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Fast and reliable algorithms for estimating the head pose are essential for many applications and higher-level face analysis tasks. We address the problem of head pose estimation from depth data, which can be captured using the ever more affordable 3D sensing technologies available today. To achieve robustness, we formulate pose estimation as a regression problem. While detecting specific face parts like the nose is sensitive to occlusions, learning the regression on rather generic surfacedoi:10.1109/cvpr.2011.5995458 dblp:conf/cvpr/FanelliGG11 fatcat:b7wmz435tnbczlhflxcstj4c6q