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Recovering 3D human pose from monocular images
2006
IEEE Transactions on Pattern Analysis and Machine Intelligence
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor prior labelling of body parts in the image. Instead, it recovers pose by direct nonlinear regression against shape descriptor vectors extracted automatically from image silhouettes. For robustness against local silhouette segmentation errors, silhouette shape is encoded by histogram-of-shape-contexts descriptors. We
doi:10.1109/tpami.2006.21
pmid:16402618
fatcat:wvxmdenp45a77n3ldze74dkdcu