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» Discrete Mixture Models for Unsupervised Image Segmentation
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AIPR
2004
IEEE
13 years 11 months ago
An Image Retrieval System Using Multispectral Random Field Models, Color, and Geometric Features
This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves...
Orlando J. Hernandez, Alireza Khotanzad
CVPR
2010
IEEE
13 years 7 months ago
Scene understanding by statistical modeling of motion patterns
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of pattern...
Imran Saleemi, Lance Hartung, Mubarak Shah
ICRA
2005
IEEE
178views Robotics» more  ICRA 2005»
14 years 1 months ago
Supervised Multispectral Image Segmentation using Active Contours
— Active contours have been widely used as image segmentation methods. The use of level set theory has provided more flexibility and convenience for the implementation of active...
Cheolha Pedro Lee, Wesley E. Snyder, Cliff Wang
TNN
2010
216views Management» more  TNN 2010»
13 years 2 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
ECCV
2006
Springer
14 years 9 months ago
Smooth Image Segmentation by Nonparametric Bayesian Inference
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
Peter Orbanz, Joachim M. Buhmann