Abstract
We present a markerless real-time, model-based 3D face tracking methodology. The system combines two robust and complimentary op-timization-based strategies, namely active contours and mutual information template matching, in order to obtain real-time performances for full 6dof tracking. First, robust head contour estimation is realized by means of the Contracting Curve Density algorithm, effectively employing local color statistics separation for contour shape optimization. Afterwards, the 3D face template is robustly matched to the underlying image, through fast mutual information optimization. Off-line model building is done using a fast modeling procedure, providing a unique appearance model for each user. Re-initialization criteria are employed in order to obtain a complete and autonomous tracking system.
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References
Toyama, K.: Look, ma — no hands!’ hands-free cursor control with real-time 3d face tracking (1998)
Toyama, K., Hager, G.: Incremental focus of attention for robust visual tracking (1996)
Lu, L., Dai, X.T., Hager, G.: A particle filter without dynamics for robust 3d face tracking. In: CVPRW 2004: Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW 2004), vol. 5, p. 70. IEEE Computer Society, Washington, DC, USA (2004)
Vacchetti, L., Lepetit, V., Fua, P.: Stable real-time 3d tracking using online and offline information. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 1391–1391 (2004)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 381–395 (1981)
Isard, M., Blake, A.: Condensation – conditional density propagation for visual tracking. International Journal of Computer Vision 29, 5–28 (1998)
Matthews, I., Baker, S.: Active appearance models revisited. Technical Report CMU-RI-TR-03-02, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (2003)
Xiao, J., Baker, S., Matthews, I., Kanade, T.: Real-time combined 2d+3d active appearance models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 535–542 (2004)
Cascia, M., Sclaroff, S., Athitsos, V.: Fast, reliable head tracking under varying illumination: An approach based on registration of texture-mapped 3d models (1999)
Park, I.K., Zhang, H., Vezhnevets, V., Choh, H.K.: Image-based photorealistic 3-d face modeling. In: FGR, pp. 49–56 (2004)
Viola, P.A., Jones, M.J.: Robust real-time face detection. In: ICCV, p. 747 (2001)
Hanek, R., Beetz, M.: The contracting curve density algorithm: Fitting parametric curve models to images using local self-adapting separation criteria. Int. J. Comput. Vision 59, 233–258 (2004)
Panin, G., Ladikos, A., Knoll, A.: An efficient and robust real-time contour tracking system. In: ICVS, p. 44 (2006)
Moddemeijer, R.: On estimation of entropy and mutual information of continuous distributions. Signal Processing 16, 233–246 (1989)
Viola, P., William, M., Wells, I.: Alignment by maximization of mutual information. Int. J. Comput. Vision 24, 137–154 (1997)
Nelder, J., Mead, R.: A simplex method for function minimization. Computer Journal 7, 308–313 (1965)
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Panin, G., Knoll, A. (2007). Real-Time 3D Face Tracking with Mutual Information and Active Contours. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76858-6_1
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DOI: https://doi.org/10.1007/978-3-540-76858-6_1
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