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ICIP
2004
IEEE
14 years 9 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte
PAMI
2007
155views more  PAMI 2007»
13 years 7 months ago
Localization of Shapes Using Statistical Models and Stochastic Optimization
—In this paper, we present a new model for deformations of shapes. A pseudolikelihood is based on the statistical distribution of the gradient vector field of the gray level. The...
François Destrempes, Max Mignotte, Jean-Fra...
CVPR
2007
IEEE
14 years 9 months ago
Tracking as Repeated Figure/Ground Segmentation
Tracking over a long period of time is challenging as the appearance, shape and scale of the object in question may vary. We propose a paradigm of tracking by repeatedly segmentin...
Xiaofeng Ren, Jitendra Malik
MICCAI
2003
Springer
14 years 8 months ago
A New Brain Segmentation Framework
We present a new brain segmentation framework which we apply to T1-weighted magnetic resonance image segmentation. The innovation of the algorithm in comparison to the state-of-the...
Torsten Butz, Patric Hagmann, Eric Tardif, Reto Me...
CRV
2009
IEEE
237views Robotics» more  CRV 2009»
14 years 2 months ago
SEC: Stochastic Ensemble Consensus Approach to Unsupervised SAR Sea-Ice Segmentation
The use of synthetic aperture radar (SAR) has become an integral part of sea-ice monitoring and analysis in the polar regions. An important task in sea-ice analysis is to segment ...
Alexander Wong, David A. Clausi, Paul W. Fieguth