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» Structured Learning with Approximate Inference
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ICIP
2002
IEEE
14 years 9 months ago
A Bayesian approach to inferring vascular tree structure from 2D imagery
We describe a method for inferring tree-like vascular structures from 2D imagery. A Markov Chain Monte Carlo (MCMC) algorithm is employed to produce approximate samples from the p...
Abhir Bhalerao, Elke Thönnes, Roland Wilson, ...
ICCV
2007
IEEE
14 years 9 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
ICML
2010
IEEE
13 years 8 months ago
Accelerated dual decomposition for MAP inference
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
Vladimir Jojic, Stephen Gould, Daphne Koller
ICRA
2009
IEEE
218views Robotics» more  ICRA 2009»
13 years 5 months ago
Automatically and efficiently inferring the hierarchical structure of visual maps
In Simultaneous Localisation and Mapping (SLAM), it is well known that probabilistic filtering approaches which aim to estimate the robot and map state sequentially suffer from poo...
Margarita Chli, Andrew J. Davison
PAMI
2010
205views more  PAMI 2010»
13 years 5 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille