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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
16 years 1 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
HUMO
2007
Springer
16 years 26 days ago
Silhouette Based Generic Model Adaptation for Marker-Less Motion Capturing
This work presents a marker-less motion capture system that incorporates an approach to smoothly adapt a generic model mesh to the individual shape of a tracked person. This is don...
Martin Sunkel, Bodo Rosenhahn, Hans-Peter Seidel
IJCAI
1997
15 years 8 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida
JMLR
2010
117views more  JMLR 2010»
15 years 1 months ago
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Xinhua Zhang, Thore Graepel, Ralf Herbrich
TNN
2010
233views Management» more  TNN 2010»
15 years 1 months ago
A hierarchical RBF online learning algorithm for real-time 3-D scanner
In this paper, a novel real-time online network model is presented. It is derived from the hierarchical radial basis function (HRBF) model and it grows by automatically adding unit...
Stefano Ferrari, Francesco Bellocchio, Vincenzo Pi...