Sequence of the Most Informative Joints (SMIJ): A new representation for human skeletal action recognition
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Ruzena Bajcsy | René Vidal | Gregorij Kurillo | Ferda Ofli | Rizwan Chaudhry | R. Vidal | R. Bajcsy | Rizwan Ahmed Chaudhry | G. Kurillo | Ferda Ofli
[1] Jessica K. Hodgins,et al. Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Ruzena Bajcsy,et al. Berkeley MHAD: A comprehensive Multimodal Human Action Database , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).
[3] René Vidal,et al. Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynamic scenes , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Luc Van Gool,et al. Metric Learning from Poses for Temporal Clustering of Human Motion , 2012, BMVC.
[5] Alexei A. Efros,et al. Unbiased look at dataset bias , 2011, CVPR 2011.
[6] 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.
[7] Hans-Peter Seidel,et al. Efficient and Robust Annotation of Motion Capture Data , 2009 .
[8] R. Vidal,et al. Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[9] Geoffrey E. Hinton,et al. Factored conditional restricted Boltzmann Machines for modeling motion style , 2009, ICML '09.
[10] Rama Chellappa,et al. Machine Recognition of Human Activities: A Survey , 2008, IEEE Transactions on Circuits and Systems for Video Technology.
[11] Philippe Beaudoin,et al. Motion-motif graphs , 2008, SCA '08.
[12] Cordelia Schmid,et al. Learning realistic human actions from movies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Mubarak Shah,et al. Chaotic Invariants for Human Action Recognition , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[14] Stefano Soatto,et al. Classification and Recognition of Dynamical Models: The Role of Phase, Independent Components, Kernels and Optimal Transport , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Stefano Soatto,et al. Applications of hybrid system identification in computer vision , 2007, 2007 European Control Conference (ECC).
[16] Tido Röder,et al. Documentation Mocap Database HDM05 , 2007 .
[17] René Vidal,et al. A System Theoretic Approach to Synthesis and Classification of Lip Articulation , 2007 .
[18] Alexander J. Smola,et al. Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes , 2007, International Journal of Computer Vision.
[19] Geoffrey E. Hinton,et al. Modeling Human Motion Using Binary Latent Variables , 2006, NIPS.
[20] Adrian Hilton,et al. A survey of advances in vision-based human motion capture and analysis , 2006, Comput. Vis. Image Underst..
[21] Cordelia Schmid,et al. Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).
[22] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[23] Serge J. Belongie,et al. Behavior recognition via sparse spatio-temporal features , 2005, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance.
[24] Nuno Vasconcelos,et al. Probabilistic kernels for the classification of auto-regressive visual processes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[25] Jernej Barbic,et al. Segmenting Motion Capture Data into Distinct Behaviors , 2004, Graphics Interface.
[26] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.
[27] Ivan Laptev,et al. On Space-Time Interest Points , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[28] Bart De Moor,et al. Subspace angles between ARMA models , 2002, Syst. Control. Lett..
[29] Y. Wu,et al. Dynamic Textures , 2003, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[30] Stefano Soatto,et al. Recognition of human gaits , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[31] Thomas B. Moeslund,et al. A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..
[32] B. Moor,et al. Subspace angles and distances between ARMA models , 2000 .
[33] Jake K. Aggarwal,et al. Human motion analysis: a review , 1997, Proceedings IEEE Nonrigid and Articulated Motion Workshop.
[34] Bart De Moor,et al. N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..
[35] Enrique Vidal,et al. Computation of Normalized Edit Distance and Applications , 1993, IEEE Trans. Pattern Anal. Mach. Intell..
[36] Junji Yamato,et al. Recognizing human action in time-sequential images using hidden Markov model , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[37] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[38] R. Shumway,et al. AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM , 1982 .
[39] Robert A. Wagner,et al. An Extension of the String-to-String Correction Problem , 1975, JACM.
[40] Michael J. Fischer,et al. The String-to-String Correction Problem , 1974, JACM.
[41] Vladimir I. Levenshtein,et al. Binary codes capable of correcting deletions, insertions, and reversals , 1965 .
[42] Fred J. Damerau,et al. A technique for computer detection and correction of spelling errors , 1964, CACM.