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EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence
(Georgia Institute of Technology, 2003)
Learning spatial models from sensor data raises the challenging data association
problem of relating model parameters to individual measurements. This paper proposes an
EM-based algorithm, which solves the model learning ...
An MCMC-based Particle Filter for Tracking Multiple Interacting Targets
(Georgia Institute of Technology, 2003)
We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such interactions cause ...
A Sample of Monte Carlo Methods in Robotics and Vision
(Georgia Institute of Technology, 2003-12)
Approximate inference by sampling from an appropriately constructed posterior has recently seen a dramatic increase in popularity in both the robotics and computer vision community. In this
paper, I will describe a number ...
Multitarget Tracking with Split and Merged Measurements
(Georgia Institute of Technology, 2005-06)
In many multitarget tracking applications in computer
vision, a detection algorithm provides locations of potential
targets. Subsequently, the measurements are associated
with previously estimated target trajectories
in ...