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CVPR
2006
IEEE
14 years 7 months ago
Shape-Based Approach to Robust Image Segmentation using Kernel PCA
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum
ICPR
2008
IEEE
14 years 6 days ago
Top down image segmentation using congealing and graph-cut
This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
ICIP
2010
IEEE
13 years 3 months ago
Fast semantic scene segmentation with conditional random field
In this paper, we present a fast approach to obtain semantic scene segmentation with high precision. We employ a two-stage classifier to label all image pixels. First, we use the ...
Wen Yang, Dengxin Dai, Bill Triggs, Gui-Song Xia, ...
IPMI
2005
Springer
14 years 6 months ago
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images
Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain ...
Alan S. Willsky, Godtfred Holmvang, Müjdat &C...
CVPR
2011
IEEE
12 years 9 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk