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CVGIP
2006
75views more  CVGIP 2006»
13 years 10 months ago
Momentum-based parameterization of dynamic character motion
This paper presents a system for rapid editing of highly dynamic motion capture data. At the heart of this system is an optimization algorithm that can transform the captured moti...
Yeuhi Abe, C. Karen Liu, Zoran Popovic
ICIP
2000
IEEE
14 years 11 months ago
Motion Estimation Using Adaptive Blocksize Observation Model and Efficient Multiscale Regularization
Bayesian motion estimation requires two pdf models: observation model and motion field (prior) model. The optimization process for this method uses sequential approach, e.g. simul...
Stephanus Suryadarma Tandjung, Teddy Surya Gunawan...
CSDA
2010
87views more  CSDA 2010»
13 years 10 months ago
Semiparametric indirect utility and consumer demand
In this paper, we specify the indirect utility function as a partially linear model, where utility is nonparametric in expenditure and parametric (with fixed- or varying-coefficie...
Krishna Pendakur, Michael Scholz, Stefan Sperlich
ESSMAC
2003
Springer
14 years 3 months ago
Nonlinear Predictive Control with a Gaussian Process Model
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Jus Kocijan, Roderick Murray-Smith
TASLP
2010
97views more  TASLP 2010»
13 years 4 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals