T. Luhandjula, Y. Hamam, B. J. Van-wyk, and Q. Williams, Symmetry-based head pose estimation for intention detection, Proceedings of the 20 th Annual Symposium of the Pattern Recognition Association of South Africa, pp.93-98, 2009.

T. Luhandjula, K. Djouani, Y. Hamam, B. J. Van-wyk, and Q. Williams, A handbased visual intent recognition algorithm for wheelchair motion, Proceedings of the 3 rd International IEEE Conference on Human System Interactions, pp.749-756, 2010.

T. Luhandjula, Q. Williams, Y. Hamam, K. Djouani, and B. J. Van-wyk, Visual head pose estimation algorithm for fast intent recognition, Proceedings of the 21 st Annual Symposium of the Pattern Recognition Association of South Africa, pp.165-170, 2010.

T. Luhandjula, K. Djouani, Y. Hamam, B. J. Van-wyk, and Q. Williams, A Visual Hand Motion Detection Algorithm for Wheelchair Motion, Z.S. Hippe, J.L. Kulikowski, p.172, 2011.
DOI : 10.1007/978-3-642-23187-2_28

T. Starner and A. Pentland, Real-time American Sign Language recognition from video using Hidden Markov Models, Proceedings of International Symposium on Computer Vision, Coral Gables, pp.265-270, 1995.

A. Wilson and A. Bobick, Recognition and interpretation of parametric gesture, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp.329-336, 1998.
DOI : 10.1109/ICCV.1998.710739

M. Brand, N. Oliver, and A. Pentland, Coupled hidden Markov models for complex action recognition, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.994-999, 1997.
DOI : 10.1109/CVPR.1997.609450

A. Bobick and Y. A. Ivanov, Action recognition using probabilistic parsing, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), pp.196-202, 1998.
DOI : 10.1109/CVPR.1998.698609

H. H. Bui, S. Venkatesh, and G. West, Policy recognition in the abstract Hidden Markov Model, Journal of Artificial Intelligence Research, vol.17, pp.451-499, 2002.

H. H. Bui, A general model for online probabilistic plan recognition, Proceedings of the 8 th International Joint Conference on Artificial Intelligence, pp.1309-1318, 2003.

P. Kiefer and C. Schlieder, Exploring context-sensitivity in spatial intention recognition, Proceedings of the Workshop on Behaviour Monitoring and Interpretation, pp.102-116, 2007.

Y. Nakauchi, K. Noguchi, P. Somwong, T. Matsubara, and A. Namatame, Vivid room: human intention detection and activity support environment for ubiquitous autonomy, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), pp.773-778, 2003.
DOI : 10.1109/IROS.2003.1250723

T. Mei, X. S. Hua, and H. Q. Zhou, Tracking user's capture intention: a novel complementary view for home video content analysis, Proceedings of the 13th annual ACM International Conference on Multimedia, 2005.

T. Mei, X. S. Hua, and H. Q. Zhou, To mine capture intention of camcorder users, Visual Communications and Image Processing 2005, 2005.
DOI : 10.1117/12.631387

C. Wu and H. Aghajan, Head pose and trajectory recovery in uncalibrated camera networks ? region of interest tracking in smart home applications, Proceedings of the ACM/IEEE International Conference on distributed smart cameras, pp.1-7, 2008.

M. Khezri and M. Jahed, Real-time intelligent pattern recognition algorithm for surface EMG signals, BioMedical Engineering OnLine, vol.6, issue.1, 2007.
DOI : 10.1186/1475-925X-6-45

D. D. Salvucci, Inferring driver intent: A case study in lane-change detection, Proceedings of the 48 th Annual Meeting of the Human Factors Ergonomics Society, 2004.

C. W. Geib, Problems with intent recognition for elder care, Proceedings of the Conference of the Association for the Advancement of Artificial Intelligence Conference, pp.13-17, 2002.

M. Bauer and A. Dempster-shafer, Approach to modelling agent preferences for plan recognition. User Modelling and User-Adapted Interaction, pp.3-4317, 1995.

M. Bauer, Acquisition of user preferences for plan recognition, Proceedings of the 5 th International Conference on User Modelling, p.174, 1996.

S. M. Weiss and N. Indurkhya, Rule-based machine learning methods for functional prediction, Journal of Artificial Intelligence Research, vol.3, pp.383-403, 1995.

A. Pentland and A. Liu, Modeling and Prediction of Human Behavior, Neural Computation, vol.83, issue.1, pp.229-271, 1999.
DOI : 10.1109/3468.553220

R. Bodor, R. Morlok, and N. Papanikolopoulos, Dual-camera system for multilevel activity recognition, Proceedings of the IEEE, pp.643-648, 2004.

L. Lin, D. J. Patterson, D. Fox, and H. Kautz, Behaviour recognition in assisted cognition, Proceedings of the 9 th National Conference on Artificial Intelligence, 2004.

R. A. Braga, M. Petry, A. P. Moreira, and L. P. Reis, Intellwheels: a development platform for intelligent wheelchairs for disabled people, Proceedings of the 5 th International Conference on Informatics in Control, Automation and Robotics, pp.115-121, 2008.

S. G. Tzafestas, Reinventing the wheelchair: autonomous robotic wheelchair projects in Europe improve mobility and safety, IEEE Robotics and Automation Magazine, vol.81, 2001.

R. C. Simpson, Smart wheelchairs: A literature review, The Journal of Rehabilitation Research and Development, vol.42, issue.4, pp.423-436, 2005.
DOI : 10.1682/JRRD.2004.08.0101

H. Yu, M. Spenko, and S. Dubowsky, An adaptive shared control system for an intelligent mobility aid for the elderly, Autonomous Robots, vol.15, issue.1, pp.53-66, 2003.
DOI : 10.1023/A:1024488717009

P. Aigner and B. J. Mccarragher, Modelling and constraining human interactions in shared control utilizing a discrete event framework, IEEE Transactions on Systems, Man, and Cybernetics -Part A: Systems and Humans, 2000.

C. Martens, N. Ruchel, O. Lang, O. Ivlev, and A. Gräaser, A FRIEND for assisting handicapped people, IEEE Robotics & Automation Magazine, vol.8, issue.1, pp.57-65, 2001.
DOI : 10.1109/100.924364

T. Carlson and Y. Demiris, Human-wheelchair collaboration through prediction of intention and adaptive assistance, 2008 IEEE International Conference on Robotics and Automation, pp.3926-3931, 2008.
DOI : 10.1109/ROBOT.2008.4543814

B. Benfold and I. Reid, Colour Invariant Head Pose Classification in Low Resolution Video, Procedings of the British Machine Vision Conference 2008, 2008.
DOI : 10.5244/C.22.49

T. Vatahska, M. Bennewitz, and S. Behnke, Feature-based head pose estimation from images, 2007 7th IEEE-RAS International Conference on Humanoid Robots, pp.330-335, 2007.
DOI : 10.1109/ICHR.2007.4813889

N. Gourier, J. Maisonnasse, D. Hall, and J. L. Crowley, Head Pose Estimation on Low Resolution Images, 2007.
DOI : 10.1007/978-3-540-69568-4_24
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.9901

J. Hoey, D. Gunn, and A. Mihailidis, Obstacle avoidance wheelchair system, Proceedings of the International Conference on Robotics and Automation, 2006.

T. Felzer and R. Nordman, Alternative wheelchair control, Proceedings of the International IEEE-BAIS Symposium on Research on Assistive Technologies, pp.67-74, 2007.

E. Demeester, A. H?ntemann, D. Vanhooydonck, G. Vanacker, H. Van-brussel et al., User-adapted plan recognition and user-adapted shared control, 2008.
DOI : 10.1007/s10514-007-9064-5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.570

A. Gee and R. Cipolla, Determining the gaze of faces in images, Image and Vision Computing, vol.12, issue.10, 1994.
DOI : 10.1016/0262-8856(94)90039-6

Y. Tian, L. Brown, J. H. Connell, S. Pankanti, A. Hampapur et al., Absolute head pose estimation from overhead wide-angle cameras, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443), 2003.
DOI : 10.1109/AMFG.2003.1240829

M. Voit, K. Nickel, and R. Stiefelhagen, Bayesian approaches for multi-view head pose estimation, Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, pp.31-34, 2006.

C. Wang and M. Brandstein, Robust head pose estimation by machine learning, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), pp.210-213, 2000.
DOI : 10.1109/ICIP.2000.899332

N. Robertson and I. Reid, Estimating Gaze Direction from Low-Resolution Faces in Video, Lecture Notes in Computer Science, vol.57, issue.3, pp.402-415, 2006.
DOI : 10.1023/B:VISI.0000013087.49260.fb

S. Niyogi and W. T. Freeman, Example-based head tracking, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp.374-378, 1996.
DOI : 10.1109/AFGR.1996.557294

S. O. Ba and J. M. Odobez, Evaluation of multiple cue head poses estimation algorithms in natural environments, Proceedings of the IEEE International Conference on Multimedia and Expo, pp.1330-1333, 2005.

Y. Wu and K. Toyama, Wide-range, person-and illumination-insensitive head orientation estimation, Proceedings of the 4 th IEEE International Conference on Automatic Face and Gesture Recognition, pp.183-188, 2000.

R. Pappu and P. A. Beardsley, A qualitative approach to classifying gaze direction, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, pp.160-165, 1998.
DOI : 10.1109/AFGR.1998.670942

S. Birchfield, Elliptical head tracking using intensity gradients and colour histograms, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.232-237, 1998.

D. B. Russakoff and M. Herman, Head tracking using stereo. Machine Vision Applications, pp.164-173, 2002.

I. Matthews and S. Baker, Active Appearance Models Revisited, International Journal of Computer Vision, vol.60, issue.2, pp.135-164, 2004.
DOI : 10.1023/B:VISI.0000029666.37597.d3
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.8544

H. Rowley, S. Baluja, and T. Kanade, Neural network-based face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.1, pp.23-38, 1998.
DOI : 10.1109/34.655647
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.110.5546

M. Voit, K. Nickel, and R. Stiefelhagen, Head Pose Estimation in Single- and Multi-view Environments - Results on the CLEAR???07 Benchmarks, Proceedings of the 2 nd International Evaluation Workshop on Classification of Events, Activities and Relationships, pp.307-316, 2007.
DOI : 10.1007/978-3-540-68585-2_29

M. Turk and A. P. Pentland, Face recognition using eigenfaces, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.586-591, 1991.
DOI : 10.1109/CVPR.1991.139758

K. S. Huang, M. M. Trivedi, and T. Gandhi, Driver head pose and view estimation with single omnidirectional video stream, Proceedings of the IEEE Intelligent Vehicle Symposium, p.181, 2003.

M. Turk and A. P. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neuroscience, vol.10, issue.9, pp.71-86, 1991.
DOI : 10.1007/BF00239352

Y. Fu and T. S. Huang, Graph embedded analysis for head pose estimation, Proceedings of the 7 th IEEE International Conference on Automatic Face and Gesture Recognition, pp.3-8, 2006.

J. L. Tu, Y. Fu, Y. X. Hu, and T. S. Huang, Evaluation of Head Pose Estimation for Studio Data, Proceedings of the Classification of Events, Activities and Relationships Evaluation Workshop, 2006.
DOI : 10.1007/978-3-540-69568-4_25

L. B. Chen, L. Zhang, Y. X. Hu, M. J. Li, and H. J. Zhang, Head pose estimation using Fisher Manifold learning, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443), pp.203-207, 2003.
DOI : 10.1109/AMFG.2003.1240844

S. T. Roweis and L. K. Saul, Nonlinear Dimensionality Reduction by Locally Linear Embedding, Science, vol.290, issue.5500, pp.2902323-2326, 2000.
DOI : 10.1126/science.290.5500.2323

M. Belkin and P. Niyogi, Laplacian eigenmap and spectral techniques for embedding and clustering, Proceedings of Advances in Neural Information Processing Systems, 2001.

