Human Pose Estimation with Fields of Parts

This paper proposes a new formulation of the human pose estimation problem. We present the Fields of Parts model, a binary Conditional Random Field model designed to detect human body parts of articulated people in single images.

[1]  Vittorio Ferrari,et al.  Better Appearance Models for Pictorial Structures , 2009, BMVC.

[2]  Toby Sharp,et al.  Real-time human pose recognition in parts from single depth images , 2011, CVPR.

[3]  Vittorio Ferrari,et al.  Appearance Sharing for Collective Human Pose Estimation , 2012, ACCV.

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

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

[6]  Justin Domke,et al.  Parameter learning with truncated message-passing , 2011, CVPR 2011.

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

[8]  Justin Domke,et al.  Learning Graphical Model Parameters with Approximate Marginal Inference , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Cordelia Schmid,et al.  Towards Understanding Action Recognition , 2013, 2013 IEEE International Conference on Computer Vision.

[10]  Silvio Savarese,et al.  An efficient branch-and-bound algorithm for optimal human pose estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Andrew Adams,et al.  Fast High‐Dimensional Filtering Using the Permutohedral Lattice , 2010, Comput. Graph. Forum.

[12]  Peter V. Gehler,et al.  Strong Appearance and Expressive Spatial Models for Human Pose Estimation , 2013, 2013 IEEE International Conference on Computer Vision.

[13]  Pushmeet Kohli,et al.  PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts , 2006, ECCV.

[14]  Antti Oulasvirta,et al.  Computer Vision – ECCV 2006 , 2006, Lecture Notes in Computer Science.

[15]  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).

[16]  Vladlen Koltun,et al.  Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials , 2011, NIPS.

[17]  Jonathan Tompson,et al.  Learning Human Pose Estimation Features with Convolutional Networks , 2013, ICLR.

[18]  Luc Van Gool,et al.  Human Pose Estimation Using Body Parts Dependent Joint Regressors , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[19]  Sebastian Nowozin,et al.  Decision tree fields , 2011, 2011 International Conference on Computer Vision.

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

[21]  Ben Taskar,et al.  Adaptive pose priors for pictorial structures , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[22]  Mark Everingham,et al.  Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation , 2010, BMVC.

[23]  Vibhav Vineet,et al.  PoseField: An Efficient Mean-Field Based Method for Joint Estimation of Human Pose, Segmentation, and Depth , 2013, EMMCVPR.

[24]  Andrew Zisserman,et al.  Human Pose Estimation Using a Joint Pixel-wise and Part-wise Formulation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Peter V. Gehler,et al.  Poselet Conditioned Pictorial Structures , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

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

[27]  Ben Taskar,et al.  Parsing human motion with stretchable models , 2011, CVPR 2011.

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

[29]  Yi Yang,et al.  Articulated Human Detection with Flexible Mixtures of Parts , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  Daphne Koller,et al.  Multi-level inference by relaxed dual decomposition for human pose segmentation , 2011, CVPR 2011.

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

[32]  Thomas Hofmann,et al.  Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..

[33]  Vladlen Koltun,et al.  Parameter Learning and Convergent Inference for Dense Random Fields , 2013, ICML.

[34]  Nir Friedman,et al.  Probabilistic Graphical Models - Principles and Techniques , 2009 .

[35]  Thomas Deselaers,et al.  ClassCut for Unsupervised Class Segmentation , 2010, ECCV.

[36]  Jitendra Malik,et al.  Articulated Pose Estimation Using Discriminative Armlet Classifiers , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[37]  Matthew D. Zeiler.  ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.