Head Yaw Estimation using Frontal Face Detector

José Mennesson, Afifa Dahmane, Taner Danisman, Ioan Marius Bilasco

2016

Abstract

Detecting accurately head orientation is an important task in systems relying on face analysis. The estimation of the horizontal rotation of the head (yaw rotation) is a key step in detecting the orientation of the face. The purpose of this paper is to use a well-known frontal face detector in order to estimate head yaw angle. Our approach consists in simulating 3D head rotations and detecting face using a frontal face detector. Indeed, head yaw angle can be estimated by determining the angle at which the 3D head must be rotated to be frontal. This approach is model-free and unsupervised (except the generic learning step of VJ algorithm). The method is experimented and compared with the state-of-the-art approaches using continuous and discrete protocols on two well-known databases : FacePix and Pointing04.

References

  1. Aissaoui, A., Martinet, J., and Djeraba, C. (2014). Rapid and accurate face depth estimation in passive stereo systems. Multimedia Tools and Applications, 72(3):2413-2438.
  2. Auguste, R. (2014). Racv library can be downloaded from. https://github.com/auguster/libRacv/.
  3. Balasubramanian, V., Ye, J., and Panchanathan, S. (2007). Biased manifold embedding: A framework for person-independent head pose estimation. In CVPR, 2007. IEEE Conference on, pages 1-7.
  4. Black, J., Gargesha, M., Kahol, K., Kuchi, P., and Panchanathan, S. (2002). A framework for performance evaluation of face recognition algorithms. In ITCOM, Internet Multimedia Systems II, Boston.
  5. Blanz, V. and Vetter, T. (1999). A morphable model for the synthesis of 3d faces. In Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 7899, pages 187-194, New York, NY, USA. ACM Press/Addison-Wesley Publishing Co.
  6. Dahmane, A., Larabi, S., Bilasco, I. M., and Djeraba, C. (2014). Head Pose Estimation Based on Face Symmetry Analysis. Signal, Image and Video Processing.
  7. Danisman, T. and Bilasco, I. M. (2015). In-plane face orientation estimation in still images. Multimedia Tools and Applications, pages 1-31.
  8. Gourier, N., Hall, D., and Crowley, J. L. (2004). Estimating Face Orientation from Robust Detection of Salient Facial Features. In Proceedings of Pointing 2004, ICPR, International Workshop on Visual Observation of Deictic Gestures.
  9. Gourier, N., Maisonnasse, J., Hall, D., and Crowley, J. (2007). Head pose estimation on low resolution images. In Stiefelhagen, R. and Garofolo, J., editors, Multimodal Technologies for Perception of Humans, volume 4122 of LNCS, pages 270-280. Springer Berlin Heidelberg.
  10. Ji, H., Liu, R., Su, F., Su, Z., and Tian, Y. (2011). Robust head pose estimation via convex regularized sparse regression. In ICIP, 2011, pages 3617-3620.
  11. Jung, S.-U. and Nixon, M. (2010). On using gait biometrics to enhance face pose estimation. In Biometrics: Theory Applications and Systems, 2010 Fourth IEEE International Conference on, pages 1-6.
  12. Kwon, O., Chun, J., and Park, P. (2006). Cylindrical modelbased head tracking and 3d pose recovery from sequential face images. In Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01, pages 135-139, Washington, DC, USA. IEEE Computer Society.
  13. Liu, X., Lu, H., and Li, W. (2010). Multi-manifold modeling for head pose estimation. In ICIP, 2010, pages 3277-3280.
  14. Murphy-Chutorian, E. and Trivedi, M. (2009). Head pose estimation in computer vision: A survey. PAMI, IEEE Transactions on, 31(4):607-626.
  15. Narayanan, A., Kaimal, R., and Bijlani, K. (2014). Yaw estimation using cylindrical and ellipsoidal face models. Intelligent Transportation Systems, IEEE Transactions on, 15(5):2308-2320.
  16. Rother, C., Kolmogorov, V., and Blake, A. (2004). ”grabcut”: Interactive foreground extraction using iterated graph cuts. ACM Trans. Graph., 23(3):309-314.
  17. Stiefelhagen, R. (2004). Estimating head pose with neural nnetwork - results on the pointing04 icpr workshop evaluation data. In Pointing 2004 Workshop: Visual Observation of Deictic Gestures.
  18. Tu, J., Fu, Y., Hu, Y., and Huang, T. (2007). Evaluation of head pose estimation for studio data. In Stiefelhagen, R. and Garofolo, J., editors, Multimodal Technologies for Perception of Humans, volume 4122 of LNCS, pages 281-290. Springer Berlin Heidelberg.
  19. Viola, P. and Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. pages 511-518.
  20. Zaidan, A., Ahmad, N., Karim, H. A., Larbani, M., Zaidan, B., and Sali, A. (2014). Image skin segmentation based on multi-agent learning bayesian and neural network. Engineering Applications of Artificial Intelligence, 32:136 - 150.
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Paper Citation


in Harvard Style

Mennesson J., Dahmane A., Danisman T. and Bilasco I. (2016). Head Yaw Estimation using Frontal Face Detector . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 517-524. DOI: 10.5220/0005711905170524


in Bibtex Style

@conference{visapp16,
author={José Mennesson and Afifa Dahmane and Taner Danisman and Ioan Marius Bilasco},
title={Head Yaw Estimation using Frontal Face Detector},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={517-524},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005711905170524},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2016)
TI - Head Yaw Estimation using Frontal Face Detector
SN - 978-989-758-175-5
AU - Mennesson J.
AU - Dahmane A.
AU - Danisman T.
AU - Bilasco I.
PY - 2016
SP - 517
EP - 524
DO - 10.5220/0005711905170524