K. R. Müller, S. Mika, G. Rätsch, K. Tsuda, and B. Schölkopf, An introduction to kernel-based learning algorithms, IEEE Transactions on Neural Networks, vol.12, issue.2, pp.181-201
DOI : 10.1109/72.914517

S. Z. Li, Q. D. Fu, L. Gu, B. Scholkopf, Y. M. Cheng et al., Kernel machine based learning for multi-view face detection and pose estimation, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, p.182, 2001.
DOI : 10.1109/ICCV.2001.937691

Z. Li, L. Gao, and A. K. Katsaggelos, Locally Embedded Linear Subspaces for Efficient Video Indexing and Retrieval, 2006 IEEE International Conference on Multimedia and Expo, pp.1765-1768, 2006.
DOI : 10.1109/ICME.2006.262893

R. Yang and Z. Zhang, Model-based head pose tracking with stereovision, Proceedings of the 5 th International Conference on Automatic Face and Gesture Recognition, pp.255-260, 2002.

L. Cascia, M. Isidoro, J. Sclaroff, and S. , Head tracking via robust registration in texture map images, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), pp.508-514
DOI : 10.1109/CVPR.1998.698653

L. M. Brown, 3D head tracking using motion adaptive texture-mapping, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.998-1003, 2001.
DOI : 10.1109/CVPR.2001.990639

W. Ke, W. Yanlai, Y. Baocai, and K. Dehui, Face pose estimation with a knowledge-based model, Proceedings of the IEEE International Conference Neural Networks and Signal Processing, pp.1131-1134, 2003.

S. Malassiotis and M. G. Strintzis, Robust real-time 3D head pose estimation from range data, Pattern Recognition, vol.38, issue.8, pp.1153-1165, 2005.
DOI : 10.1016/j.patcog.2004.11.020
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.96.5359

S. J. Mckenna and S. Gong, Real-time face pose estimation. Real-Time Imaging, p.333347, 1998.

X. L. Brolly, C. Stratelos, and J. B. Mulligan, Model-based head pose estimation for air-traffic controllers, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.113-116, 2003.
DOI : 10.1109/ICIP.2003.1246629

M. Malciu and F. J. Prieteux, A robust model-based approach for 3D head tracking in video sequences, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), pp.169-175, 2000.
DOI : 10.1109/AFGR.2000.840630
URL : https://hal.archives-ouvertes.fr/hal-00272441

Y. Zhang and C. Kambhamettu, Robust 3D head tracking under partial occlusion, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), pp.176-182, 2000.
DOI : 10.1109/AFGR.2000.840631

P. Fitzpatrick, Head pose estimation without manual initialization, 2000.

D. O. Gorodnichy, On importance of nose for face tracking, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition, pp.188-196, 2002.
DOI : 10.1109/AFGR.2002.1004153

S. Gong, S. Mckenna, and J. Collins, An investigation into face pose distributions, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp.265-270, 1996.
DOI : 10.1109/AFGR.1996.557275

H. Murase and S. K. Nayar, Illumination planning for object recognition using parametric eigenspaces, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.16, issue.12, pp.1219-1227, 1995.
DOI : 10.1109/34.387485

A. Pentland, B. Moghaddam, T. Starner, O. Oliyide, and M. Turk, View-based and modular eigenspaces for face recognition, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94, 1993.
DOI : 10.1109/CVPR.1994.323814

Y. Li, S. Gong, and H. Liddell, Support vector regression and classification based multi-view face detection and recognition, Proceedings of the 4 th IEEE International Conference on Face and Gesture Recognition, 2000.

