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CVPR
1999
IEEE
16 years 8 months ago
Histogram Clustering for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
CVPR
2003
IEEE
16 years 8 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2005
IEEE
16 years 8 months ago
A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
Qiang Ji, Yang Wang 0002
CVPR
2007
IEEE
16 years 8 months ago
Handwritten Carbon Form Preprocessing Based on Markov Random Field
This paper proposes a statistical approach to degraded handwritten form image preprocessing including binarization and form line removal. The degraded image is modeled by a Markov...
Huaigu Cao, Venu Govindaraju
ICCV
2003
IEEE
16 years 8 months ago
Background Modeling and Subtraction of Dynamic Scenes
Background modeling and subtraction is a core component in motion analysis. The central idea behind such module is to create a probabilistic representation of the static scene tha...
Antoine Monnet, Anurag Mittal, Nikos Paragios, Vis...