: A factorization approach. IJCV, 9:137-154.
  17. Viola, P. and Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. CVPR, 1:I-511- I-518 vol.1.
  18. Wang, Y., Lucey, S., and Cohn, J. (2008). Enforcing convexity for improved alignment with constrained local models. In CVPR.
  19. Xiao, J., Chai, J.-X., and Kanade, T. (2004). A Closed-Form Solution to Non-rigid Shape and Motion Recovery. In ECCV, pages 573-587.
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Paper Citation


in Harvard Style

Pernek Á. and Hajder L. (2014). Precise 3D Pose Estimation of Human Faces . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 618-625. DOI: 10.5220/0004741706180625


in Bibtex Style

@conference{visapp14,
author={Ákos Pernek and Levente Hajder},
title={Precise 3D Pose Estimation of Human Faces},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={618-625},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004741706180625},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Precise 3D Pose Estimation of Human Faces
SN - 978-989-758-009-3
AU - Pernek Á.
AU - Hajder L.
PY - 2014
SP - 618
EP - 625
DO - 10.5220/0004741706180625