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» Decision Making Using Probabilistic Inference Methods
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ICCV
1995
IEEE
15 years 8 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
WSNA
2003
ACM
15 years 9 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 6 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 6 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 10 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