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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 ...
What Are the Ants Doing? Vision-Based Tracking and Reconstruction of Control Programs
(Georgia Institute of Technology, 2005-04)
In this paper, we study the problem of going
from a real-world, multi-agent system to the generation of
control programs in an automatic fashion. In particular,
a computer vision system is presented, capable of ...
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 Multi-Camera Pose Tracker for Assisting the Visually Impaired
(Georgia Institute of Technology, 2005-06)
6DOF Pose tracking is useful in many contexts, e.g.,
in augmented reality (AR) applications. In particular,
we seek to assist visually impaired persons by providing
them with an auditory interface to their environment
through ...
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 ...
Semantic Modeling of Places using Objects
(Georgia Institute of Technology, 2007-06)
While robot mapping has seen massive strides
recently, higher level abstractions in map representation are
still not widespread. Maps containing semantic concepts such
as objects and labels are essential for many tasks ...
GroupSAC: Efficient Consensus in the Presence of Groupings
(Georgia Institute of Technology, 2009-09)
We present a novel variant of the RANSAC algorithm
that is much more efficient, in particular when dealing with
problems with low inlier ratios. Our algorithm assumes
that there exists some grouping in the data, based ...
Out-of-Core Bundle Adjustment for Large-Scale 3D Reconstruction
(Georgia Institute of Technology, 2007-10)
Large-scale 3D reconstruction has recently received
much attention from the computer vision community. Bundle
adjustment is a key component of 3D reconstruction
problems. However, traditional bundle adjustment ...
Spectral Partitioning for Structure from Motion
(Georgia Institute of Technology, 2003-10)
We propose a spectral partitioning approach for large-scale
optimization problems, specifically structure from motion.
In structure from motion, partitioning methods reduce the
problem into smaller and better conditioned ...
Bayesian Surprise and Landmark Detection
(Georgia Institute of Technology, 2009-05)
Automatic detection of landmarks, usually special
places in the environment such as gateways, for topological
mapping has proven to be a difficult task. We present the use of
Bayesian surprise, introduced in computer ...