N. Courty, Animation référencée vision : de la tâche au comportement, 2002.

A. Héloir, Agent virtuel signeur -Aidè a la communication des personnes sourdes, 2008.

C. Awad, Indexation et Interrogations de Bases de Données de Mouvements pour l'Animation d'Humanoides Virtuels, 2010.

P. Allain, Analyse et synthèse de mouvements de foule par contrôle optimal, 2012.

N. I. Badler, C. B. Phillips, and B. L. Webber, Simulating humans: computer graphics animation and control, 1993.

W. A. Wolovich and H. Elliot, A computational technique for inverse kinematics, The 23rd IEEE Conference on Decision and Control, pp.1359-1363, 1984.
DOI : 10.1109/CDC.1984.272258

C. Welman, Inverse kinematics and geometric constraints for articulated figure manipulation, 1993.

J. Zhao and N. Badler, Inverse kinematics positioning using nonlinear programming for highly articulated figures, Proc. SIGGRAPH), pp.313-336, 1994.
DOI : 10.1145/195826.195827

R. Boulic, R. Mas, and D. Thalmann, A robust approach for the control of the center of mass with inverse kinetics, Computers & Graphics, vol.20, issue.5, 1996.
DOI : 10.1016/S0097-8493(96)00043-X

K. Yamane and Y. Nakamura, Natural motion animation through constraining and deconstraining at will, IEEE Transactions on Visualization and Computer Graphics, vol.9, issue.3, pp.352-360, 2003.
DOI : 10.1109/TVCG.2003.1207443

P. Baerlocher and R. Boulic, An inverse kinematics architecture enforcing an arbitrary number of strict priority levels. The Visual Computer, pp.402-417, 2004.

L. Sentis and O. Khatib, SYNTHESIS OF WHOLE-BODY BEHAVIORS THROUGH HIERARCHICAL CONTROL OF BEHAVIORAL PRIMITIVES, International Journal of Humanoid Robotics, vol.02, issue.04, 2005.
DOI : 10.1142/S0219843605000594

C. Rose, M. F. Cohen, and B. Bodenheimer, Verbs and adverbs: multidimensional motion interpolation, IEEE Computer Graphics and Applications, vol.18, issue.5, pp.32-40, 1998.
DOI : 10.1109/38.708559

T. Mukai and S. Kuriyama, Geostatistical motion interpolation, ACM Transactions on Graphics, vol.24, issue.3, pp.1062-1070, 2005.
DOI : 10.1145/1073204.1073313

C. S. Myers and L. R. Rabiner, A comparative study of several dynamic time-warping algorithms for connected word recognition. The Bell System Technical Journal, pp.1389-1409, 1981.

L. Kovar, M. Gleicher, and F. Pighin, Motion graphs, ACM Trans. on Graphics, vol.21, issue.3, pp.473-482, 2002.

J. Lee, J. Chai, P. S. Reitsma, J. K. Hodgins, and N. S. Pollard, Interactive control of avatars animated with human motion data, ACM Trans. Graph, vol.21, issue.3, pp.491-500, 2002.

L. Kovar and M. Gleicher, Automated extraction and parameterization of motions in large data sets, SIGGRAPH '04: ACM SIGGRAPH 2004 Papers, pp.559-568, 2004.

J. Chai and J. K. Hodgins, Constraint-based motion optimization using a statistical dynamic model, ACM Trans. on Graphics, vol.26, issue.3, pp.686-696, 2007.

Y. Li, T. Wang, and H. Shum, Motion texture, Proceedings of the 29th annual conference on Computer graphics and interactive techniques , SIGGRAPH '02, pp.465-472, 2002.
DOI : 10.1145/566570.566604

S. Carvalho, R. Boulic, and D. Thalmann, Interactive low-dimensional human motion synthesis by combining motion models and PIK, Computer Animation and Virtual Worlds, vol.15, issue.4-5, 2007.
DOI : 10.1002/cav.210

J. M. Wang, D. J. Fleet, and A. Hertzmann, Gaussian Process Dynamical Models for Human Motion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.2, pp.283-298, 2008.
DOI : 10.1109/TPAMI.2007.1167
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.5571

L. Ikemoto, O. Arikan, and D. Forsyth, Generalizing motion edits with Gaussian processes, ACM Transactions on Graphics, vol.28, issue.1, pp.1-12, 2009.
DOI : 10.1145/1477926.1477927

M. Lau, Z. Bar-joseph, and J. Kuffner, Modeling spatial and temporal variation in motion data, ACM Trans. Graph, issue.5, p.28, 2009.

K. Pullen and C. Bregler, Animating by multi-level sampling, Proceedings Computer Animation 2000, pp.36-42, 2000.
DOI : 10.1109/CA.2000.889031

M. Brand and A. Hertzmann, Style machines, Proceedings of the 27th annual conference on Computer graphics and interactive techniques , SIGGRAPH '00, pp.183-192, 2000.
DOI : 10.1145/344779.344865

J. Chai and J. Hodgins, Performance animation from low-dimensional control signals, ACM Trans. on

K. Grochow, S. Martin, A. Hertzmann, and Z. Popovic, Style-based inverse kinematics, ACM Transactions on Graphics, vol.23, issue.3, pp.522-531, 2004.
DOI : 10.1145/1015706.1015755
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.58.2119

R. Urtasun, D. J. Fleet, and P. Fua, 3D People Tracking with Gaussian Process Dynamical Models, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.15
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.4176

J. M. Wang, D. J. Fleet, and A. Hertzmann, Multifactor Gaussian process models for style-content separation, Proceedings of the 24th international conference on Machine learning, ICML '07, 2007.
DOI : 10.1145/1273496.1273619

O. Arikan, D. A. Forsyth, and J. F. O-'brien, Motion synthesis from annotations, ACM Transactions on Graphics, vol.22, issue.3, pp.402-408, 2003.
DOI : 10.1145/882262.882284
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.6928

. Shih-pin, C. Chao, S. Chiu, T. Yang, and . Lin, Tai chi synthesizer: a motion synthesis framework based on key-postures and motion instructions: Research articles, Comput. Animat. Virtual Worlds, vol.15, pp.3-4259, 2004.

K. Forbes and E. Fiume, An efficient search algorithm for motion data using weighted PCA, Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation , SCA '05, pp.67-76, 2005.
DOI : 10.1145/1073368.1073377

E. Keogh, T. Palpanas, V. B. Zordan, D. Gunopulos, and M. Cardle, Indexing Large Human-Motion Databases, VLDB '04: Proceedings of the Thirtieth international conference on Very large data bases, pp.780-791, 2004.
DOI : 10.1016/B978-012088469-8.50069-3
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.4767

S. Basu, S. Shanbhag, and S. Chandran, Search and transitioning for motion captured sequences, Proceedings of the ACM symposium on Virtual reality software and technology , VRST '05, pp.220-223, 2005.
DOI : 10.1145/1101616.1101660

M. Müller, T. Röder, and M. Clausen, Efficient content-based retrieval of motion capture data, ACM Transactions on Graphics, vol.24, issue.3, pp.677-685, 2005.
DOI : 10.1145/1073204.1073247

I. Marshall and E. Safar, Grammar development for sign language avatar-based synthesis, Proc. of the 3rd Int. Conf. on Universal Access in Human-Computer Interaction (UAHCI 2005), 2005.

Y. H. Chiu, C. H. Wu, H. Y. Su, and C. J. Cheng, Joint Optimization of Word Alignment and Epenthesis Generation for Chinese to Taiwanese Sign Synthesis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.1, pp.28-39, 2007.
DOI : 10.1109/TPAMI.2007.250597

J. R. Kennaway, J. R. Glauert, and I. Zwitserlood, Providing signed content on the Internet by synthesized animation, ACM Transactions on Computer-Human Interaction, vol.14, issue.3, p.15, 2007.
DOI : 10.1145/1279700.1279705

S. Fotinea, E. Efthimiou, G. Caridakis, and K. Karpouzis, A knowledge-based sign synthesis architecture, Universal Access in the Information Society, vol.1, issue.1???2, pp.405-418, 2008.
DOI : 10.1007/s10209-007-0094-8
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.326

M. Huenerfauth, L. Zhao, E. Gu, and J. Allbeck, Evaluation of American Sign Language Generation by Native ASL Signers, ACM Transactions on Accessible Computing, vol.1, issue.1, pp.1-27, 2008.
DOI : 10.1145/1361203.1361206

S. Gibet, T. Lebourque, and P. F. Marteau, High-level Specification and Animation of Communicative Gestures, Journal of Visual Languages & Computing, vol.12, issue.6, pp.657-687, 2001.
DOI : 10.1006/jvlc.2001.0202

M. Filhol, A. Braffort, and L. Bolot, Signing avatar: Say hello to elsi!, Proc. of Gesture Workshop 2007, 2007.

C. Awad, N. Courty, K. Duarte, T. L. Naour, and S. Gibet, A Combined Semantic and Motion Capture Database for Real-Time Sign Language Synthesis, Proc of IVA, pp.432-470, 2009.
DOI : 10.1007/978-3-642-04380-2_47
URL : https://hal.archives-ouvertes.fr/hal-00493426

A. Kendon and . Tools, Language and Cognition, chapter Human gesture, pp.43-62, 1993.

D. Mcneill, Hand and Mind -What Gestures Reveal about Thought, 1992.

S. Kita, I. Van-gijn, and H. Van-der-hulst, Movement phases in signs and co-speech gestures, and their transcription by human coders, Proc. of the Int. Gesture Workshop, pp.23-35, 1997.
DOI : 10.1007/BFb0052986

M. Kipp, M. Neff, K. Kipp, and I. Albrecht, Toward natural gesture synthesis: Evaluating gesture units in a data-driven approach, Intelligent Virtual Agents (IVA'07), pp.15-28, 2007.

C. William and . Stokoe, Semiotics and Human Sign Language, 1972.

S. Prillwitz, R. Leven, H. Zienert, T. Hanke, and J. Henning, Hamburg Notation System for Sign Languages -An Introductory Guide, 1989.

J. Cassell, J. Sullivan, S. Prevost, and E. F. Churchill, Embodied Conversational Agents, 2000.

R. Elliott, J. Glauert, V. Jennings, and J. Kennaway, An overview of the sigml notation and sigml signing software system, Workshop on the Representation and Processing of Signed Languages, 4th Int'l Conf. on Language Resources and Evaluation, 2004.

A. Kranstedt, S. Kopp, and I. Wachsmuth, MURML: A Multimodal Utterance Representation Markup Language for Conversational Agents, Proceedings of the AAMAS02 Workshop on Embodied Conversational Agents -let's specify and evaluate them, 2002.

H. Noot and Z. Ruttkay, Variations in gesturing and speech by GESTYLE, International Journal of Human-Computer Studies, vol.62, issue.2, pp.211-229, 2005.
DOI : 10.1016/j.ijhcs.2004.11.007

B. Hartmann, M. Mancini, and C. Pelachaud, Implementing expressive gesture synthesis for embodied conversational agents. Gesture in Human-Computer Interaction and Simulation, pp.188-199, 2006.

