M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing, vol.50, issue.2, pp.174-188, 2002.
DOI : 10.1109/78.978374

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.1144

S. O. Ba and J. Odobez, A probabilistic framework for joint head tracking and pose estimation, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004.
DOI : 10.1109/ICPR.2004.1333754

H. Bay, A. Ess, T. Tuytelaars, and L. Van-gool, Speeded-up robust features (surf) Computer vision and image understanding, pp.346-359, 2008.
DOI : 10.1016/j.cviu.2007.09.014

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.738

C. Benabdelkader, Robust Head Pose Estimation Using Supervised Manifold Learning, 2010.
DOI : 10.1007/978-3-642-15567-3_38

A. Bhattachayya, On a measure of divergence between two statistical population defined by their population distributions, Bulletin Calcutta Mathematical Society, vol.35, pp.99-109, 1943.

C. Bishop, Pattern recognition and machine learning, 2007.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

A. Deleforge, F. Forbes, and R. Horaud, High-dimensional regression with gaussian mixtures and partially-latent response variables, Statistics and Computing, vol.19, issue.11, pp.893-911, 2015.
DOI : 10.1007/s11222-014-9461-5

URL : https://hal.archives-ouvertes.fr/hal-01107604

F. Dornaika and F. Davoine, Head and Facial Animation Tracking using Appearance-Adaptive Models and Particle Filters, 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004.
DOI : 10.1109/CVPR.2004.359

URL : https://hal.archives-ouvertes.fr/hal-00143756

V. Drouard, S. Ba, G. Evangelidis, A. Deleforge, and R. Horaud, Head pose estimation via probabilistic highdimensional regression, IEEE ICIP, 2015.
DOI : 10.1109/icip.2015.7351683

URL : https://hal.archives-ouvertes.fr/hal-01163663

G. Fanelli, M. Dantone, J. Gall, A. Fossati, and L. Van-gool, Random Forests for Real Time 3D Face Analysis, International Journal of Computer Vision, vol.41, issue.5, pp.437-458, 2013.
DOI : 10.1007/s11263-012-0549-0

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.6933

J. Foytik and V. Asari, A Two-Layer Framework for Piecewise Linear Manifold-Based Head Pose Estimation, International Journal of Computer Vision, vol.19, issue.2, pp.270-287, 2013.
DOI : 10.1007/s11263-012-0567-y

A. Gee and R. Cipolla, Fast visual tracking by temporal consensus, Image and Vision Computing, vol.14, issue.2, pp.105-114, 1996.
DOI : 10.1016/0262-8856(95)01044-0

Z. Ghahramani and G. E. Hinton, Switching state-space models, 1996.

R. Girshick, J. Donahue, T. Darrell, and J. Malik, Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014.
DOI : 10.1109/CVPR.2014.81

URL : http://arxiv.org/abs/1311.2524

N. Hu, W. Huang, and S. Ranganath, Head pose estimation by non-linear embedding and mapping, IEEE ICIP, 2005.

C. Kim, Dynamic linear models with Markov-switching, Journal of Econometrics, vol.60, issue.1-2, pp.1-22, 1994.
DOI : 10.1016/0304-4076(94)90036-1

J. F. Kooij, G. Englebienne, and D. M. Gavrila, A nonparametric hierarchical model to discover behavior dynamics from tracks, 2012.
DOI : 10.1007/978-3-642-33783-3_20

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.5852

Z. Li, Y. Fu, J. Yuan, T. Huang, and Y. Wu, Query driven localized linear discriminant models for head pose estimation Distinctive image features from scaleinvariant keypoints, IEEE International Conference on Multimedia and Expo, pp.91-110, 2004.
DOI : 10.1109/icme.2007.4285024

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.728

C. Ma, J. Huang, X. Yang, and M. Yang, Hierarchical Convolutional Features for Visual Tracking, 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
DOI : 10.1109/ICCV.2015.352

M. Marin-jimenez, A. Zisserman, M. Eichner, and V. Ferrari, Detecting People Looking at Each Other in Videos, International Journal of Computer Vision, vol.25, issue.1, pp.282-296, 2014.
DOI : 10.1007/s11263-013-0655-7

B. Massé, S. Ba, and R. Horaud, Simultaneous estimation of gaze direction and visual focus of attention for multi-personto-robot interaction, IEEE International Conference on Multimedia and Expo, 2016.

T. Maurer, C. Von, and . Malsburg, Tracking and learning graphs and pose on image sequences of faces, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 1996.
DOI : 10.1109/AFGR.1996.557261

K. A. Mora, F. Monay, and J. Odobez, EYEDIAP, Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA '14, pp.255-258, 2014.
DOI : 10.1145/2578153.2578190

K. A. Mora and J. Odobez, Gaze estimation from multimodal kinect data, IEEE CVPRW, 2012.

K. P. Murphy, Switching kalman filters, 1998.

E. Murphy-chutorian, A. Doshi, and M. Trivedi, Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation, 2007 IEEE Intelligent Transportation Systems Conference, 2007.
DOI : 10.1109/ITSC.2007.4357803

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.6242

E. Murphy-chutorian and M. M. Trivedi, Head Pose Estimation in Computer Vision: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.4, pp.607-626, 2009.
DOI : 10.1109/TPAMI.2008.106

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.8306

S. M. Oh, J. M. Rehg, T. Balch, F. Dellaert, V. Pavlovic et al., Learning and inference in parametric switching linear dynamic systems Learning switching linear models of human motion, IEEE ICCV, 2005. [31] Conference on Neural Information Processing Systems, 2000.

B. Raytchev, I. Yoda, and K. Sakaue, Head pose estimation by nonlinear manifold learning, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004.
DOI : 10.1109/ICPR.2004.1333802

D. Salmond, Mixture Reduction Algorithms for Point and Extended Object Tracking in Clutter, IEEE Transactions on Aerospace and Electronic Systems, vol.45, issue.2, pp.667-686, 2009.
DOI : 10.1109/TAES.2009.5089549

A. Sharif-razavian, H. Azizpour, J. Sullivan, and S. Carlsson, Cnn features off-the-shelf: an astounding baseline for recognition, IEEE CVPRW, 2014.

S. Srinivasan and K. L. Boyer, Head pose estimation using view based eigenspaces, Object recognition supported by user interaction for service robots, 2002.
DOI : 10.1109/ICPR.2002.1047456

K. Sundararajan and D. L. Woodard, Head pose estimation in the wild using approximate view manifolds, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2015.
DOI : 10.1109/CVPRW.2015.7301354

S. Taheri, A. C. Sankaranarayanan, and R. Chellappa, Joint Albedo Estimation and Pose Tracking from Video, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.7, pp.1674-1689, 2013.
DOI : 10.1109/TPAMI.2012.249

J. Tu, T. Huang, and H. Tao, Accurate head pose tracking in low resolution video, IEEE International Conference on Automatic Face and Gesture Recognition, 2006.

M. U?i?á?, V. Franc, and V. Hlavá?, Facial Landmarks Detector Learned by the Structured Output SVM, International Conference on Computer Vision Theory and Applications, 2012.
DOI : 10.1007/978-3-642-38241-3_26

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001.
DOI : 10.1109/CVPR.2001.990517

R. Yang and Z. Zhang, Model-based head pose tracking with stereovision, IEEE International Conference on Automatic Face and Gesture Recognition, 2002.

P. Yao, G. Evans, and A. Calway, Using affine correspondence to estimate 3-D facial pose, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001.
DOI : 10.1109/ICIP.2001.958274

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.3831