Efficient Human Pose Estimation from Single Depth Images
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Andrew Blake | Toby Sharp | Antonio Criminisi | Pushmeet Kohli | Ross B. Girshick | Jamie Shotton | Ross Girshick | Andrew Fitzgibbon | Mat Cook | Richard Moore | Mark Finocchio | Alex Kipman | Pushmeet Kohli | A. Fitzgibbon | J. Shotton | A. Criminisi | T. Sharp | A. Kipman | M. Finocchio | A. Blake | Mat Cook | R. Moore | Richard Moore
[1] Martin A. Fischler,et al. The Representation and Matching of Pictorial Structures , 1973, IEEE Transactions on Computers.
[2] B. A. Shepherd,et al. An Appraisal of a Decision Tree Approach to Image Classification , 1983, IJCAI.
[3] Teofilo F. GONZALEZ,et al. Clustering to Minimize the Maximum Intercluster Distance , 1985, Theor. Comput. Sci..
[4] Jeffrey Scott Vitter,et al. Random sampling with a reservoir , 1985, TOMS.
[5] Yali Amit,et al. Shape Quantization and Recognition with Randomized Trees , 1997, Neural Computation.
[6] Jitendra Malik,et al. Tracking people with twists and exponential maps , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).
[7] Dariu Gavrila,et al. Pedestrian Detection from a Moving Vehicle , 2000, ECCV.
[8] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[9] Michael J. Black,et al. Implicit Probabilistic Models of Human Motion for Synthesis and Tracking , 2002, ECCV.
[10] Jitendra Malik,et al. Estimating Human Body Configurations Using Shape Context Matching , 2002, ECCV.
[11] Trevor Darrell,et al. Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[12] Pietro Perona,et al. Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[13] David A. Forsyth,et al. Finding and tracking people from the bottom up , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[14] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[15] David A. Forsyth,et al. Probabilistic Methods for Finding People , 2001, International Journal of Computer Vision.
[16] Ankur Agarwal,et al. 3D human pose from silhouettes by relevance vector regression , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[17] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[18] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[19] Daniel P. Huttenlocher,et al. Pictorial Structures for Object Recognition , 2004, International Journal of Computer Vision.
[20] Sidharth Bhatia,et al. Tracking loose-limbed people , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[21] Ben Taskar,et al. Discriminative learning of Markov random fields for segmentation of 3D scan data , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[22] Vincent Lepetit,et al. Randomized trees for real-time keypoint recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[23] Reinhard Koch,et al. Nonlinear Body Pose Estimation from Depth Images , 2005, DAGM-Symposium.
[24] Frédéric Jurie,et al. Fast Discriminative Visual Codebooks using Randomized Clustering Forests , 2006, NIPS.
[25] Adrian Hilton,et al. A survey of advances in vision-based human motion capture and analysis , 2006, Comput. Vis. Image Underst..
[26] Rüdiger Dillmann,et al. Sensor fusion for 3D human body tracking with an articulated 3D body model , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[27] Jamie Shotton,et al. The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[28] Antonio Criminisi,et al. TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation , 2006, ECCV.
[29] Kikuo Fujimura,et al. Constrained Optimization for Human Pose Estimation from Depth Sequences , 2007, ACCV.
[30] Bernt Schiele,et al. Robust Object Detection with Interleaved Categorization and Segmentation , 2008, International Journal of Computer Vision.
[31] Andrew W. Fitzgibbon,et al. The Joint Manifold Model for Semi-supervised Multi-valued Regression , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[32] Cristian Sminchisescu,et al. Semi-supervised Hierarchical Models for 3D Human Pose Reconstruction , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[33] Ronald Poppe,et al. Vision-based human motion analysis: An overview , 2007, Comput. Vis. Image Underst..
[34] Philip H. S. Torr,et al. Randomized trees for human pose detection , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[35] Toby Sharp,et al. Implementing Decision Trees and Forests on a GPU , 2008, ECCV.
[36] Zhuowen Tu,et al. Auto-context and its application to high-level vision tasks , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Stefano Soatto,et al. Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images , 2008, ECCV.
[38] Roberto Cipolla,et al. Semantic texton forests for image categorization and segmentation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[39] Trevor Darrell,et al. Sparse probabilistic regression for activity-independent human pose inference , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[40] Yihong Gong,et al. Discriminative learning of visual words for 3D human pose estimation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[41] Juergen Gall,et al. Class-specific Hough forests for object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Jitendra Malik,et al. Poselets: Body part detectors trained using 3D human pose annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[43] Robert Y. Wang,et al. Real-time hand-tracking with a color glove , 2009, ACM Trans. Graph..
[44] David J. Fleet,et al. Physics-Based Person Tracking Using the Anthropomorphic Walker , 2010, International Journal of Computer Vision.
[45] Aaron Hertzmann,et al. Learning 3D mesh segmentation and labeling , 2010, ACM Trans. Graph..
[46] Michael Arens,et al. Human pose estimation with implicit shape models , 2010, ARTEMIS '10.
[47] Sebastian Thrun,et al. Real-time identification and localization of body parts from depth images , 2010, 2010 IEEE International Conference on Robotics and Automation.
[48] Antonio Criminisi,et al. Regression Forests for Efficient Anatomy Detection and Localization in CT Studies , 2010, MCV.
[49] Sebastian Thrun,et al. Real time motion capture using a single time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[50] Gérard G. Medioni,et al. Human pose estimation from a single view point, real-time range sensor , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[51] Jitendra Malik,et al. Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.
[52] Dimitris N. Metaxas,et al. Entangled Decision Forests and Their Application for Semantic Segmentation of CT Images , 2011, IPMI.
[53] Andrew W. Fitzgibbon,et al. Efficient regression of general-activity human poses from depth images , 2011, 2011 International Conference on Computer Vision.
[54] Toby Sharp,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR.
[55] Sebastian Nowozin,et al. Improved Information Gain Estimates for Decision Tree Induction , 2012, ICML.
[56] Antonio Criminisi,et al. Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning , 2012, Found. Trends Comput. Graph. Vis..