H. Vilhalmsson, N. Cantelmo, J. Cassell, N. E. Chafai, M. Kipp et al., The behavior markup language: Recent developments and challenges, 2007.

D. Tolani, A. Goswami, and N. Badler, Real-Time Inverse Kinematics Techniques for Anthropomorphic Limbs, Graphical Models, vol.62, issue.5, pp.353-388, 2000.
DOI : 10.1006/gmod.2000.0528

S. Kopp and I. Wachsmuth, Synthesizing multimodal utterances for conversational agents, Computer Animation and Virtual Worlds, vol.15, issue.1, pp.39-52, 2004.
DOI : 10.1002/cav.6

M. Neff, M. Kipp, I. Albrecht, and H. Seidel, Gesture modeling and animation based on a probabilistic re-creation of speaker style, ACM Transactions on Graphics, vol.27, issue.1, pp.233-51, 2008.
DOI : 10.1145/1330511.1330516

Z. Deng, P. Chiang, P. Fox, and U. Newmann, Animating blendshape faces by cross-mapping motion capture data, Proceedings of the 2006 symposium on Interactive 3D graphics and games , SI3D '06, pp.43-48, 2006.
DOI : 10.1145/1111411.1111419

O. Arikan, D. Forsyth, and J. O-'brien, Motion synthesis from annotations, ACM Transactions on Graphics, vol.22, issue.3, pp.402-408, 2003.
DOI : 10.1145/882262.882284

S. Gibet, N. Courty, K. Duarte, and T. L. Naour, The signcom system for data-driven animation of interactive virtual signers: Methodology and evaluation, ACM Transactions on Interactive Intelligent Systems, vol.16, issue.1, pp.1-6, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00664705

G. Cheung, S. Baker, and T. Kanade, Visual hull alignment and refinement across time: a 3D reconstruction algorithm combining shape-from-silhouette with stereo, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.375-382, 2003.
DOI : 10.1109/CVPR.2003.1211493

J. Deutscher and I. Reid, Articulated Body Motion Capture by Stochastic Search, International Journal of Computer Vision, vol.61, issue.2, pp.185-205, 2005.
DOI : 10.1023/B:VISI.0000043757.18370.9c

R. Raskar, H. Nii, B. Dedecker, Y. Hashimoto, J. Summet et al., Prakash: Lighting-aware motion capture using photosensing markers and multiplexed illumination session : Performance Capture, ACM Trans. Graph, vol.26, issue.3, 2007.

K. Shoemake, QUATERNIONS AND 4 ?? 4 MATRICES, Graphics Gems II, pp.351-354, 1991.
DOI : 10.1016/B978-0-08-050754-5.50074-8

J. Kuffner, Effective sampling and distance metrics for 3D rigid body path planning, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, 2004.
DOI : 10.1109/ROBOT.2004.1308895

T. Tangkuampien and D. Suter, Human Motion De-noising via Greedy Kernel Principal Component Analysis Filtering, 18th International Conference on Pattern Recognition (ICPR'06), pp.457-460, 2006.
DOI : 10.1109/ICPR.2006.639

A. Héloir, N. Courty, S. Gibet, and F. Multon, Temporal alignment of communicative gesture sequences, Computer Animation and Virtual Worlds, vol.24, issue.3-4, pp.347-357, 2006.
DOI : 10.1002/cav.138

N. Courty, Bilateral Human Motion Filtering, Proc. of the 16th European Signal Processing Conference Proc. of the 16th European Signal Processing Conference, pp.1-5, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00494141

C. Tomasi and R. Manduchi, Bilateral filtering for gray and color images, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp.839-846, 1998.
DOI : 10.1109/ICCV.1998.710815

E. Bennett and L. Mcmillan, Video enhancement using per-pixel virtual exposures, ACM Transactions on Graphics, vol.24, issue.3, pp.845-852, 2005.
DOI : 10.1145/1073204.1073272
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.3972

C. Liu, W. Freeman, R. Szeliski, and S. B. Kang, Noise estimation from a single image, CVPR, pp.901-908, 2006.

B. Oh, M. Chen, J. Dorsey, and F. Durand, Image-based modeling and photo editing, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.433-442, 2001.
DOI : 10.1145/383259.383310

F. Durand and J. Dorsey, Fast bilateral filtering for the display of high-dynamic-range images, ACM Trans. Graph, vol.21, issue.3, pp.257-266, 2002.

G. Petschnigg, R. Szeliski, M. Agrawala, M. Cohen, H. Hoppe et al., Digital photography with flash and no-flash image pairs, ACM Transactions on Graphics, vol.23, issue.3, pp.664-672, 2004.
DOI : 10.1145/1015706.1015777

S. Bae, S. Paris, and F. Durand, Two-scale tone management for photographic look, ACM Transactions on Graphics, vol.25, issue.3, pp.637-645, 2006.
DOI : 10.1145/1141911.1141935

H. Winnemöller, S. Olsen, and B. Gooch, Real-time video abstraction, ACM Transactions on Graphics, vol.25, issue.3, pp.1221-1226, 2006.
DOI : 10.1145/1141911.1142018

J. Xiao, H. Cheng, H. Sawhney, C. Rao, and M. Isnardi, Bilateral Filtering-Based Optical Flow Estimation with Occlusion Detection, ECCV, pp.211-224, 2006.
DOI : 10.1007/11744023_17

W. Wong, A. Chung, and S. Yu, Trilateral filtering for biomedical images, 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821), pp.820-823, 2004.
DOI : 10.1109/ISBI.2004.1398664

M. Elad, On the origin of the bilateral filter and ways to improve it, IEEE Transactions on Image Processing, vol.11, issue.10, pp.1141-1151, 2002.
DOI : 10.1109/TIP.2002.801126

A. Buades, B. Coll, and J. Morel, Neighborhood filters and PDE???s, Numerische Mathematik, vol.23, issue.1, pp.1-34, 2006.
DOI : 10.1007/s00211-006-0029-y

T. Jones, F. Durand, and M. Desbrun, Non-iterative, feature-preserving mesh smoothing, ACM Trans. Graph, vol.22, issue.3, 2003.
DOI : 10.1145/1201775.882367
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.73

S. Fleishman, I. Drori, and D. Cohen-or, Bilateral mesh denoising, ACM Transactions on Graphics, vol.22, issue.3, pp.950-953, 2003.
DOI : 10.1145/882262.882368

S. Paris, H. Briceño, and F. Sillion, Capture of hair geometry from multiple images, ACM Transactions on Graphics, vol.23, issue.3, pp.712-719, 2004.
DOI : 10.1145/1015706.1015784
URL : https://hal.archives-ouvertes.fr/inria-00510161

J. Lee and S. Y. Shin, General construction of time-domain filters for orientation data, IEEE Trans. on Visualization and Computer Graphics, vol.8, issue.2, pp.119-128, 2002.

J. Johnstone and J. Williams, Rational control of orientation for animation, Graphics Interface '95, pp.179-186, 1995.

Y. C. Fang, C. C. Hsieh, M. J. Kim, J. J. Chang, and T. C. Woo, Real time motion fairing with unit quaternions, Computer-Aided Design, vol.30, issue.3, pp.191-198, 1998.
DOI : 10.1016/S0010-4485(97)00057-2

A. Héloir, N. Courty, S. Gibet, and F. Multon, Temporal alignment of communicative gesture sequences. Computer Animation and Virtual Worlds (selected best papers from CASA'06), pp.347-357, 2006.

M. P. Johnson, Exploiting quaternions to support expressive interactive character motion, 2003.

T. Fletcher, C. Lu, S. Pizer, and S. Joshi, Principal Geodesic Analysis for the Study of Nonlinear Statistics of Shape, IEEE Transactions on Medical Imaging, vol.23, issue.8, pp.995-1005, 2004.
DOI : 10.1109/TMI.2004.831793

S. Said, N. Courty, N. Lebihan, and S. J. Sangwine, Exact Principal Geodesic Analysis for Data on SO(3), Proceedings of the 15th European Signal Processing Conference, EUSIPCO-2007 15th European Signal Processing Conference Département Images et Signal, pp.1700-1705, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00494170

S. Sommer, F. Lauze, and M. Nielsen, The differential of the exponential map, jacobi fields and exact principal geodesic analysis, 1008.

S. Sommer, F. Lauze, S. Hauberg, and M. Nielsen, Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations, ECCV 2010, pp.43-56, 2010.
DOI : 10.1007/978-3-642-15567-3_4

M. Tournier, X. Wu, N. Courty, E. Arnaud, and L. Reveret, Motion Compression using Principal Geodesics Analysis, Computer Graphics Forum, vol.29, issue.2, 2009.
DOI : 10.1111/j.1467-8659.2009.01375.x
URL : https://hal.archives-ouvertes.fr/inria-00590253

N. Courty and A. Cuzol, Conditional Stochastic Simulation for Character Animation Computer Animation and Virtual Worlds (best selected papers from CASA, pp.1-10, 2010.

N. Courty, T. Burger, and P. Marteau, Geodesic Analysis on the Gaussian RKHS Hypersphere, proceedings of ECML-PKDD 2012, LNCS, Royaume-Uni, 2012.
DOI : 10.1007/978-3-642-33460-3_25
URL : https://hal.archives-ouvertes.fr/hal-00710683

L. Ljung, System Identification -Theory For the User, N.J, 1999.

K. P. Körding and D. M. Wolpert, Bayesian integration in sensorimotor learning, Nature, vol.427, issue.6971, pp.244-247, 2004.
DOI : 10.1038/nature02169

S. Gibet and P. F. Marteau, A self-organized model for the control, planning and learning of nonlinear multi-dimensional systems using a sensory feedback, Applied Intelligence, vol.3, issue.4, pp.337-349, 1994.
DOI : 10.1007/BF00872473

Y. Nakamura and H. Hanafusa, Inverse Kinematic Solutions With Singularity Robustness for Robot Manipulator Control, Journal of Dynamic Systems, Measurement, and Control, vol.108, issue.3, pp.163-171, 1986.
DOI : 10.1115/1.3143764

A. Maciejewski, Dealing with the ill-conditioned equations of motion for articulated figures, IEEE Computer Graphics and Applications, vol.10, issue.3, pp.63-71, 1990.
DOI : 10.1109/38.55154

N. Courty, E. Marchand, and B. Arnaldi, Through-the-eyes control of a virtual humanô Od, Proc. of Computer Animation, pp.74-83, 2001.

B. , L. Callennec, and R. Boulic, Interactive motion deformation with prioritized constraints, Graphical Models, Références, vol.68, issue.2, pp.175-193, 2006.

