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IDA
2009
Springer
15 years 4 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»
15 years 10 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
ICCV
2005
IEEE
15 years 12 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 5 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
ICASSP
2009
IEEE
15 years 4 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