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» A probabilistic model for classifying segmented images
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CVPR
2001
IEEE
16 years 1 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 6 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 11 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
MICCAI
2008
Springer
16 years 29 days 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 11 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...