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ICCV
2009
IEEE
16 years 8 months ago
A Global Perspective on MAP Inference for Low-Level Vision
In recent years the Markov Random Field (MRF) has become the de facto probabilistic model for low-level vision applications. However, in a maximum a posteriori (MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
143
Voted
CVPR
2007
IEEE
16 years 5 months ago
Model-Guided Segmentation of 3D Neuroradiological Image Using Statistical Surface Wavelet Model
This paper proposes a novel model-guided segmentation framework utilizing a statistical surface wavelet model as a shape prior. In the model building process, a set of training sh...
Yang Li, Tiow Seng Tan, Ihar Volkau, Wieslaw L. No...
ICCV
2003
IEEE
16 years 5 months ago
Entropy-of-likelihood Feature Selection for Image Correspondence
Feature points for image correspondence are often selected according to subjective criteria (e.g. edge density, nostrils). In this paper, we present a general, non-subjective crit...
Matthew Toews, Tal Arbel
ICCV
1999
IEEE
16 years 5 months ago
Dynamic Feature Ordering for Efficient Registration
Existing sequential feature-based registration algorithms involving search typically either select features randomly (eg. the RANSAC[8] approach) or assume a predefined, intuitive...
Tat-Jen Cham, James M. Rehg
ECCV
2006
Springer
16 years 5 months ago
Dense Photometric Stereo by Expectation Maximization
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...
Tai-Pang Wu, Chi-Keung Tang