M. W. Krueger, Artificial reality II, 1991.

X. Yin and M. Xie, Finger identification and hand posture recognition for human???robot interaction, Image and Vision Computing, vol.25, issue.8, pp.1291-1300, 2007.
DOI : 10.1016/j.imavis.2006.08.003

K. G. Derpanis, A review of vision-based hand gesture (Unpublished), 2004.

A. D. Wilson, A. F. Bobick, and J. Cassell, Recovering the temporal structure of natural gesture, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp.66-71, 1996.
DOI : 10.1109/AFGR.1996.557245

O. 'hagan, R. G. Zalensky, A. Rougeaux, and S. , Visual gesture interfaces for virtual environments, Interacting with Computers, vol.14, issue.3, pp.231-250, 2002.
DOI : 10.1016/S0953-5438(01)00050-9

G. Mcallister, S. J. Mckenna, and I. W. Ricketts, Hand tracking for behaviour understanding, Image and Vision Computing, vol.20, issue.12, pp.827-840, 2002.
DOI : 10.1016/S0262-8856(02)00093-8

T. Ahmad, C. J. Taylor, A. Lanitis, and T. F. Cootes, Tracking and recognising hand gestures, using statistical shape models, Image and Vision Computing, vol.15, issue.5, pp.345-352, 1997.
DOI : 10.1016/S0262-8856(96)01136-5

P. Garg, N. Aggarwal, and S. Sofat, Vision-based hand gesture recognition, World Academy of Science, Engineering and Technology, vol.49, pp.972-977, 2009.

H. Francke, J. Ruiz-del-solar, and R. Verschae, Real-Time Hand Gesture Detection and Recognition Using Boosted Classifiers and Active Learning, Proceedings of the 2 nd Pacific Rim Conference on Advances in image and video technology, pp.553-547, 2007.
DOI : 10.1007/978-3-540-77129-6_47

Y. Xiong and F. Quek, Hand Motion Gesture Frequency Properties and Multimodal Discourse Analysis, International Journal of Computer Vision, vol.22, issue.1, pp.353-371, 2006.
DOI : 10.1007/s11263-006-8112-5

S. Wu and L. Hong, Hand tracking in a natural conversational environment by the interacting multiple model and probabilistic data association (IMM-PDA) algorithm, Pattern Recognition, vol.38, issue.11, pp.2143-2158, 2005.
DOI : 10.1016/j.patcog.2005.01.020

F. S. Chen, C. M. Fu, and C. L. Huang, Hand gesture recognition using a real-time tracking method and hidden Markov models, Image and Vision Computing, vol.21, issue.8, pp.745-758, 2003.
DOI : 10.1016/S0262-8856(03)00070-2

T. Coogan, G. Awad, J. Han, and A. Sutherland, Real Time Hand Gesture Recognition Including Hand Segmentation and Tracking, Advances in Visual Computing, pp.495-504, 2006.
DOI : 10.1007/11919476_50
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.456.6561

A. Erol, G. Bebis, M. Nicolescu, R. D. Boyle, and X. Twombly, Vision-based hand pose estimation: A review, Computer Vision and Image Understanding, vol.108, issue.1-2, pp.52-73, 2007.
DOI : 10.1016/j.cviu.2006.10.012

B. Ionescu, D. Coquin, P. Lambert, and V. Buzuloiu, Dynamic Hand Gesture Recognition Using the Skeleton of the Hand, EURASIP Journal on Advances in Signal Processing, vol.2005, issue.13, pp.2101-2109, 2005.
DOI : 10.1155/ASP.2005.2101
URL : https://hal.archives-ouvertes.fr/hal-00623729

D. J. Sturman and D. Zeltzer, A survey of glove-based input, IEEE Computer Graphics and Applications, vol.14, issue.1, pp.30-39, 1994.
DOI : 10.1109/38.250916

T. Takahashi and F. Kishino, A hand gesture recognition method and its application, Systems and Computers in Japan, pp.38-48, 1992.

A. F. Bobick and A. D. Wilson, A state-based technique for the summarization and recognition of gesture, Proceedings of IEEE International Conference on Computer Vision, pp.382-388, 1995.
DOI : 10.1109/ICCV.1995.466914

A. Shamaie and A. Sutherland, Hand tracking in bimanual movements, Image and Vision Computing, vol.23, issue.13, pp.1131-1149, 2005.
DOI : 10.1016/j.imavis.2005.07.010

G. Iannizzotto, M. Villari, and L. Vita, Hand tracking for human computer interaction with gray level visual glove: turning back to the simple way, Proceedings of the workshop on Perceptive user interfaces, 2001.

