Implicit Probabilistic Models of Human Motion for Synthesis and Tracking

Abstract

This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an explicit probabilistic model from available training data is currently impractical. Instead we exploit methods from texture synthesis that treat images as representing an implicit empirical… (More)
DOI: 10.1007/3-540-47969-4_52

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