3D skeleton-based human action classification: A survey

[1]  Bharti Bansal,et al.  Gesture Recognition: A Survey , 2016 .

[2]  Marco La Cascia,et al.  Hankelet-based dynamical systems modeling for 3D action recognition , 2015, Image Vis. Comput..

[3]  Robert Bergevin,et al.  Semantic human activity recognition: A literature review , 2015, Pattern Recognit..

[4]  Youfu Li,et al.  Integral invariants for space motion trajectory matching and recognition , 2015, Pattern Recognit..

[5]  Alberto Del Bimbo,et al.  Submitted to Ieee Transactions on Cybernetics 1 3d Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold , 2022 .

[6]  Stephen J. Maybank,et al.  Action classification using a discriminative multilevel HDP-HMM , 2015, Neurocomputing.

[7]  Anuj Srivastava,et al.  Accurate 3D action recognition using learning on the Grassmann manifold , 2015, Pattern Recognit..

[8]  Nasser Kehtarnavaz,et al.  Improving Human Action Recognition Using Fusion of Depth Camera and Inertial Sensors , 2015, IEEE Transactions on Human-Machine Systems.

[9]  Ekta Vats,et al.  Fuzzy human motion analysis: A review , 2014, Pattern Recognit..

[10]  Chalavadi Krishna Mohan,et al.  Human Action Recognition Based on MOCAP Information Using Convolution Neural Networks , 2014, 2014 13th International Conference on Machine Learning and Applications.

[11]  Ling Shao,et al.  Realistic action recognition via sparsely-constructed Gaussian processes , 2014, Pattern Recognit..

[12]  Koichi Shinoda,et al.  Spectral Graph Skeletons for 3D Action Recognition , 2014, ACCV.

[13]  Christian Bauckhage,et al.  Efficient Pose-Based Action Recognition , 2014, ACCV.

[14]  Marco La Cascia,et al.  Gesture Modeling by Hanklet-Based Hidden Markov Model , 2014, ACCV.

[15]  Jake K. Aggarwal,et al.  Human activity recognition from 3D data: A review , 2014, Pattern Recognit. Lett..

[16]  Guodong Guo,et al.  A survey on still image based human action recognition , 2014, Pattern Recognit..

[17]  James M. Rehg,et al.  Movement Pattern Histogram for Action Recognition and Retrieval , 2014, ECCV.

[18]  Georgios Evangelidis,et al.  Skeletal Quads: Human Action Recognition Using Joint Quadruples , 2014, 2014 22nd International Conference on Pattern Recognition.

[19]  Arif Mahmood,et al.  HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition , 2014, ECCV.

[20]  Alexandros André Chaaraoui,et al.  A discussion on the validation tests employed to compare human action recognition methods using the MSR Action3D dataset , 2014, ArXiv.

[21]  Gérard G. Medioni,et al.  Structured Time Series Analysis for Human Action Segmentation and Recognition , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Cristian Sminchisescu,et al.  Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Juan Carlos Niebles,et al.  Discriminative Hierarchical Modeling of Spatio-temporally Composable Human Activities , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[24]  Ling Shao,et al.  Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Sebastian Nowozin,et al.  Efficient Nonlinear Markov Models for Human Motion , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[26]  Rama Chellappa,et al.  Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Mohammad H. Mahoor,et al.  Human activity recognition using multi-features and multiple kernel learning , 2014, Pattern Recognit..

[28]  Hyung Jin Chang,et al.  Robust action recognition using local motion and group sparsity , 2014, Pattern Recognit..

[29]  Mario Fernando Montenegro Campos,et al.  Online gesture recognition from pose kernel learning and decision forests , 2014, Pattern Recognit. Lett..

[30]  Nasser Kehtarnavaz,et al.  Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition , 2014, IEEE Sensors Journal.

[31]  Mathieu Barnachon,et al.  Ongoing human action recognition with motion capture , 2014, Pattern Recognit..

[32]  Leonid Sigal.  Human Pose Estimation , 2014, Computer Vision, A Reference Guide.

[33]  Alexandros André Chaaraoui,et al.  Fusion of Skeletal and Silhouette-Based Features for Human Action Recognition with RGB-D Devices , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[34]  Agata Rozga,et al.  Joint Alignment and Modeling of Correlated Behavior Streams , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[35]  Cristian Sminchisescu,et al.  The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection , 2013, 2013 IEEE International Conference on Computer Vision.

[36]  Nanning Zheng,et al.  Concurrent Action Detection with Structural Prediction , 2013, 2013 IEEE International Conference on Computer Vision.

[37]  Ying Wu,et al.  Learning Maximum Margin Temporal Warping for Action Recognition , 2013, 2013 IEEE International Conference on Computer Vision.

[38]  Hong Wei,et al.  A survey of human motion analysis using depth imagery , 2013, Pattern Recognit. Lett..

[39]  Cordelia Schmid,et al.  Temporal Localization of Actions with Actoms. , 2013, IEEE transactions on pattern analysis and machine intelligence.

[40]  Alberto Del Bimbo,et al.  Space-Time Pose Representation for 3D Human Action Recognition , 2013, ICIAP Workshops.

[41]  Marwan Torki,et al.  Human Action Recognition Using a Temporal Hierarchy of Covariance Descriptors on 3D Joint Locations , 2013, IJCAI.

[42]  Qingmin Liao,et al.  Part template: 3D representation for multiview human pose estimation , 2013, Pattern Recognit..

[43]  Wen Gao,et al.  Learning discriminative features for fast frame-based action recognition , 2013, Pattern Recognit..

[44]  Alan L. Yuille,et al.  An Approach to Pose-Based Action Recognition , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[45]  Ruzena Bajcsy,et al.  Bio-inspired Dynamic 3D Discriminative Skeletal Features for Human Action Recognition , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[46]  Alberto Del Bimbo,et al.  Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[47]  Guodong Guo,et al.  Fusing Spatiotemporal Features and Joints for 3D Action Recognition , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[48]  Jake K. Aggarwal,et al.  Spatio-temporal Depth Cuboid Similarity Feature for Activity Recognition Using Depth Camera , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[49]  Mohan M. Trivedi,et al.  Joint Angles Similarities and HOG2 for Action Recognition , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[50]  James M. Rehg,et al.  Decoding Children's Social Behavior , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[51]  Zicheng Liu,et al.  HON4D: Histogram of Oriented 4D Normals for Activity Recognition from Depth Sequences , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[52]  Richard Bowden,et al.  Hollywood 3D: Recognizing Actions in 3D Natural Scenes , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[53]  Andrés Pérez-Uribe,et al.  Indoor Activity Recognition by Combining One-vs.-All Neural Network Classifiers Exploiting Wearable and Depth Sensors , 2013, IWANN.

[54]  Ruzena Bajcsy,et al.  Berkeley MHAD: A comprehensive Multimodal Human Action Database , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

[55]  Ashwin Thangali Varadaraju.  Exploiting phonological constraints for handshape recognition in sign language video , 2013 .

[56]  Cordelia Schmid,et al.  Dense Trajectories and Motion Boundary Descriptors for Action Recognition , 2013, International Journal of Computer Vision.

[57]  Joseph J. LaViola,et al.  Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition , 2013, International Journal of Computer Vision.

[58]  Mubarak Shah,et al.  UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild , 2012, ArXiv.

[59]  Mubarak Shah,et al.  Recognizing 50 human action categories of web videos , 2012, Machine Vision and Applications.

[60]  Alexandros André Chaaraoui,et al.  Optimal Joint Selection for Skeletal Data from RGB-D Devices Using a Genetic Algorithm , 2012, MICAI.

[61]  Ying Wu,et al.  Robust 3D Action Recognition with Random Occupancy Patterns , 2012, ECCV.

[62]  Mario Fernando Montenegro Campos,et al.  STOP: Space-Time Occupancy Patterns for 3D Action Recognition from Depth Map Sequences , 2012, CIARP.

[63]  Ioannis A. Kakadiaris,et al.  Part-based motion descriptor image for human action recognition , 2012, Pattern Recognit..

[64]  Binlong Li,et al.  Cross-view activity recognition using Hankelets , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[65]  Jake K. Aggarwal,et al.  View invariant human action recognition using histograms of 3D joints , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[66]  Ying Wu,et al.  Mining actionlet ensemble for action recognition with depth cameras , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[67]  Kristen Grauman,et al.  Efficient activity detection with max-subgraph search , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[68]  Xiaodong Yang,et al.  EigenJoints-based action recognition using Naïve-Bayes-Nearest-Neighbor , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[69]  Jason J. Corso,et al.  Action bank: A high-level representation of activity in video , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[70]  Ruzena Bajcsy,et al.  Sequence of the Most Informative Joints (SMIJ): A new representation for human skeletal action recognition , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[71]  Helena M. Mentis,et al.  Instructing people for training gestural interactive systems , 2012, CHI.