E. A. Wan and R. Van-der-merwe, The unscented Kalman filter for nonlinear estimation, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373), 2000.
DOI : 10.1109/ASSPCC.2000.882463

S. Tak and H. Ko, A physically-based motion retargeting filter, ACM Transactions on Graphics, vol.24, issue.1, pp.98-117, 2005.
DOI : 10.1145/1037957.1037963

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

A. Doucet, N. De-freitas, and N. Gordon, Sequential Monte Carlo methods in practice, 2001.
DOI : 10.1007/978-1-4757-3437-9

N. Courty and E. Arnaud, Sequential monte carlo inverse kinematics, Research Report, vol.6426, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00194947

M. L. Stein, Interpolation of Spatial Data: Some Theory for Kriging, 1999.
DOI : 10.1007/978-1-4612-1494-6

C. Edward-rasmussen and C. K. Williams, Gaussian Processes for Machine Learning, 2005.

T. B. Moeslund, A. Hilton, and V. Kruger, A survey of advances in vision-based human motion capture and analysis, Computer Vision and Image Understanding, vol.104, issue.2-3, pp.90-126, 2006.
DOI : 10.1016/j.cviu.2006.08.002

Y. Cao, W. C. Tien, P. Faloutsos, and F. Pighin, Expressive speech-driven facial animation, ACM Transactions on Graphics, vol.24, issue.4, pp.1283-302, 2005.
DOI : 10.1145/1095878.1095881
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.7008

Z. Deng, U. Newmann, J. P. Lewis, T. Kim, M. Bulut et al., Expressive Facial Animation Synthesis by Learning Speech Coarticulation and Expression Spaces, IEEE Transactions on Visualization and Computer Graphics, vol.12, issue.6, pp.1523-1557, 2006.
DOI : 10.1109/TVCG.2006.90

X. Liu, T. Mao, S. Xia, Y. Yu, and Z. Wang, Facial animation by optimized blendshapes from motion capture data, Computer Animation and Virtual Worlds, vol.6, issue.4, pp.3-4235, 2008.
DOI : 10.1002/cav.248

L. Csató and M. Opper, Sparse On-Line Gaussian Processes, Neural Computation, vol.14, issue.3, pp.641-68, 2002.
DOI : 10.1109/34.735807

X. Ma and Z. Deng, Natural eye motion synthesis by modeling gaze-head coupling, IEEE Virtual Reality Conference, pp.143-50, 2009.

T. Warabi, The reaction time of eye-head coordination in man, Neuroscience Letters, vol.6, issue.1, pp.47-51, 1977.
DOI : 10.1016/0304-3940(77)90063-5

A. Héloir, M. Kipp, S. Gibet, and N. Courty, Evaluating Data-Driven Style Transformation for Gesturing Embodied Agents, Intelligent Virtual Agent (IVA 2008) Intelligent Virtual Agent, pp.215-222, 2008.
DOI : 10.1007/978-3-540-85483-8_22

R. Mcdonnell, M. Breidt, and H. Bülthoff, Render me real?, ACM Transactions on Graphics, vol.31, issue.4, pp.91-99, 2012.
DOI : 10.1145/2185520.2185587

M. Vicovaro, L. Hoyet, L. Burigana, and C. O. Sullivan, Evaluating the plausibility of edited throwing animations, Proc. of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA '12, pp.175-182, 2012.

L. Hoyet, F. Multon, A. Lecuyer, and T. Komura, Perception Based Real-Time Dynamic Adaptation of Human Motions, Motion in Games, pp.266-277, 2010.
DOI : 10.1007/978-3-642-16958-8_25
URL : https://hal.archives-ouvertes.fr/inria-00535979

R. Mcdonnell, M. Larkin, S. Dobbyn, S. Collins, and C. O. Sullivan, Clone attack! Perception of crowd variety, ACM Transactions on Graphics, vol.27, issue.3, pp.1-8, 2008.
DOI : 10.1145/1360612.1360625

R. Mcdonnell, M. Larkin, B. Hernandez, I. Rudomín, and C. O. Sullivan, Eye-catching crowds: saliency based selective variation, 2009.

A. Majkowska, V. B. Zordan, and P. Faloutsos, Automatic splicing for hand and body animations, ACM SIGGRAPH 2006 Sketches on , SIGGRAPH '06, pp.309-316, 2006.
DOI : 10.1145/1179849.1179889

J. Starck and A. Hilton, Surface Capture for Performance-Based Animation, IEEE Computer Graphics and Applications, vol.27, issue.3, pp.21-31, 2007.
DOI : 10.1109/MCG.2007.68

K. J. Choi and H. S. Ko, Online motion retargetting, The Journal of Visualization and Computer Animation, vol.61, issue.5, pp.223-235, 2000.
DOI : 10.1002/1099-1778(200012)11:5<223::AID-VIS236>3.0.CO;2-5

R. Kulpa, F. Multon, and B. Arnaldi, Morphology-independent representation of motions for interactive human-like animation, Computer Graphics Forum, vol.7, issue.4, pp.343-352, 2005.
DOI : 10.1111/j.1467-8659.2005.00859.x
URL : https://hal.archives-ouvertes.fr/inria-00000220

C. Hecker, B. Raabe, R. Enslow, J. Deweese, J. Maynard et al., Real-time motion retargeting to highly varied user-created morphologies, ACM Transactions on Graphics, vol.27, issue.3, pp.1-11, 2008.
DOI : 10.1145/1360612.1360626

E. Ho, T. Komura, and C. Tai, Spatial relationship preserving character motion adaptation, ACM Transactions on Graphics, vol.29, issue.4, pp.1-8, 2010.
DOI : 10.1145/1778765.1778770

D. Bertram, J. Kuffner, R. Dillmann, and T. Asfour, An integrated approach to inverse kinematics and path planning for redundant manipulators, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., pp.1874-1879, 2006.
DOI : 10.1109/ROBOT.2006.1641979

L. Zhang, M. C. Lin, D. Manocha, and J. Pan, A hybrid approach for simulating human motion in constrained environments, Computer Animation and Virtual Worlds, vol.21, pp.3-4137, 2010.

