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MIA
2010
170views more  MIA 2010»
13 years 2 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
CVPR
2009
IEEE
15 years 3 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CVPR
2009
IEEE
15 years 3 months ago
Minimizing Sparse Higher Order Energy Functions of Discrete Variables
Higher order energy functions have the ability to encode high level structural dependencies between pixels, which have been shown to be extremely powerful for image labeling pro...
Carsten Rother (Microsoft Research Cambridge), Pus...
CVPR
2007
IEEE
14 years 10 months ago
Feature Extraction by Maximizing the Average Neighborhood Margin
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
Fei Wang, Changshui Zhang
ICCV
2005
IEEE
14 years 10 months ago
Fusion of Multi-View Silhouette Cues Using a Space Occupancy Grid
In this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. To this aim, we propose a new framework for multi-view s...
Jean-Sébastien Franco, Edmond Boyer