[72]  Alessio Malizia,et al.  The artificiality of natural user interfaces , 2012, CACM.

[73]  Bart Selman,et al.  Unstructured human activity detection from RGBD images , 2011, 2012 IEEE International Conference on Robotics and Automation.

[74]  Cristina Videira Lopes,et al.  Monitoring Intake Gestures using Sensor Fusion (Microsoft Kinect and Inertial Sensors) for Smart Hom , 2012 .

[75]  Amit K. Roy-Chowdhury,et al.  A “string of feature graphs” model for recognition of complex activities in natural videos , 2011, 2011 International Conference on Computer Vision.

[76]  Ruigang Yang,et al.  Accurate 3D pose estimation from a single depth image , 2011, 2011 International Conference on Computer Vision.

[77]  Yao-Jen Chang,et al.  A Kinect-based system for physical rehabilitation: a pilot study for young adults with motor disabilities. , 2011, Research in developmental disabilities.

[78]  Darko Kirovski,et al.  Real-time classification of dance gestures from skeleton animation , 2011, SCA '11.

[79]  Bart Selman,et al.  Human Activity Detection from RGBD Images , 2011, Plan, Activity, and Intent Recognition.

[80]  Andrew W. Fitzgibbon,et al.  Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.

[81]  Yi Yang,et al.  Articulated pose estimation with flexible mixtures-of-parts , 2011, CVPR 2011.

[82]  Binlong Li,et al.  Activity recognition using dynamic subspace angles , 2011, CVPR 2011.

[83]  Yang Wang,et al.  Learning hierarchical poselets for human parsing , 2011, CVPR 2011.

[84]  Stan Sclaroff,et al.  Exploiting phonological constraints for handshape inference in ASL video , 2011, CVPR 2011.

[85]  Bohyung Han,et al.  Scenario-based video event recognition by constraint flow , 2011, CVPR 2011.

[86]  Fernando De la Torre,et al.  Joint segmentation and classification of human actions in video , 2011, CVPR 2011.

[87]  Rémi Ronfard,et al.  A survey of vision-based methods for action representation, segmentation and recognition , 2011, Comput. Vis. Image Underst..

[88]  S. Foix,et al.  Lock-in Time-of-Flight (ToF) Cameras: A Survey , 2011, IEEE Sensors Journal.

[89]  Patrick Pérez,et al.  View-Independent Action Recognition from Temporal Self-Similarities , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[90]  Luc Van Gool,et al.  Does Human Action Recognition Benefit from Pose Estimation? , 2011, BMVC.

[91]  Ben Taskar,et al.  Cascaded Models for Articulated Pose Estimation , 2010, ECCV.

[92]  David A. Forsyth,et al.  Improved Human Parsing with a Full Relational Model , 2010, ECCV.

[93]  Wanqing Li,et al.  Action recognition based on a bag of 3D points , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

[94]  Stan Sclaroff,et al.  Fast globally optimal 2D human detection with loopy graph models , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[95]  Ronald Poppe,et al.  A survey on vision-based human action recognition , 2010, Image Vis. Comput..

[96]  Dieter Fox,et al.  RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments , 2010, ISER.

[97]  Pierre Vandergheynst,et al.  Wavelets on Graphs via Spectral Graph Theory , 2009, ArXiv.

[98]  Jitendra Malik,et al.  Poselets: Body part detectors trained using 3D human pose annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[99]  Andrew Gilbert,et al.  Fast realistic multi-action recognition using mined dense spatio-temporal features , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[100]  Andrew Zisserman,et al.  Efficient discriminative learning of parts-based models , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[101]  B. Schiele,et al.  Pictorial structures revisited: People detection and articulated pose estimation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[102]  Jiebo Luo,et al.  Recognizing realistic actions from videos “in the wild” , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[103]  Umberto Castellani,et al.  Multiple kernel learning , 2009 .

[104]  Cordelia Schmid,et al.  A Spatio-Temporal Descriptor Based on 3D-Gradients , 2008, BMVC.

[105]  Chris Hecker,et al.  Real-time motion retargeting to highly varied user-created morphologies , 2008, ACM Trans. Graph..

[106]  David A. McAllester,et al.  A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[107]  Andrew Zisserman,et al.  Progressive search space reduction for human pose estimation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[108]  Juan Carlos Niebles,et al.  Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words , 2008, International Journal of Computer Vision.