T. Le-naour, N. Courty, and S. Gibet, Cinématique guidée par les distances. Revue Electronique Francophone d, Informatique Graphique (REFIG), vol.6, issue.1, 2012.

A. Héloir and S. Gibet, A Qualitative and Quantitative Characterisation of Style in Sign Language Gestures, Gesture in Human-Computer Interaction and Simulation, 2007.
DOI : 10.1007/3-540-46616-9_25

D. Thalmann and S. R. Musse, Crowd Simulation, 2007.

N. Pelechano, J. Allbeck, and N. Badler, Virtual Crowds: Methods, Simulation, and Control. Synthesis Lectures on Computer Graphics and Animation, 2008.

S. , R. Musse, and D. Thalmann, Hierarchical model for real time simulation of virtual human crowds, In IEEE Trans. on Vis and Comp. Graph, vol.7, issue.2, pp.152-164, 2001.

M. Sung, M. Gleicher, and S. Chenney, Scalable behaviors for crowd simulation, Computer Graphics Forum, vol.21, issue.3, pp.519-528, 2004.
DOI : 10.1109/38.708559

C. W. Reynolds, Flocks, herds, and schools: A distributed behavioral model, Graph.: Proc. of SIGGRAPH, pp.25-34, 1987.

D. Helbing, I. Farkas, and T. Vicsek, Simulating dynamical features of escape panic, Nature, vol.407, issue.6803, pp.487-490, 2000.
DOI : 10.1038/35035023

S. Paris, J. Pettre, and S. Donikian, Pedestrian steering for crowd simulation: A predictive approach, Proc. of Eurographics), 2007.

S. J. Guy, J. Chhugani, S. Curtis, P. Dubey, M. C. Lin et al., Pledestrians: A least-effort approach to crowd simulation, Symposium on Computer Animation, SCA'10, 2010.

J. Ond?ej, J. Pettré, A. Olivier, and S. Donikian, A synthetic-vision based steering approach for crowd simulation, Proc. SIGGRAPH 2010), pp.1-1239, 2010.

N. Pelechano and N. Badler, Modeling Crowd and Trained Leader Behavior during Building Evacuation, IEEE Computer Graphics and Applications, vol.26, issue.6, pp.80-86, 2006.
DOI : 10.1109/MCG.2006.133

R. L. Hughes, A continuum theory for the flow of pedestrians, Transportation Research Part B: Methodological, vol.36, issue.6, pp.507-535, 2002.
DOI : 10.1016/S0191-2615(01)00015-7

A. Treuille, S. Cooper, and Z. Popovic, Continuum crowds, Proc. ACM SIGGRAPH, pp.1160-1168, 2006.
DOI : 10.1145/1141911.1142008

L. Pimenta, N. Michael, R. Mesquita, G. Pereira, and V. Kumar, Control of swarms based on Hydrodynamic models, 2008 IEEE International Conference on Robotics and Automation, pp.1948-1953, 2008.
DOI : 10.1109/ROBOT.2008.4543492

R. Narain, A. Golas, S. Curtis, and M. C. Lin, Aggregate dynamics for dense crowd simulation, Proc. SIGGRAPH 2009), pp.1-122, 2009.

B. Ulicny, P. Ciechomski, and D. Thalmann, Crowdbrush: interactive authoring of real-time crowd scenes, Symposium on Computer Animation'04, SCA '04, pp.243-252, 2004.

S. Chenney, Flow tiles, Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation , SCA '04, pp.233-242, 2004.
DOI : 10.1145/1028523.1028553

X. Jin, J. Xu, C. Wang, S. Huang, and J. Zhang, Interactive control of large-crowd navigation in virtual environments using vector fields, IEEE Computer Graphics and Applications, vol.28, pp.37-46, 2008.

M. Park, Guiding flows for controlling crowds. The Visual Computer, pp.1383-1391, 2010.

S. Patil, J. Van-den-berg, S. Curtis, M. C. Lin, and D. Manocha, Directing Crowd Simulations Using Navigation Fields, IEEE Transactions on Visualization and Computer Graphics, vol.17, issue.2, pp.244-254, 2011.
DOI : 10.1109/TVCG.2010.33
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.183.7823

N. Courty and T. Corpetti, Crowd motion capture, Computer Animation and Virtual Worlds, vol.12, issue.4-5, pp.361-370, 2007.
DOI : 10.1002/cav.199
URL : https://hal.archives-ouvertes.fr/hal-00493381

T. Kwon, K. Hoon-lee, J. Lee, and S. Takahashi, Group motion editing, Proc. ACM SIGGRAPH, 2008.
DOI : 10.1145/1399504.1360679

S. Takahashi, K. Yoshida, T. Kwon, K. H. Lee, J. Lee et al., Spectral-Based Group Formation Control, Proc. Eurographics, pp.639-648, 2009.
DOI : 10.1111/j.1467-8659.2009.01404.x
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.4622

B. Zhan, D. N. Monekosso, P. Remagnino, S. A. Velastin, and L. Xu, Crowd analysis: a survey, Machine Vision and Applications, vol.26, issue.9, pp.5-6345, 2008.
DOI : 10.1007/s00138-008-0132-4
URL : http://eprints.kingston.ac.uk/8264/

S. Cho, T. W. Chow, and C. Leung, A neural-based crowd estimation by hybrid global learning algorithm, IEEE Tra. on SMC, vol.29, issue.4, pp.535-541, 1999.

C. S. Regazzoni and A. Tesei, Distributed data fusion for real-time crowding estimation, Signal Processing, vol.53, issue.1, pp.47-63, 1996.
DOI : 10.1016/0165-1684(96)00075-8

D. B. Yang, H. H. González-ba-nos, and L. J. Guibas, Counting people in crowds with a real-time network of simple image sensors, Proceedings Ninth IEEE International Conference on Computer Vision, p.122, 2003.
DOI : 10.1109/ICCV.2003.1238325

E. Kalogerakis, O. Vesselova, J. Hays, A. Efros, and A. Hertzmann, You'll never walk alone: modeling social behavior for multi-target tracking, ICCV, 2009.

A. Elgammal and L. S. Davis, Probabilistic framework for segmenting people under occlusion, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.145-152, 2001.
DOI : 10.1109/ICCV.2001.937617

S. Lin, J. Chen, and H. Chai, Estimation of number of people in crowded scenes using perspective transformation, IEEE Tra. on SMC, issue.6, pp.31645-654, 2001.

T. Zhao and R. Nevatia, Bayesian human segmentation in crowded situations, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.459-466, 2003.
DOI : 10.1109/CVPR.2003.1211503

V. Rabaud and S. Belongie, Counting Crowded Moving Objects, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.705-711, 2006.
DOI : 10.1109/CVPR.2006.92

M. Rodriguez, S. Ali, and T. Kanade, Tracking in unstructured crowded scenes, 2009 IEEE 12th International Conference on Computer Vision, pp.1-8, 2009.
DOI : 10.1109/ICCV.2009.5459301

A. Treuille, S. Cooper, and Z. Popovic, Continuum crowds, Proc. ACM SIGGRAPH 2006, pp.1160-1168, 2006.
DOI : 10.1145/1141911.1142008

P. Allain, N. Courty, and T. Corpetti, Crowd Flow Characterization with Optimal Control Theory, ACCV, Xi'an, China, 2009.
DOI : 10.1007/978-3-642-12304-7_27
URL : https://hal.archives-ouvertes.fr/hal-00493443

R. Mehran, A. Oyama, and M. Shah, Abnormal crowd behavior detection using social force model, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.935-942, 2009.
DOI : 10.1109/CVPR.2009.5206641

N. Courty and T. Corpetti, Crowd motion capture, Computer Animation and Virtual Worlds, vol.12, issue.4-5, pp.361-370, 2007.
DOI : 10.1002/cav.199
URL : https://hal.archives-ouvertes.fr/hal-00493381

S. Ali and M. Shah, A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-6, 2007.
DOI : 10.1109/CVPR.2007.382977

E. L. Andrade, S. Blunsden, and R. B. Fisher, Modelling Crowd Scenes for Event Detection, 18th International Conference on Pattern Recognition (ICPR'06), pp.175-178, 2006.
DOI : 10.1109/ICPR.2006.806

B. A. Boghossian and S. A. Velastin, Motion-based machine vision techniques for the management of large crowds, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357), pp.961-964, 2002.
DOI : 10.1109/ICECS.1999.813392

K. Lee, M. Choi, Q. Hong, and J. Lee, Group behavior from video: a data-driven approach to crowd simulation, ACM SIGGRAPH/Eurographics Symp. on Computer Animation, SCA'07, pp.109-118, 2007.

A. Lerner, Y. Chrysanthou, and D. Lischinski, Crowds by Example, Proc. of Eurographics), 2007.
DOI : 10.1111/j.1467-8659.2004.00783.x

B. Horn and B. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1651

P. Allain, N. Courty, and T. Corpetti, Crowd Flow Characterization with Optimal Control Theory, Ninth Asian Conference on Computer Vision (ACCV 2009) Ninth Asian Conference on Computer Vision, pp.279-290, 2009.
DOI : 10.1007/978-3-642-12304-7_27
URL : https://hal.archives-ouvertes.fr/hal-00493443

J. Lions, Optimal control of systems governed by PDEs, 1971.

F. X. Le-dimet and O. Talagrand, Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, Tellus A: Dynamic Meteorology and Oceanography, vol.109, issue.2, pp.97-110, 1986.
DOI : 10.3402/tellusa.v38i2.11706

R. Kimmel and J. Sethian, Optimal algorithm for shape from shading and path planning, Journal of Mathematical Imaging and Vision, vol.14, issue.3, pp.237-244, 2001.
DOI : 10.1023/A:1011234012449

O. Talagrand, Variational Assimilation. Adjoint Equations, 2002.
DOI : 10.1007/978-94-010-0029-1_4
URL : https://hal.archives-ouvertes.fr/hal-01136782

B. Lucas and T. Kanade, An iterative image registration technique with an application to stereo vision, Proc. Seventh Int. Joint Conf. on Art. Intell, pp.674-679, 1981.

E. Andrade, S. Blunsden, and R. Fisher, Modelling Crowd Scenes for Event Detection, 18th International Conference on Pattern Recognition (ICPR'06), pp.175-178, 2006.
DOI : 10.1109/ICPR.2006.806

B. Zhan, D. N. Monekosso, P. Remagnino, S. A. Velastin, and L. Xu, Crowd analysis: a survey, Machine Vision and Applications, vol.26, issue.9, pp.5-6345, 2008.
DOI : 10.1007/s00138-008-0132-4

L. Fei-fei, R. Fergus, and P. Perona, One-shot learning of object categories, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.4, pp.594-611, 2006.
DOI : 10.1109/TPAMI.2006.79

S. Baker, D. Scharstein, J. P. Lewis, S. Roth, M. J. Black et al., A database and evaluation methodology for optical flow, ICCV, pp.1-8, 2007.

L. Sigal, A. Balan, and M. J. Black, HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human??Motion, International Journal of Computer Vision, vol.74, issue.3, pp.4-27, 2010.
DOI : 10.1007/s11263-009-0273-6

F. Qureshi and D. Terzopoulos, Surveillance in Virtual Reality: System Design and Multi-Camera Control, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383071

G. R. Taylor, A. J. Chosak, and P. C. Brewer, OVVV: Using Virtual Worlds to Design and Evaluate Surveillance Systems, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383518

S. R. Musse, M. Paravisi, R. Rodrigues, J. C. Jacques-jr, and C. R. Jung, Using synthetic ground truth data to evaluate computer vision techniques, Proc. of int. workshop on PETS, pp.25-32, 2007.

R. Soraia, C. R. Musse, J. C. Jung, A. Jacques, and . Braun, Using computer vision to simulate the motion of virtual agents, Computer Animation and Virtual Worlds, vol.18, issue.2, pp.83-93, 2007.

M. Moussaid, D. Helbing, S. Garnier, A. Johansson, M. Combe et al., Experimental study of the behavioural mechanisms underlying self-organization in human crowds, Proceedings of the Royal Society B: Biological Sciences, vol.72, issue.45, pp.2762755-2762, 1668.
DOI : 10.1073/pnas.0704916104
URL : https://hal.archives-ouvertes.fr/hal-00435743

I. Taras, D. J. Lakoba, N. M. Kaup, and . Finkelstein, Modifications of the helbing-molnár-farkas-vicsek social force model for pedestrian evolution, Simulation, vol.81, issue.5, pp.339-352, 2005.

D. Helbing and P. Molnar, Social force model for pedestrian dynamics, Physical Review E, vol.51, issue.5, p.4282, 1995.
DOI : 10.1103/PhysRevE.51.4282
URL : http://arxiv.org/abs/cond-mat/9805244

T. Driemeyer, Rendering with mental ray, 2001.

N. Courty and T. Corpetti, Crowd Motion Capture Computer Animation and Virtual Worlds (selected best papers from CASA, pp.4-5361, 2007.

P. Allain, N. Courty, and T. Corpetti, Particle swarm control, Optimal Control Applications and Methods, vol.2, issue.3, 1997.
DOI : 10.1002/oca.2095
URL : https://hal.archives-ouvertes.fr/hal-00904044

A. Mcnamara, A. Treuille, Z. Popovi´cpopovi´c, and J. Stam, Fluid control using the adjoint method, Proc. SIGGRAPH 2004), pp.449-456, 2004.
DOI : 10.1145/1015706.1015744

C. Wojtan, P. Mucha, and G. Turk, Keyframe control of complex particle systems using the adjoint method, Symposium on Computer Animation'06, pp.15-23, 2006.

Z. Khan, T. Balch, and F. Dellaert, Mcmc-based particle filtering for tracking a variable number of interacting targets. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.27, issue.11, pp.1805-1819, 2005.

K. Smith, D. Gatica-perez, and J. Odobez, Using Particles to Track Varying Numbers of Interacting People, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.962-969, 2005.
DOI : 10.1109/CVPR.2005.361

C. Twigg and D. James, Many-worlds browsing for control of multibody dynamics, ACM Trans. Graph, vol.26, 2007.

B. D. Lucas, Generalized image matching by the method of differences, 1984.

. Anonymousauthors, Particle swarm control. submitted to Swarm Intelligence, 2012.

C. Cortes and V. Vapnik, Support vector machine, Machine Learning, pp.273-297, 1995.

B. Schölkopf, A. Smola, and K. R. Müller, Kernel principal component analysis, Artificial Neural Networks - ICANN'97, pp.583-588, 1997.
DOI : 10.1007/BFb0020217

B. Schölkopf and A. J. Smola, Learning with kernels: Support vector machines, regularization, optimization, and beyond, 2002.

J. Lafferty and G. Lebanon, Diffusion kernels on statistical manifolds, Journal of Machine Learning Research, vol.6, pp.129-163, 2005.

S. Said, N. Courty, N. Lebihan, and S. J. Sangwine, Exact principal geodesic analysis for data on so(3), Proceedings of EUSIPCO 2007, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00494170

H. Karcher, Riemannian center of mass and mollifier smoothing, Communications on Pure and Applied Mathematics, vol.3, issue.5, pp.509-541, 1977.
DOI : 10.1002/cpa.3160300502

W. S. Kendall, Convexity and the Hemisphere, Journal of the London Mathematical Society, vol.2, issue.3, p.567, 1991.
DOI : 10.1112/jlms/s2-43.3.567

S. Mika, B. Schölkopf, A. J. Smola, K. R. Müller, M. Scholz et al., Kernel pca and de-noising in feature spaces, Advances in Neural Information Processing Systems, pp.536-542, 1999.

J. Kwok and I. Tsang, The Pre-Image Problem in Kernel Methods, IEEE Transactions on Neural Networks, vol.15, issue.6, pp.1517-1525, 2004.
DOI : 10.1109/TNN.2004.837781

]. D. Huang, Y. Tian, and F. De-la-torre, Local isomorphism to solve the pre-image problem in kernel methods, CVPR 2011, pp.2761-2768, 2011.
DOI : 10.1109/CVPR.2011.5995685