Human activity recognition from 3D data: A review, Pattern Recognition Letters, vol.48, pp.70-80, 2014. ,
DOI : 10.1016/j.patrec.2014.04.011
Human activity analysis, ACM Computing Surveys, vol.43, issue.3 ,
DOI : 10.1145/1922649.1922653
, ACM Computing Surveys (CSUR), vol.43, issue.3, p.16, 2011.
Action Recognition Using Rate-Invariant Analysis of Skeletal Shape Trajectories, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38, issue.1, pp.1-13, 2016. ,
DOI : 10.1109/TPAMI.2015.2439257
Human activity recognition using multidimensional indexing, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.8, pp.1091-1104, 2002. ,
DOI : 10.1109/TPAMI.2002.1023805
The recognition of human movement using temporal templates, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.3, pp.257-267, 2001. ,
DOI : 10.1109/34.910878
Realtime multi-person 2d pose estimation using part affinity fields. arXiv preprint, 2016. ,
Evolutionary joint selection to improve human action recognition with RGB-D devices, Expert Systems with Applications, vol.41, issue.3, pp.786-794, 2014. ,
DOI : 10.1016/j.eswa.2013.08.009
LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, p.27, 2011. ,
DOI : 10.1145/1961189.1961199
UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor, 2015 IEEE International Conference on Image Processing (ICIP), pp.168-172 ,
DOI : 10.1109/ICIP.2015.7350781
A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion, IEEE Sensors Journal, vol.16, issue.3, pp.773-781, 2016. ,
DOI : 10.1109/JSEN.2015.2487358
Skeleton-based action recognition with extreme learning machines, Neurocomputing, vol.149, pp.387-396, 2015. ,
DOI : 10.1016/j.neucom.2013.10.046
P-cnn: Pose-based cnn features for action recognition, Proceedings of the IEEE International Conference on Computer Vision, pp.3218-3226 ,
Monitoring Activities of Daily Living in Smart Homes: Understanding human behavior, IEEE Signal Processing Magazine, vol.33, issue.2, pp.81-94, 2016. ,
DOI : 10.1109/MSP.2015.2503881
Hierarchical recurrent neural network for skeleton based action recognition, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.1110-1118 ,
Recognizing action at a distance, Proceedings Ninth IEEE International Conference on Computer Vision, pp.726-733 ,
DOI : 10.1109/ICCV.2003.1238420
URL : http://lear.inrialpes.fr/people/triggs/events/iccv03/cdrom/iccv03/0726_efros.pdf
Efficient Pose-Based Action Recognition, Asian Conference on Computer and Applications, pp.3479-3494, 2016. ,
DOI : 10.1007/978-3-319-16814-2_28
URL : http://www.iai.uni-bonn.de/%7Egall/download/jgall_action2d3d_accv14.pdf
Group Sparsity and Geometry Constrained Dictionary Learning for Action Recognition from Depth Maps, 2013 IEEE International Conference on Computer Vision, pp.1809-1816 ,
DOI : 10.1109/ICCV.2013.227
URL : http://web.eecs.utk.edu/%7Ejluo9/DL-GSGC.pdf
Learning features combination for human action recognition from skeleton sequences, Pattern Recognition Letters, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01515376
Human action recognition using extreme learning machine based on visual vocabularies, Neurocomputing, vol.73, issue.10-12, pp.1906-1917, 2010. ,
DOI : 10.1016/j.neucom.2010.01.020
An rdf-based action recognition framework with feature selection capability, considering therapy exercises utilizing depth cameras, Journal of Theoretical and Applied Computer Science, vol.8, issue.3, pp.3-22, 2014. ,
DOI : 10.1007/978-3-642-39094-4_74
A decision forest based feature selection framework for action recognition from rgb-depth cameras, International Conference Image Analysis and Recognition, pp.648-657 ,
DOI : 10.1007/978-3-642-39094-4_74
A human activity recognition framework using max-min features and key poses with differential evolution random forests classifier, Pattern Recognition Letters, vol.99, 2017. ,
DOI : 10.1016/j.patrec.2017.05.004
URL : http://publications.aston.ac.uk/30712/1/Max_min_features_and_key_poses_with_differential_evolution_random_forests_classifier.pdf
Self-organizing neural integration of pose-motion features for human action recognition, Frontiers in Neurorobotics, vol.32, issue.6, 2015. ,
DOI : 10.1016/j.imavis.2014.04.005
URL : http://journal.frontiersin.org/article/10.3389/fnbot.2015.00003/pdf
Bag of visual words and fusion methods for action recognition: Comprehensive study and good practice, Computer Vision and Image Understanding, vol.150, pp.109-125, 2016. ,
DOI : 10.1016/j.cviu.2016.03.013
URL : http://arxiv.org/pdf/1405.4506
A survey on vision-based human action recognition, Image and Vision Computing, vol.28, issue.6, pp.976-990, 2010. ,
DOI : 10.1016/j.imavis.2009.11.014
3D skeleton-based human action classification: A survey, Pattern Recognition, vol.53, pp.130-147, 2016. ,
DOI : 10.1016/j.patcog.2015.11.019
Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition, Pattern Recognition, vol.66, 2017. ,
DOI : 10.1016/j.patcog.2017.01.015
URL : http://arxiv.org/pdf/1504.04923
Human Action Recognition With Video Data: Research and Evaluation Challenges, IEEE Transactions on Human-Machine Systems, vol.44, issue.5, pp.650-663, 2014. ,
DOI : 10.1109/THMS.2014.2325871
Action bank: A high-level representation of activity in video, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.1234-1241 ,
DOI : 10.1109/CVPR.2012.6247806
URL : http://www.cse.buffalo.edu/%7Ejcorso/pubs/jcorso_CVPR2012_actionbank.pdf
A 3-dimensional sift descriptor and its application to action recognition, Proceedings of the 15th international conference on Multimedia , MULTIMEDIA '07, pp.357-360 ,
DOI : 10.1145/1291233.1291311
, ACM
Human action recognition using Dynamic Time Warping, Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, pp.1-5 ,
DOI : 10.1109/ICEEI.2011.6021605
, IEEE
3D human action segmentation and recognition using pose kinetic energy, 2014 IEEE International Workshop on Advanced Robotics and its Social Impacts, pp.69-75, 2014. ,
DOI : 10.1109/ARSO.2014.7020983
Real-time human pose recognition in parts from single depth images, Communications of the ACM, vol.56, issue.1, pp.116-124, 2013. ,
DOI : 10.1145/2398356.2398381
Unstructured human activity detection from rgbd images, Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp.842-849 ,
Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), pp.61-69 ,
DOI : 10.1109/ICCVW.2015.48
EXMOVES: Mid-level Features for Efficient Action Recognition and Video Analysis, International Journal of Computer Vision, vol.64, issue.2???3, p.26 ,
DOI : 10.1007/978-3-642-33712-3_50
,
, Computer Vision, vol.119, issue.3, pp.239-253, 2016.
