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We present a method for estimating articulated human pose from a single static image based on a graphical model with novel pairwise relations that make adaptive use of local image measurements.
The representation and matching of pictorial structures
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Support vector machine learning for interdependent and structured output spaces
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Histograms of oriented gradients for human detection
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P. F. Felzenszwalb and D. P. Huttenlocher · 2005
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Learning to parse images of articulated bodies
D. Ramanan · 2006
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Progressive search space reduction for human pose estimation
V. Ferrari, M. Marin-Jimenez, and A. Zisserman · 2008
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Clustered pose and nonlinear appearance models for human pose estimation
S. Johnson and M. Everingham · 2010
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Adaptive pose priors for pictorial structures
B. Sapp, C. Jordan, and B. Taskar · 2010
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Cascaded models for articulated pose estimation
B. Sapp, A. Toshev, and B. Taskar · 2010
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M. Eichner and V. Ferrari · 2012
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2d articulated human pose estimation and retrieval in (almost) unconstrained still images
M. Eichner, M. Marin-Jimenez, A. Zisserman, and V. Ferrari · 2012
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L. Karlinsky and S. Ullman · 2012
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Poselet conditioned pictorial structures
L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele · 2013
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Strong appearance and expressive spatial models for human pose estimation
L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele · 2013
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Modec: Multimodal decomposable models for human pose estimation
B. Sapp and B. Taskar · 2013
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An approach to pose-based action recognition
C. Wang, Y. Wang, and A. L. Yuille · 2013
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Articulated human detection with flexible mixtures of parts
Y. Yang and D. Ramanan · 2013
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Detect what you can: Detecting and representing objects using holistic models and body parts
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