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» Meta-Evaluation of Image Segmentation Using Machine Learning
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ICPR
2008
IEEE
14 years 1 months 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...
ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
13 years 5 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
CVPR
2008
IEEE
14 years 9 months ago
Unsupervised estimation of segmentation quality using nonnegative factorization
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the...
Roman Sandler, Michael Lindenbaum
ICIP
2009
IEEE
13 years 5 months ago
Precise head segmentation on arbitrary backgrounds
We propose a method for segmentation of frontal human portraits from arbitrary unknown backgrounds. Semantic information is used to project the face into a normalized reference fr...
David C. Schneider, Benjamin Prestele, Peter Eiser...
RIAO
2007
13 years 9 months ago
Using the Knowledge of Object Colors to Segment Images and Improve Web Image Search
With web image search engines, we face a situation where the results are very noisy, and when we ask for a specific object, we are not ensured that this object is contained in all...
Christophe Millet, Isabelle Bloch