Abstract
This work presents a new method to automatically locate frontal facial feature points under large scene variations (illumination, pose and facial expressions). First, we use a kernel-based tracker to detect and track the facial region in an image sequence. Then the results of the face tracking, i.e. face region and face pose, are used to constrain prominent facial feature detection and tracking. In our case, eyes and mouth corners are considered as prominent facial features. In a final step, we propose an improvement to the Bayesian Tangent Shape Model for the detection and tracking of the full shape model. A constrained regularization algorithm is proposed using the head pose and the accurately aligned prominent features to constrain the deformation parameters of the shape model. Extensive experiments demonstrate the accuracy and effectiveness of our proposed method.
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References
Hou, Y., Zhang, Y., Zhao, R.: Robust object tracking based on uncertainty factorization subspace constraints optical flow. In: Hao, Y., Liu, J., Wang, Y.-P., Cheung, Y.-m., Yin, H., Jiao, L., Ma, J., Jiao, Y.-C. (eds.) CIS 2005. LNCS (LNAI), vol. 3802, pp. 875–880. Springer, Heidelberg (2005)
Hou, Y., Zhonghua Fu, Y.Z., Zhao, R.: Face feature points extraction based on refined asm. Chinese Journal of Application Research of Computers 23, 255–257 (2006)
Yang, J., Stiefelhagen, R., Meier, U., Waibel, A.: Real-time face and facial feature tracking and applications. In: Proceedings of Auditory-Visual Speech Processing, Terrigal, Australia, pp. 79–84 (1998)
Strom, J., Jebara, T., Basu, S., Pentland, A.: Real time tracking and modeling of faces: An ekf-based analysis by synthesis approach. In: Proceedings of the Modelling People Workshop at International Conference on Computer Vision, pp. 55–61 (1999)
Bourel, F., Chibelushi, C., Low, A.: Robust facial feature tracking. In: Proceedings of British Machine Vision Conference, Bristol, England, vol. 1, pp. 232–241 (2000)
Zhang, Y., Ji, Q.: Active and dynamic information fusion for facial expression understanding from image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 699–714 (2005)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: Proceedings of European Conference on Computer Vision, vol. 2, pp. 484–498 (1998)
Cootes, T.F., Taylor, C.J.: Constrained active appearance models. In: Proceedings of IEEE International Conference on Computer Vision, vol. 1, pp. 748–754 (2001)
Zhou, Y., Gu, L., Zhang, H.: Bayesian tangent shape model: estimating shape and pose parameters via bayesian inference. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 109–116 (2003)
Zhou, Y., Zhang, W., Tang, X., Shum, H.: A bayesian mixture model for multi-view face alignment. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 741–746. IEEE, Los Alamitos (2005)
Zhang, W., Zhou, Y., Tang, X., Deng, J.: A probabilistic model for robust face alignment in videos. In: Proceedings of IEEE International Conference on Image Processing, vol. 3, pp. 11–14. IEEE, Los Alamitos (2005)
Liang, L., Wen, F., Xu, Y., Tang, X., Shum, H.Y.: Accurate face alignment using shape constrained markov network. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 1313–1319. IEEE, Los Alamitos (2006)
Ravyse, I., Enescu, V., Sahli, H.: Kernel-based head tracker for videophony. In: ICIP 2005. The IEEE International Conference on Image Processing 2005, Genoa, Italy, September 11-14, 2005, vol. 3, pp. 1068–1071. IEEE, Los Alamitos (2005)
Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the International Joint Conference on Artificial Intelligence, Vancouver, pp. 674–679 (1981)
Zivkovic, Z., Kröse, B.: An em-like algorithm for color-histogram-based object tracking. In: CVPR 2004. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, D.C., USA, June 27-July 02, 2004, vol. 1, pp. 798–803. IEEE, Los Alamitos (2004)
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Hou, Y., Sahli, H., Ilse, R., Zhang, Y., Zhao, R. (2007). Robust Shape-Based Head Tracking. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_31
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DOI: https://doi.org/10.1007/978-3-540-74607-2_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74606-5
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