L. N. Abdullah and S. A. Noah, Integrating Audio Visual Data for Human Action Detection, 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation, pp.242-246, 2008.
DOI : 10.1109/CGIV.2008.65

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.2274-2282, 2012.
DOI : 10.1109/TPAMI.2012.120

A. Angeli, D. Filliat, S. Doncieux, and J. Meyer, Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words, IEEE Transactions on Robotics, vol.24, issue.5, pp.1027-1037, 2008.
DOI : 10.1109/TRO.2008.2004514
URL : https://hal.archives-ouvertes.fr/hal-00652598

J. Baraglia, M. Cakmak, Y. Nagai, R. Rao, and M. Asada, Initiative in robot assistance during collaborative task execution, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp.67-74, 2016.
DOI : 10.1109/HRI.2016.7451735

J. Bohg, K. Hausman, B. Sankaran, O. Brock, D. Kragic et al., Interactive perception: Leveraging action in perception and perception in action. arXiv preprint, 2016.

R. Camoriano, G. Pasquale, C. Ciliberto, L. Natale, L. Rosasco et al., Incremental object recognition in robotics with extension to new classes in constant time. arXiv preprint, 2016.

A. Collet, D. Berenson, S. S. Srinivasa, and D. Ferguson, Object recognition and full pose registration from a single image for robotic manipulation, 2009 IEEE International Conference on Robotics and Automation, pp.48-55, 2009.
DOI : 10.1109/ROBOT.2009.5152739
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.8416

H. Dahlkamp, A. Kaehler, D. Stavens, S. Thrun, and G. Bradski, Selfsupervised monocular road detection in desert terrain, Proceedings of Robotics: Science and Systems, 2006.
DOI : 10.15607/rss.2006.ii.005
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.74.503

J. Dumora, F. Geffard, C. Bidard, N. A. Aspragathos, and P. Fraisse, Robot Assistance Selection for Large Object Manipulation with a Human, 2013 IEEE International Conference on Systems, Man, and Cybernetics, pp.1828-1833, 2013.
DOI : 10.1109/SMC.2013.315

A. Gijsberts and G. Metta, Real-time model learning using Incremental Sparse Spectrum Gaussian Process Regression, Neural Networks, vol.41, pp.59-69, 2013.
DOI : 10.1016/j.neunet.2012.08.011

W. Gong, J. Gonzàlez, J. M. Tavares, and F. X. Roca, A New Image Dataset on Human Interactions, pp.204-209, 2012.
DOI : 10.1007/978-3-642-31567-1_20

P. Iravani, P. Hall, D. Beale, C. Charron, and Y. Hicks, Visual object classification by robots, using on-line, self-supervised learning, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp.1092-1099, 2011.
DOI : 10.1109/ICCVW.2011.6130372

B. S. Sung and C. Ponce, Human activity detection from rgbd images, AAAI workshop on Pattern, Activity and Intent Recognition (PAIR), 2011.

J. Kenney, T. Buckley, and O. Brock, Interactive segmentation for manipulation in unstructured environments, 2009 IEEE International Conference on Robotics and Automation, pp.1377-1382, 2009.
DOI : 10.1109/ROBOT.2009.5152393

M. Krainin, B. Curless, and D. Fox, Autonomous generation of complete 3D object models using next best view manipulation planning, 2011 IEEE International Conference on Robotics and Automation, pp.5031-5037, 2011.
DOI : 10.1109/ICRA.2011.5980429

A. Kuznetsova, S. J. Hwang, B. Rosenhahn, and L. Sigal, Expanding object detector's Horizon: Incremental learning framework for object detection in videos, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.28-36, 2015.
DOI : 10.1109/CVPR.2015.7298597

K. Lai, L. Bo, X. Ren, and D. Fox, A large-scale hierarchical multiview rgb-d object dataset, 2011.
DOI : 10.1109/icra.2011.5980382
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.1598

S. Lee, J. Lim, and I. H. Suh, Incremental learning from a single seed image for object detection, Intelligent Robots and Systems (IROS) IEEE/RSJ International Conference on, pp.1905-1912, 2015.

G. Pasquale, C. Ciliberto, F. Odone, L. Rosasco, L. Natale et al., Teaching icub to recognize objects using deep convolutional neural networks, Proc. Work. Mach. Learning Interactive Syst, pp.21-25, 2015.

U. Reiser, C. P. Connette, J. Fischer, J. Kubacki, A. Bubeck et al., 3 - creating a product vision for service robot applications by integrating design and technology, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.1992-1998, 2009.
DOI : 10.1109/IROS.2009.5354526

J. Rituerto, A. C. Murillo, J. Koå, and ?. Aecka, Label propagation in videos indoors with an incremental non-parametric model update, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2383-2389, 2011.
DOI : 10.1109/IROS.2011.6094997

E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, ORB: An efficient alternative to SIFT or SURF, 2011 International Conference on Computer Vision, pp.2564-2571, 2011.
DOI : 10.1109/ICCV.2011.6126544
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.370.4395

J. Sinapov, C. Schenck, and A. Stoytchev, Learning relational object categories using behavioral exploration and multimodal perception, 2014 IEEE International Conference on Robotics and Automation (ICRA), pp.5691-5698, 2014.
DOI : 10.1109/ICRA.2014.6907696
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.4503

A. Singh, J. Sha, K. S. Narayan, T. Achim, and P. Abbeel, BigBIRD: A large-scale 3D database of object instances, 2014 IEEE International Conference on Robotics and Automation (ICRA), pp.509-516, 2014.
DOI : 10.1109/ICRA.2014.6906903

A. Vatakis and K. Pastra, A multimodal dataset of spontaneous speech and movement production on object affordances. Scientific Data, p.150078, 2016.

A. Yao, J. Gall, C. Leistner, and L. Van-gool, Interactive object detection, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.3242-3249, 2012.
DOI : 10.1109/CVPR.2012.6248060