[109]  Pinar Duygulu Sahin,et al.  Human Action Recognition Using Distribution of Oriented Rectangular Patches , 2007, Workshop on Human Motion.

[110]  Richard Bowden,et al.  Large Lexicon Detection of Sign Language , 2007, ICCV-HCI.

[111]  David A. Forsyth,et al.  Searching Video for Complex Activities with Finite State Models , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[112]  Ramakant Nevatia,et al.  Single View Human Action Recognition using Key Pose Matching and Viterbi Path Searching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[113]  S. Mitra,et al.  Gesture Recognition: A Survey , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[114]  Deva Ramanan,et al.  Learning to parse images of articulated bodies , 2006, NIPS.

[115]  Bernt Schiele,et al.  Multiple Object Class Detection with a Generative Model , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[116]  Jitendra Malik,et al.  Recovering human body configurations using pairwise constraints between parts , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[117]  Bruno Arnaldi,et al.  Morphology‐independent representation of motions for interactive human‐like animation , 2005, Comput. Graph. Forum.

[118]  Meinard Müller,et al.  Efficient content-based retrieval of motion capture data , 2005, ACM Trans. Graph..

[119]  David A. Forsyth,et al.  Strike a pose: tracking people by finding stylized poses , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[120]  Pascal Fua,et al.  A parallel stereo algorithm that produces dense depth maps and preserves image features , 1993, Machine Vision and Applications.

[121]  Ronan Boulic,et al.  An inverse kinematics architecture enforcing an arbitrary number of strict priority levels , 2004, The Visual Computer.

[122]  Michael I. Jordan,et al.  Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.

[123]  Ignazio Infantino,et al.  A posture sequence learning system for an anthropomorphic robotic hand , 2004, Robotics Auton. Syst..

[124]  Mun Wai Lee,et al.  Proposal maps driven MCMC for estimating human body pose in static images , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[125]  Alexei A. Efros,et al.  Recovering human body configurations: combining segmentation and recognition , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[126]  Daniel P. Huttenlocher,et al.  Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.

[127]  Ignazio Infantino,et al.  Visual control of a robotic hand , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[128]  Sangho Park,et al.  Recognition of two-person interactions using a hierarchical Bayesian network , 2003, IWVS '03.

[129]  Ivan Laptev,et al.  On Space-Time Interest Points , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[130]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[131]  Richard Szeliski,et al.  High-accuracy stereo depth maps using structured light , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[132]  M. Barker,et al.  Partial least squares for discrimination , 2003 .

[133]  Christian D. Schunn,et al.  Integrating perceptual and cognitive modeling for adaptive and intelligent human-computer interaction , 2002, Proc. IEEE.

[134]  Vladimir Kolmogorov,et al.  Multi-camera Scene Reconstruction via Graph Cuts , 2002, ECCV.

[135]  D. Heckerman,et al.  Autoregressive Tree Models for Time-Series Analysis , 2002, SDM.

[136]  Roman Rosipal,et al.  Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space , 2002, J. Mach. Learn. Res..

[137]  D. Scharstein,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001).

[138]  Richard K. Beatson,et al.  Reconstruction and representation of 3D objects with radial basis functions , 2001, SIGGRAPH.

[139]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[140]  Michael Gleicher,et al.  Comparing Constraint-Based Motion Editing Methods , 2001, Graph. Model..

[141]  Thomas B. Moeslund,et al.  A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..

[142]  Don Ray Murray,et al.  Using Real-Time Stereo Vision for Mobile Robot Navigation , 2000, Auton. Robots.

[143]  Jinyan Li,et al.  Efficient mining of emerging patterns: discovering trends and differences , 1999, KDD '99.

[144]  David Haussler,et al.  Exploiting Generative Models in Discriminative Classifiers , 1998, NIPS.

[145]  Michael Gleicher,et al.  Retargetting motion to new characters , 1998, SIGGRAPH.

[146]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .

[147]  Alex Pentland,et al.  Coupled hidden Markov models for complex action recognition , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[148]  James W. Davis,et al.  GESTURE RECOGNITION , 2023, International Research Journal of Modernization in Engineering Technology and Science.

[149]  G. Johansson.  Visual perception of biological motion and a model for its analysis , 1973 .

[150]  J. Humphreys.  Introduction to Lie Algebras and Representation Theory , 1973 .

[151]  Martin A. Fischler,et al.  The Representation and Matching of Pictorial Structures , 1973, IEEE Transactions on Computers.