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» Robust Kernel-Based Tracking using Optimal Control
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ICMLA
2010
15 years 14 days ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
129
Voted
ICRA
2007
IEEE
211views Robotics» more  ICRA 2007»
15 years 8 months ago
Control Camera and Light Source Positions using Image Gradient Information
— In this paper, we propose an original approach to control camera position and/or lighting conditions in an environment using image gradient information. Our goal is to ensure a...
Éric Marchand
134
Voted
CVPR
2010
IEEE
15 years 8 months ago
Free-Form Mesh Tracking : a Patch-Based Approach
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...
Cedric Cagniart, Edmond Boyer, Slobodan Ilic
CVPR
2010
IEEE
15 years 2 months ago
Free-form mesh tracking: A patch-based approach
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...
Cedric Cagniart, Edmond Boyer, Slobodan Ilic
115
Voted
AAAI
1998
15 years 3 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge