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121
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IDA
2009
Springer
15 years 9 months ago
Estimating Markov Random Field Potentials for Natural Images
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...
Urs Köster, Jussi T. Lindgren, Aapo Hyvä...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 3 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
102
Voted
ICCV
2005
IEEE
16 years 4 months ago
Towards Ultimate Motion Estimation: Combining Highest Accuracy with Real-Time Performance
Although variational methods are among the most accurate techniques for estimating the optical flow, they have not yet entered the field of real-time vision. Main reason is the gr...
Andrés Bruhn, Joachim Weickert
CVPR
2009
IEEE
16 years 9 months ago
StaRSaC: Stable Random Sample Consensus for Parameter Estimation
We address the problem of parameter estimation in presence of both uncertainty and outlier noise. This is a common occurrence in computer vision: feature localization is perform...
Jongmoo Choi, Gérard G. Medioni
116
Voted
ICASSP
2009
IEEE
15 years 9 months ago
ViBE: A powerful random technique to estimate the background in video sequences
Background subtraction is a crucial step in many automatic video content analysis applications. While numerous acceptable techniques have been proposed so far for background extra...
Olivier Barnich, Marc Van Droogenbroeck