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» Probabilistic Scene Models for Image Interpretation
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ICCV
2009
IEEE
14 years 7 months ago
Segmentation, ordering and multi-object tracking using graphical models
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Chaohui Wang, Martin de La Gorce, Nikos Paragios
NIPS
2008
14 years 11 months ago
An ideal observer model of infant object perception
Before the age of 4 months, infants make inductive inferences about the motions of physical objects. Developmental psychologists have provided verbal accounts of the knowledge tha...
Charles Kemp, Fei Xu
ICPR
2008
IEEE
15 years 11 months ago
Extraction of shoe-print patterns from impression evidence using Conditional Random Fields
Impression evidence in the form of shoe-prints are commonly found in crime scenes. A critical step in automatic shoe-print identification is extraction of the shoe-print pattern. ...
Sargur N. Srihari, Veshnu Ramakrishnan
TMI
2010
217views more  TMI 2010»
14 years 4 months ago
A Generative Model for Image Segmentation Based on Label Fusion
We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inferen...
Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Le...
ICIP
1999
IEEE
15 years 11 months ago
Uncertainties in Bayesian Geometric Models
Deformable geometric models fit very naturally into the context of Bayesian analysis. The prior probability of boundary shapes is taken to proportional to the negative exponential...
Kenneth M. Hanson, Gregory S. Cunningham, Robert J...