Computer vision-based classification of hand grip variations in neurorehabilitation, 2011 IEEE International Conference on Rehabilitation Robotics, pp.1-4, 2011. ,
DOI : 10.1109/ICORR.2011.5975421
Apraxias in neurodegenerative dementias, Apraxias in neurodegenerative dementias, p.42, 2015. ,
DOI : 10.4103/0253-7176.150817
, Clinical Neuropsychology, vol.128, issue.10, pp.215-235, 2003.
The rises and falls of disconnection syndromes, Brain, vol.128, issue.10, pp.2224-2239, 2005. ,
DOI : 10.1146/annurev.ne.18.030195.002043
Association, Diagnostic and statistical manual of mental disorders, text rev ,
Evaluation des apraxies gestuelles, pp.133-138, 2003. ,
Recognizing complex instrumental activities of daily living using scene information and fuzzy logic, Computer Vision and Image Understanding, vol.140, pp.68-82, 2015. ,
DOI : 10.1016/j.cviu.2015.04.005
Posture Recognition Based on Fuzzy Logic for Home Monitoring of the Elderly, IEEE Transactions on Information Technology in Biomedicine, vol.16, issue.5, pp.974-982, 2012. ,
DOI : 10.1109/TITB.2012.2208757
URL : https://hal.archives-ouvertes.fr/hal-00742239
Detecting activities of daily living in first-person camera views, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.2847-2854, 2012. ,
DOI : 10.1109/CVPR.2012.6248010
Generating unsupervised mod- 590 els for online long-term daily living activity recognition, Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference on, pp.186-190, 2015. ,
Recognition of Activities of Daily Living for Smart Home Environments, 2013 9th International Conference on Intelligent Environments, pp.173-180, 2013. ,
DOI : 10.1109/IE.2013.37
Ecological assessment of autonomy in instrumental activities of daily living in dementia patients by the means of an automatic video monitoring system, ICT for assessment and rehabilitation in Alzheimers disease and related disorders (2016) 29 Game-based human computer interaction using gesture recognition for rehabilitation, Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on, pp.595-600, 2013. ,
Gesture therapy: A vision-based system for upper extremity stroke rehabilitation, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, pp.3690-3693, 2010. ,
DOI : 10.1109/IEMBS.2010.5627458
Free-hand interaction with leap motion controller for stroke re- 610 habilitation, Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems, pp.1663-1668, 2014. ,
,
A new computer vision-based approach to aid the diagnosis of Parkinson's disease, Computer Methods and Programs in Biomedicine, vol.136, pp.79-88, 2016. ,
DOI : 10.1016/j.cmpb.2016.08.005
Gradient-based learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998. ,
DOI : 10.1109/5.726791
Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.620-1735, 1997. ,
DOI : 10.1016/0893-6080(88)90007-X
Design of the workstation for hand rehabilitation based on data glove, 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), pp.769-771, 2010. ,
DOI : 10.1109/BIBMW.2010.5703907
Development of hand rehabilitation system for paralysis patient?universal design using wire-driven mechanism?, in: Engineering in Medicine and Biology Society, EMBC 2009. Annual International Conference of the IEEE, pp.7122-7125, 2009. ,
Self-Correcting Pattern Recognition System of Surface EMG Signals for Upper Limb Prosthesis Control, IEEE Transactions on Biomedical Engineering, vol.61, issue.4, pp.1167-1176, 2014. ,
DOI : 10.1109/TBME.2013.2296274
Abstract, Infection Control & Hospital Epidemiology, vol.29, issue.04, pp.24-302, 2003. ,
DOI : 10.1067/mic.2000.107267
An adaptive home-use robotic rehabilitation system for the upper body, IEEE Journal of Translational Engineering in Health and Medicine, vol.2, pp.1-10, 2014. ,
DOI : 10.1109/JTEHM.2014.2314097
The treatment of phantom limb pain using immersive virtual reality: Three case studies, Disability and Rehabilitation, vol.62, issue.18, pp.1465-1469, 2007. ,
DOI : 10.1093/rheumatology/keh529
Vollenbroek- Hutten, Chronic pain rehabilitation with a serious game using multimodal input, Virtual Rehabilitation (ICVR), 2011 International Conference on, pp.645-646, 2011. ,
Evaluating a dancer's performance using kinect-based skeleton tracking, Proceedings of the 19th ACM international conference on Multimedia, MM '11, pp.659-662, 2011. ,
DOI : 10.1145/2072298.2072412
Real-time classification of dance gestures from skeleton animation, Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA '11, pp.147-156, 2011. ,
DOI : 10.1145/2019406.2019426
Sign language recognition and translation with kinect, IEEE Conf. on AFGR Sign language recognition using convolutional neural networks, in: Workshop at the European Conference on Computer Vision, pp.655-572, 2013. ,
Spherical Blurred Shape Model for 3-D Object and Pose Recognition: Quantitative Analysis and HCI Applications in Smart Environments, IEEE Transactions on Cybernetics, vol.44, issue.12, pp.1-1, 2014. ,
DOI : 10.1109/TCYB.2014.2307121
Video classification with Densely extracted HOG/HOF/MBH features: an evaluation of the accuracy/computational efficiency trade-off, International Journal of Multimedia Information Retrieval, vol.103, issue.3, pp.33-44, 2015. ,
DOI : 10.5244/C.23.124
Dense Trajectories and Motion Boundary Descriptors for Action Recognition, International Journal of Computer Vision, vol.73, issue.2, pp.60-79, 2013. ,
DOI : 10.1007/s11263-006-9794-4
URL : https://hal.archives-ouvertes.fr/hal-00803241
A Robust and Efficient Video Representation for Action Recognition, International Journal of Computer Vision, vol.103, issue.1, pp.219-238, 2016. ,
DOI : 10.1109/ICCV.2013.442
URL : https://hal.archives-ouvertes.fr/hal-01145834
Action Recognition with Improved Trajectories, 2013 IEEE International Conference on Computer Vision, pp.3551-3558, 2013. ,
DOI : 10.1109/ICCV.2013.441
URL : https://hal.archives-ouvertes.fr/hal-00873267
Realistic action recognition via sparsely-constructed Gaussian processes, Pattern Recognition, vol.47, issue.12, pp.3819-3827, 2014. ,
DOI : 10.1016/j.patcog.2014.07.006
Spatio-Temporal Laplacian Pyramid Coding for Action Recognition, IEEE Transactions on Cybernetics, vol.44, issue.6, pp.817-827, 2014. ,
DOI : 10.1109/TCYB.2013.2273174
Silhouette Analysis-Based Action Recognition Via Exploiting Human Poses, IEEE Transactions on Circuits and Systems for Video Technology, vol.23, issue.2, pp.23-236, 2013. ,
DOI : 10.1109/TCSVT.2012.2203731
A selective spatio-temporal interest point detector for human action recognition in complex scenes, 2011 International Conference on Computer Vision, pp.1776-1783, 2011. ,
DOI : 10.1109/ICCV.2011.6126443
, 685 [40] I. Laptev, On space-time interest points, International journal of computer vision, vol.64, issue.2-3, pp.107-123, 2005.
An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector, European conference on computer vision, pp.650-663, 2008. ,
DOI : 10.1109/ICCV.2007.4409049
A Spatio-Temporal Descriptor Based on 3D-Gradients, Procedings of the British Machine Vision Conference 2008, pp.690-275, 2008. ,
DOI : 10.5244/C.22.99
URL : https://hal.archives-ouvertes.fr/inria-00514853
Evaluation of local spatio-temporal features for action recognition, Procedings of the British Machine Vision Conference 2009, pp.124-125, 2009. ,
DOI : 10.5244/C.23.124
URL : https://hal.archives-ouvertes.fr/inria-00439769
Watch-n-patch: Unsupervised understanding of actions and relations, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.4362-4370, 2015. ,
DOI : 10.1109/CVPR.2015.7299065
Human action recognition by represent- 700 ing 3d skeletons as points in a lie group, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.588-595, 2014. ,
Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.724-731, 2014. ,
DOI : 10.1109/CVPR.2014.98
A decision forest based feature selection framework for action recognition from rgb-depth cameras, International Conference Image Analysis and Recognition, pp.705-648, 2013. ,
ChaLearn multi-modal gesture recognition 2013, Proceedings of the 15th ACM on International conference on multimodal interaction, ICMI '13, pp.365-368, 2013. ,
DOI : 10.1145/2522848.2532597
Structured Time Series Analysis for Human Action Segmentation and Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.7, pp.1414-1427, 2014. ,
DOI : 10.1109/TPAMI.2013.244
Group Sparsity and Geometry Constrained Dictionary Learning for Action Recognition from Depth Maps, 2013 IEEE International Conference on Computer Vision, pp.1809-1816, 2013. ,
DOI : 10.1109/ICCV.2013.227
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost, Computer Vision?ECCV, vol.50, issue.2, pp.720-359, 2006. ,
DOI : 10.1109/CVPR.2005.58
ImageNet classification with deep convolutional neural networks, Communications of the ACM, vol.60, issue.6, pp.1097-1105, 2012. ,
DOI : 10.1162/neco.2009.10-08-881
, convolutional neural networks for human action recognition, pp.725-53, 2013.
Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3593-3601, 2016. ,
DOI : 10.1109/CVPR.2016.391
Hands deep in deep learning for hand pose estimation, arXiv preprint ,
Real-time continuous pose recovery 735 of human hands using convolutional networks, ACM Transactions on Graphics (ToG), vol.33, issue.169, 2014. ,
P-CNN: Pose-Based CNN Features for Action Recognition, 2015 IEEE International Conference on Computer Vision (ICCV), pp.3218-3226, 2015. ,
DOI : 10.1109/ICCV.2015.368
Human Pose Estimation via Convolutional Part Heatmap Regression, European Conference on Computer Vision, pp.740-717, 2016. ,
DOI : 10.1109/CVPR.2016.335
,
Deep dynamic neural networks for multimodal gesture segmentation and 745 recognition, IEEE transactions on pattern analysis and machine intelligence, vol.38, issue.8, pp.1583-1597, 2016. ,
Learning hierarchical invariant spatiotemporal features for action recognition with independent subspace analysis, Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp.750-3361, 2011. ,
Spatio-Temporal Convolutional Sparse Auto-Encoder for Sequence Classification, Procedings of the British Machine Vision Conference 2012, pp.1-12, 2012. ,
DOI : 10.5244/C.26.124
URL : https://hal.archives-ouvertes.fr/hal-01353046
Long-term recurrent convolutional networks for visual recognition and description, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.2625-2634, 2015. ,
Sequential Deep Learning for Human Action Recognition, International Workshop on Human 760 Behavior Understanding, pp.29-39, 2011. ,
DOI : 10.1007/978-3-642-25446-8_4
URL : https://hal.archives-ouvertes.fr/hal-01354493
Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification, IEEE Transactions on Cybernetics ,
DOI : 10.1109/TCYB.2017.2662199
Effective 3D action recognition using EigenJoints, Journal of Visual Communication and Image Representation, vol.25, issue.1, p.765 ,
DOI : 10.1016/j.jvcir.2013.03.001
, Visual Communication and Image Representation, vol.25, issue.1, pp.2-11, 2014.
Deepcut: Joint subset partition and labeling for multi person pose estimation Conditional regression forests for human pose estimation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. 770 [67] M. Sun Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference, pp.2012-3394 ,
Action recognition based on a bag of 3D points, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, pp.9-14, 2010. ,
DOI : 10.1109/CVPRW.2010.5543273
The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection, 2013 IEEE International Conference on Computer Vision, pp.2752-2759, 2013. ,
DOI : 10.1109/ICCV.2013.342
, Otsu, A threshold selection method from gray-level histograms, IEEE Transactions on systems, man, and cybernetics, vol.9, issue.1, pp.780-62, 1979.
Very deep convolutional networks for large-scale image recognition ,
,
, Hierarchical Image Database, p.9, 2009.
Large-scale image retrieval with compressed Fisher vectors, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3384-3391, 2010. ,
DOI : 10.1109/CVPR.2010.5540009
Improving the fisher kernel for large- 790 scale image classification, European conference on computer vision, pp.143-156, 2010. ,
, Going deeper with convolutions Computer Vision and Pattern Recognition (CVPR), 2015. 795 URL http
How Transferable Are CNN-Based Features for Age and Gender Classification?, 2016 International Conference of the Biometrics Special Interest Group (BIOSIG), pp.1-6, 2016. ,
DOI : 10.1109/BIOSIG.2016.7736925
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data is Continuous and Weakly Labelled, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3793-3802, 2016. ,
DOI : 10.1109/CVPR.2016.412
, Caffe: Convolutional architecture for fast feature embedding, 805 arXiv preprint
Backpropagation through time: what it does and how to do it, Proceedings of the IEEE, vol.78, issue.10, pp.1550-1560, 1990. ,
DOI : 10.1109/5.58337
Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification, IEEE Transactions on Cybernetics ,
DOI : 10.1109/TCYB.2017.2662199
Adam: A method for stochastic optimization ,