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» A probabilistic framework for image segmentation
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ICIP
2005
IEEE
14 years 1 months ago
Silhouette-based probabilistic 2D human motion estimation for real-time applications
This paper presents a novel technique for 2D human motion estimation using a single non calibrated camera. The user’s five crucial human features (head, hands and feet) are ext...
Pedro Correa, Jacek Czyz, Toshiyuki Umeda, Ferran ...
MICCAI
2009
Springer
14 years 5 months ago
ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences
The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segm...
Francesco Ciompi, Oriol Pujol, Eduard Ferná...
ICIP
1995
IEEE
14 years 9 months ago
3D super-resolution using generalized sampling expansion
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
ICIP
2002
IEEE
14 years 9 months ago
Joint space-time image sequence segmentation based on volume competition and level sets
In this paper, we address the issue of joint space-time segmentation of image sequences. Typical approaches to such segmentation consider two image frames at a time, and perform t...
Mirko Ristivojevic, Janusz Konrad
ISVC
2009
Springer
14 years 2 months ago
Adaptive Contextual Energy Parameterization for Automated Image Segmentation
Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights...
Josna Rao, Ghassan Hamarneh, Rafeef Abugharbieh