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JMLR
2008
151views more  JMLR 2008»
15 years 6 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs
CVPR
2010
IEEE
16 years 2 months ago
Nonparametric Higher-Order Learning for Interactive Segmentation
In this paper, we deal with a generative model for multi-label, interactive segmentation. To estimate the pixel likelihoods for each label, we propose a new higher-order formulatio...
Tae Hoon Kim (Seoul National University), Kyoung M...
CVPR
2005
IEEE
16 years 8 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
CVPR
1998
IEEE
16 years 8 months ago
Hierarchical Morphable Models
This paper presents a new technique for modelling object classes (such as faces) and matching the model to novel images from the object class. The technique can be used for a vari...
Michael J. Jones, Tomaso Poggio
ECCV
2008
Springer
16 years 8 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher