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» A probabilistic model for classifying segmented images
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CVPR
2001
IEEE
15 years 11 months ago
3D Object Recognition from Range Images using Local Feature Histograms
This paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occ...
Bastian Leibe, Bernt Schiele, Günter Hetzel, ...
ICPR
2008
IEEE
15 years 4 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...
TIP
2002
179views more  TIP 2002»
14 years 9 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
90
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MICCAI
2008
Springer
15 years 11 months ago
Active Volume Models with Probabilistic Object Boundary Prediction Module
We propose a novel Active Volume Model (AVM) which deforms in a free-form manner to minimize energy. Unlike Snakes and level-set active contours which only consider curves or surfa...
Tian Shen, Yaoyao Zhu, Xiaolei Huang, Junzhou H...
TMM
2002
104views more  TMM 2002»
14 years 9 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...