Efficient large-scale action recognition in videos using extreme learning machines, Expert Systems with Applications, vol.42, issue.21, pp.8274-8282, 2015. ,
DOI : 10.1016/j.eswa.2015.06.013
Differential Recurrent Neural Networks for Action Recognition, 2015 IEEE International Conference on Computer Vision (ICCV), pp.4041-4049 ,
DOI : 10.1109/ICCV.2015.460
Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.588-595 ,
DOI : 10.1109/CVPR.2014.82
R3DG features: Relative 3D geometry-based skeletal representations for human action recognition, Computer Vision and Image Understanding, vol.152, pp.155-166, 2016. ,
DOI : 10.1016/j.cviu.2016.04.005
A survey on activity recognition and behavior understanding in video surveillance, The Visual Computer, vol.114, issue.12, pp.983-1009, 2013. ,
DOI : 10.1016/j.cviu.2009.11.005
An Approach to Pose-Based Action Recognition, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.915-922 ,
DOI : 10.1109/CVPR.2013.123
Mining 3D Key-Pose-Motifs for Action Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2639-2647 ,
DOI : 10.1109/CVPR.2016.289
Action recognition by dense trajectories, CVPR 2011, pp.3169-3176 ,
DOI : 10.1109/CVPR.2011.5995407
URL : https://hal.archives-ouvertes.fr/inria-00583818
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-00725627
Learning actionlet ensemble for 3D human action recognition, pp.11-40, 2014. ,
Mining actionlet ensemble for action recognition with depth cameras, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.1290-1297 ,
DOI : 10.1109/CVPR.2012.6247813
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks, Proceedings of the 2016 ACM on Multimedia Conference, MM '16, pp.102-106 ,
DOI : 10.1109/DICTA.2014.7008101
, ACM
View invariant human action recognition using histograms of 3D joints, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.20-27 ,
DOI : 10.1109/CVPRW.2012.6239233
Recognizing actions using depth motion maps-based histograms of oriented gradients, Proceedings of the 20th ACM international conference on Multimedia, MM '12, pp.1057-1060 ,
DOI : 10.1145/2393347.2396382
Latent Max-Margin Multitask Learning With Skelets for 3-D Action Recognition, IEEE Transactions on Cybernetics, vol.47, issue.2, pp.439-448, 2017. ,
DOI : 10.1109/TCYB.2016.2519448
Does Human Action Recognition Benefit from Pose Estimation?, Procedings of the British Machine Vision Conference 2011 ,
DOI : 10.5244/C.25.67
Spatiotemporal representation of 3d skeleton jointsbased action recognition using modified spherical harmonics, Pattern Recognition Letters, vol.83, pp.32-41, 2016. ,
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 ,
DOI : 10.1109/ICCV.2013.342
Event-based analysis of video, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, p.II?II, 2001. ,
DOI : 10.1109/CVPR.2001.990935
RGB-D-based action recognition datasets: A survey, Pattern Recognition, vol.60, pp.86-105, 2016. ,
DOI : 10.1016/j.patcog.2016.05.019
, Improving Bag-of-poses with Semi-temporal Pose Descriptors for Skeleton-based Action Recognition 27
On geometric features for skeletonbased action recognition using multilayer lstm networks, Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on, pp.148-157 ,
From handcrafted to learned representations for human action recognition: A??survey, Image and Vision Computing, vol.55, pp.42-52, 2016. ,
DOI : 10.1016/j.imavis.2016.06.007
Human action recognition using multi-layer codebooks of key poses and atomic motions, Signal Processing: Image Communication, vol.42, pp.19-30, 2016. ,
DOI : 10.1016/j.image.2016.01.003
Co-occurrence feature learning for skeleton based action recognition using regularized deep lstm networks, 2016. ,
Fusing multiple features for depthbased action recognition, ACM Transactions on Intelligent Systems and Technology (TIST), vol.6, issue.2, p.18, 2015. ,