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In this paper we propose a novel method for discriminative monocular human pose tracking using a mixture of Gaussian processes and a dynamic programming algorithm for selecting the optimal expert at each frame. The proposed tracking mechanism incorporates a dynamical model into the predictive distribution which is combined with the appearance model in a principled manner. This model is able to give a smoother predicted pose and resolves ambiguities in the image to pose mapping. We introduce adoi:10.5244/c.26.7 dblp:conf/bmvc/FergieG12 fatcat:btdvc7fndjb4tpc5iykzgw56ua