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JMLR
2008
151views more  JMLR 2008»
14 years 11 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
15 years 8 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 1 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 1 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 1 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