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» Decision Making Using Probabilistic Inference Methods
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ICCV
1995
IEEE
15 years 6 months ago
Bayesian Decision Theory, the Maximum Local Mass Estimate, and Color Constancy
Computational vision algorithms are often developed in a Bayesian framework. Two estimators are commonly used: maximum a posteriori (MAP), and minimum mean squared error (MMSE). W...
William T. Freeman, David H. Brainard
121
Voted
WSNA
2003
ACM
15 years 7 months ago
Parametric probabilistic sensor network routing
Motivated by realistic sensor network scenarios that have mis-informed nodes and variable network topologies, we propose a fundamentally different approach to routing that combine...
Christopher L. Barrett, Stephan Eidenbenz, Lukas K...
CVPR
2008
IEEE
16 years 4 months ago
Real-time pose estimation of articulated objects using low-level motion
We present a method that is capable of tracking and estimating pose of articulated objects in real-time. This is achieved by using a bottom-up approach to detect instances of the ...
Ben Daubney, David P. Gibson, Neill W. Campbell
ECCV
2000
Springer
16 years 4 months ago
Non-linear Bayesian Image Modelling
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Christopher M. Bishop, John M. Winn
CIVR
2007
Springer
180views Image Analysis» more  CIVR 2007»
15 years 8 months ago
Probabilistic matching and resemblance evaluation of shapes in trademark images
We present a novel matching and similarity evaluation method for planar geometric shapes represented by sets of polygonal curves. Given two shapes, the matching algorithm randomly...
Helmut Alt, Ludmila Scharf, Sven Scholz