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» Robot trajectory optimization using approximate inference
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IJCV
2008
188views more  IJCV 2008»
13 years 7 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
JMLR
2010
149views more  JMLR 2010»
13 years 2 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 7 days ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
IROS
2009
IEEE
185views Robotics» more  IROS 2009»
14 years 2 months ago
Scalable and convergent multi-robot passive and active sensing
— A major barrier preventing the wide employment of mobile networks of robots in tasks such as exploration, mapping, surveillance, and environmental monitoring is the lack of efï...
Elias B. Kosmatopoulos, Lefteris Doitsidis, Konsta...
ICPR
2008
IEEE
14 years 8 months ago
Solving quadratically constrained geometrical problems using lagrangian duality
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point ...
Carl Olsson, Anders Eriksson