R. Achanta, A. Shaji, K. Smith, P. Lucchi, S. Fua et al., SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.11, pp.342274-2282, 2012.
DOI : 10.1109/TPAMI.2012.120

S. Allin and D. Ramanan, Assessment of Post-Stroke Functioning using Machine Vision, MVA, 2007.

B. D. Argall, S. Chernova, M. Veloso, and B. Browning, A survey of robot learning from demonstration, Robotics and Autonomous Systems, vol.57, issue.5, pp.469-483, 2009.
DOI : 10.1016/j.robot.2008.10.024

V. Athitsos and S. Sclaroff, Estimating 3D hand pose from a cluttered image, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.432-442, 2003.
DOI : 10.1109/CVPR.2003.1211500

L. Bourdev and J. Malik, Poselets: Body part detectors trained using 3D human pose annotations, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459303

M. Bouzit, G. Burdea, G. Popescu, and R. Boian, The Rutgers Master II-new design force-feedback glove, IEEE/ASME Transactions on Mechatronics, vol.7, issue.2, pp.256-263, 2002.
DOI : 10.1109/TMECH.2002.1011262

I. M. Bullock, T. Feix, and A. M. Dollar, The Yale human grasping dataset: Grasp, object, and task data in household and machine shop environments, The International Journal of Robotics Research, vol.7, issue.3, pp.251-255, 2015.
DOI : 10.1109/TOH.2014.2326867

M. Cai, K. M. Kitani, and Y. Sato, A scalable approach for understanding the visual structures of hand grasps, ICRA, 2015.

M. R. Cutkosky, On grasp choice, grasp models, and the design of hands for manufacturing tasks, IEEE Transactions on Robotics and Automation, vol.5, issue.3, pp.269-279, 1989.
DOI : 10.1109/70.34763

D. Damen, A. P. Gee, W. W. Mayol-cuevas, and A. Calway, Egocentric Real-time Workspace Monitoring using an RGB-D camera, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012.
DOI : 10.1109/IROS.2012.6385829

D. Damen, T. Leelasawassuk, O. Haines, A. Calway, and W. W. Mayol-cuevas, You-do, i-learn: Discovering task relevant objects and their modes of interaction from multi-user egocentric video, BMVC, 2014.

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

A. Fathi, X. Ren, and J. Rehg, Learning to recognize objects in egocentric activities, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995444

T. Feix, R. Pawlik, H. Schmiedmayer, J. Romero, and D. Kragic, A comprehensive grasp taxonomy, RSS Workshop on Understanding the Human Hand for Advancing Robotic Manipulation, 2009.

A. R. Fielder and M. J. Moseley, Does stereopsis matter in humans?, Eye, vol.7, issue.2, pp.233-238, 1996.
DOI : 10.1016/0042-6989(92)90207-Y

M. A. Goodrich and A. C. Schultz, Human-robot interaction: a survey. Foundations and trends in human-computer interaction, pp.203-275, 2007.

R. P. Harrison, Nonverbal communication. Human Communication As a Field of Study: Selected Contemporary Views, 1989.

D. Huang, W. Ma, M. Ma, and K. M. Kitani, How do we use our hands? discovering a diverse set of common grasps, CVPR, 2015.

. Intel, Perceptual computing sdk, 2013.

Y. Jang, S. Noh, H. J. Chang, T. Kim, and W. Woo, 3D Finger CAPE: Clicking Action and Position Estimation under Self-Occlusions in Egocentric Viewpoint, IEEE Transactions on Visualization and Computer Graphics, vol.21, issue.4, pp.501-510, 2015.
DOI : 10.1109/TVCG.2015.2391860

S. Khamis, T. J. , S. J. , K. C. , I. S. et al., Learning an efficient model of hand shape variation from depth images, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2015.7298869

M. Kölsch, An Appearance-Based Prior for Hand Tracking, ACIVS (2), pp.292-303, 2010.
DOI : 10.1007/978-3-642-17691-3_27

M. Kölsch and M. Turk, Hand tracking with flocks of features Interaction capture and synthesis, CVPR, pp.1187-872, 2005.

T. Kurata, T. Kato, M. Kourogi, K. Jung, and K. Endo, A functionally-distributed hand tracking method for wearable visual interfaces and its applications, MVA, 2002.

N. Kyriazis and A. A. Argyros, Physically Plausible 3D Scene Tracking: The Single Actor Hypothesis, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.9

N. Kyriazis and A. A. Argyros, Scalable 3D Tracking of Multiple Interacting Objects, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014.
DOI : 10.1109/CVPR.2014.438

J. Liu, F. Feng, Y. C. Nakamura, and N. S. Pollard, A taxonomy of everyday grasps in action, 2014 IEEE-RAS International Conference on Humanoid Robots, 2014.
DOI : 10.1109/HUMANOIDS.2014.7041420

S. Mann, J. Huang, R. Janzen, R. Lo, V. Rampersad et al., Blind navigation with a wearable range camera and vibrotactile helmet, Proceedings of the 19th ACM international conference on Multimedia, MM '11, 2011.
DOI : 10.1145/2072298.2072005

T. Moller, A Fast Triangle-Triangle Intersection Test, Journal of Graphics Tools, vol.1, issue.2, pp.25-30, 1997.
DOI : 10.1080/10867651.1997.10487472

I. Oikonomidis, N. Kyriazis, and A. A. Argyros, Tracking the articulated motion of two strongly interacting hands, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247885

T. Pham, A. Kheddar, A. Qammaz, and A. A. Argyros, Towards force sensing from vision: Observing hand-object interactions to infer manipulation forces, CVPR, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01356136

H. Pirsiavash and D. Ramanan, Detecting activities of daily living in first-person camera views, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6248010

X. Ren, C. C. Fowlkes, and J. Malik, Figure/Ground Assignment in Natural Images, Computer Vision?ECCV 2006, pp.614-627, 2006.
DOI : 10.1068/p5265

G. Rogez, J. S. Iii, and D. Ramanan, First-person pose recognition using egocentric workspaces, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2015.7299061

J. Romero, T. Feix, H. Kjellstrom, and D. Kragic, Spatiotemporal modeling of grasping actions, IROS, 2010.

J. Romero, H. Kjellström, C. H. Ek, and D. Kragic, Nonparametric hand pose estimation with object context, Image Vision Comput, issue.8, pp.31555-564, 2013.

J. Romero, H. Kjellstrom, and D. Kragic, Hands in action: real-time 3D reconstruction of hands in interaction with objects, 2010 IEEE International Conference on Robotics and Automation, pp.458-463
DOI : 10.1109/ROBOT.2010.5509753

A. Saxena, J. Driemeyer, J. Kearns, and A. Y. Ng, Robotic grasping of novel objects, NIPS, 2006.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition. CoRR, abs, 1409.

B. Stenger, A. Thayananthan, P. Torr, and R. Cipolla, Modelbased hand tracking using a hierarchical bayesian filter, pp.1372-1384, 2006.

J. Supancic, G. Rogez, Y. Yang, J. Shotton, and D. Ramanan, Depth-Based Hand Pose Estimation: Data, Methods, and Challenges, 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
DOI : 10.1109/ICCV.2015.217
URL : https://hal.archives-ouvertes.fr/hal-01237023

R. Wang and J. Popovic, Real-time hand-tracking with a color glove, ACM Trans on Graphics, vol.28, issue.3, 2009.