V. I. Pavlovic, R. Sharma, and T. S. Huang, Visual interpretation of hand gestures for human-computer interaction: a review, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.7, pp.677-695, 1997.
DOI : 10.1109/34.598226

T. Baudel and M. Beaudouin-lafom, Charade: remote control of objects using gestures, Proceedings of the 1 st Conference on Computer Science, pp.28-35, 1993.

R. Cipolla, Y. Okamoto, and Y. Kuno, Robust structure from motion using motion parallax, 1993 (4th) International Conference on Computer Vision, pp.374-382, 1993.
DOI : 10.1109/ICCV.1993.378190

J. Davis and M. Shah, Recognising hand gestures, Proceedings of the 3 rd European Conference on Computer Vision, pp.331-340, 1994.

J. Davis and M. Shah, Visual gesture recognition, IEE Proceedings - Vision Image Signal Processing, pp.101-106, 1994.
DOI : 10.1049/ip-vis:19941058
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.496

T. Darrell and A. Pentland, Recognition of space-time gestures using a distributed representation, 1992.

Y. Cui and J. J. Weng, Hand sign recognition from intensity image sequences with complex backgrounds, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp.259-264, 1996.
DOI : 10.1109/AFGR.1996.557274

K. T. Luhandjula, E. Monacelli, Y. Hamam, B. J. Van-wyk, and Q. Williams, Visual Intention Detection for Wheelchair Motion, proceedings of the 5 th International Symposium on Visual Computing, pp.407-416, 2009.
DOI : 10.1007/978-3-642-10520-3_38
URL : https://hal.archives-ouvertes.fr/tel-00794527

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, pp.511-518, 2001.
DOI : 10.1109/CVPR.2001.990517

K. Peng, L. Chen, S. Ruan, and G. Kukharev, A robust and efficient algorithm for eye detection on grey intensity faces, Proceedings of the International Workshop on Pattern Recognition for Crime Prevention, Security and Surveillance, pp.302-308, 2005.

G. Bradski, A. Kaehler, and V. Pisarevsky, Learning-based computer vision with Intel's open source computer vision library, Intel Technology Journal, vol.9, issue.2, pp.119-130, 2005.

G. Bradski, Real time face and object tracking as a component of a perceptual user interface, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201), pp.214-219, 1998.
DOI : 10.1109/ACV.1998.732882

G. Bradski, Computer vision faces tracking for use in a perceptual user interface, Intel Technology Journal, 1998.

N. Ikizler and P. Duygulu, Histogram of oriented rectangles: A new pose descriptor for human action recognition, Image and Vision Computing, vol.27, issue.10, pp.1515-1526, 2009.
DOI : 10.1016/j.imavis.2009.02.002

C. Bishop, Neural networks for pattern recognition, p.192, 1995.

N. Cristianini and J. Shawe-taylor, An introduction to support vector machines and other kernel-based learning methods, 2000.
DOI : 10.1017/CBO9780511801389

J. B. Macqueen, Some Methods for classification and Analysis of Multivariate Observations, 5 th Berkeley Symposium on Mathematical Statistics and Probability, pp.281-297, 1967.

N. Ikizler and P. Duygulu, Human Action Recognition Using Distribution of Oriented Rectangular Patches, Proceedings of the Workshop on Human Motion-Understanding, Modelling, Capture and Animation, pp.271-284, 2007.
DOI : 10.1007/978-3-540-75703-0_19

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

E. Micheli-tzanakou, Supervised and Unsupervised Pattern Recognition: Feature Extraction and Computational Intelligence. Industrial electronics series, 2000.
DOI : 10.1201/9781420049770

T. Kanno, K. Nakata, and K. Furuta, A method for team intention inference, International Journal of Human-Computer Studies, vol.58, issue.4, pp.393-413, 2003.
DOI : 10.1016/S1071-5819(03)00011-9