Estimation of articulated motion using kinematically constrained mixture densities
- 22 November 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
We address the problem of articulated posture estimation in it's general form. Namely, the recovery of full 3D posture parameters from an uncontrolled scene. Stochastic modeling of low-level image data is unified with models of object kinematic structure through a constrained mixture of observation processes. A modified Expectation-Maximization algorithm is proposed for this purpose. Early experiments qualitatively demonstrate the efficacy of our approach.Keywords
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