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Recent works on 3D human pose tracking using unsupervised methods typically focus on improving the optimization framework to find a better maximum in the likelihood function (i.e., the tracker). In contrast, in this paper, we focus on improving the likelihood function, by making it more robust and less ambiguous, thus making the optimization task easier. In particular, we propose an exponential chamfer...