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We consider the problem of computing accurate point-to-point correspondences among a set of human bodies in similar posture using a landmark-free approach. The approach learns the locations of the anthropometric landmarks present in a database of human models in similar postures and uses this knowledge to automatically predict the locations of these anthropometric landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between adoi:10.1007/s00138-011-0361-9 fatcat:bewbkoh6qfbivamt2tf3uybqju