Bayesian Image Based 3D Pose Estimation
暂无分享,去创建一个
[1] Albert Y. Lo,et al. On a Class of Bayesian Nonparametric Estimates: I. Density Estimates , 1984 .
[2] Raveendran Paramesran,et al. Single camera 3D human pose estimation: A Review of current techniques , 2009, 2009 International Conference for Technical Postgraduates (TECHPOS).
[3] Ronald Poppe,et al. Vision-based human motion analysis: An overview , 2007, Comput. Vis. Image Underst..
[4] Wen Gao,et al. Robust Estimation of 3D Human Poses from a Single Image , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[5] Michael J. Black,et al. Pose-conditioned joint angle limits for 3D human pose reconstruction , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Yi Yang,et al. Articulated Human Detection with Flexible Mixtures of Parts , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] John W. Fisher,et al. Parallel Sampling of DP Mixture Models using Sub-Cluster Splits , 2013, NIPS.
[8] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[9] Xiaowei Zhou,et al. Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Vijay Kumar,et al. On the generation of smooth three-dimensional rigid body motions , 1998, IEEE Trans. Robotics Autom..
[11] Fiora Pirri,et al. Bayesian Non-parametric Inference for Manifold Based MoCap Representation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[12] John W. Fisher,et al. A Dirichlet Process Mixture Model for Spherical Data , 2015, AISTATS.
[13] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[14] Francesc Moreno-Noguer,et al. Single image 3D human pose estimation from noisy observations , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Bodo Rosenhahn,et al. Posebits for Monocular Human Pose Estimation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[16] Sebastian Nowozin,et al. A Non-parametric Bayesian Network Prior of Human Pose , 2013, 2013 IEEE International Conference on Computer Vision.
[17] Vincent Lepetit,et al. Predicting People's 3D Poses from Short Sequences , 2015, ArXiv.
[18] Jitendra Malik,et al. Recovering 3D human body configurations using shape contexts , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Jia Xu,et al. Manifold-valued Dirichlet Processes , 2015, ICML.
[20] Dilan Görür,et al. Nonparametric Bayesian discrete latent variable models for unsupervised learning , 2007 .
[21] Radford M. Neal,et al. A Split-Merge Markov chain Monte Carlo Procedure for the Dirichlet Process Mixture Model , 2004 .
[22] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[23] Bernt Schiele,et al. Monocular 3D pose estimation and tracking by detection , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[24] Xiaogang Wang,et al. Multi-source Deep Learning for Human Pose Estimation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[25] Jitendra Malik,et al. Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.
[26] Antoni B. Chan,et al. 3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network , 2014, ACCV.
[27] Radford M. Neal. Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .
[28] Fernando De la Torre,et al. Spatio-temporal Matching for Human Detection in Video , 2014, ECCV.
[29] Erik B. Sudderth. Graphical models for visual object recognition and tracking , 2006 .
[30] Michael J. Black,et al. Predicting 3D People from 2D Pictures , 2006, AMDO.
[31] Chun Chen,et al. A survey of human pose estimation: The body parts parsing based methods , 2015, J. Vis. Commun. Image Represent..
[32] P. Thomas Fletcher,et al. Principal geodesic analysis for the study of nonlinear statistics of shape , 2004, IEEE Transactions on Medical Imaging.
[33] Jonathan Tompson,et al. Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation , 2014, NIPS.
[34] Juergen Gall,et al. 3D Pose Estimation from a Single Monocular Image , 2015, ArXiv.
[35] Camillo J. Taylor,et al. Reconstruction of articulated objects from point correspondences in a single uncalibrated image , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[36] Xiaomin Duan,et al. Riemannian Means on Special Euclidean Group and Unipotent Matrices Group , 2013, TheScientificWorldJournal.
[37] Camilo Romero Núñez,et al. Prevalence and risk factors associated with Toxocara canis infection in children. , 2013 .
[38] Andrew W. Fitzgibbon,et al. The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[39] Ankur Agarwal,et al. Recovering 3D human pose from monocular images , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[40] Michael I. Jordan,et al. Hierarchical Dirichlet Processes , 2006 .
[41] Ryan P. Adams,et al. ClusterCluster: Parallel Markov Chain Monte Carlo for Dirichlet Process Mixtures , 2013, ArXiv.
[42] 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.
[43] Andrew Zisserman,et al. Representing shape with a spatial pyramid kernel , 2007, CIVR '07.
[44] Christian Szegedy,et al. DeepPose: Human Pose Estimation via Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[45] H. Karcher. Riemannian center of mass and mollifier smoothing , 1977 .
[46] T. Ferguson. BAYESIAN DENSITY ESTIMATION BY MIXTURES OF NORMAL DISTRIBUTIONS , 1983 .
[47] W. Kendall. Probability, Convexity, and Harmonic Maps with Small Image I: Uniqueness and Fine Existence , 1990 .
[48] René Vidal,et al. On the Convergence of Gradient Descent for Finding the Riemannian Center of Mass , 2011, SIAM J. Control. Optim..