Dynamical binary latent variable models for 3D human pose trackingEI

摘要

We introduce a new class of probabilistic latent vari- able model called the Implicit Mixture of Conditional Re- stricted Boltzmann Machines (imCRBM) for use in human pose tracking. Key properties of the imCRBM are as fol- lows: (1) learning is linear in the number of training exem- plars so it can be learned from large datasets; (2) it learns coherent models of multiple activities; (3) it automatically discovers atomic "movemes"; and (4) it can infer transi- tions between activities, even when such transitions are not present in the ...更多
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CVPR, pp. 631-638, 2010.

被引用次数129|引用|8
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