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» Markov Random Field Modeling in Computer Vision
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ICPR
2004
IEEE
14 years 10 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
ACCV
2009
Springer
13 years 10 months ago
Adaptive-Scale Robust Estimator Using Distribution Model Fitting
We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers. This is a diag...
Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa, ...
FTML
2008
185views more  FTML 2008»
13 years 9 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
IJKESDP
2010
94views more  IJKESDP 2010»
13 years 6 months ago
Rule acquisition for cognitive agents by using estimation of distribution algorithms
Cognitive Agents must be able to decide their actions based on their recognized states. In general, learning mechanisms are equipped for such agents in order to realize intellgent ...
Tokue Nishimura, Hisashi Handa
ICPR
2008
IEEE
14 years 3 months ago
Unsupervised mammograms segmentation
We present a multiscale unsupervised segmenter for automatic detection of potentially cancerous regions of interest containing fibroglandular tissue in digital screening mammogra...
Michal Haindl, Stanislav Mikes