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» A probabilistic framework for image segmentation
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177
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ECCV
2006
Springer
15 years 10 months ago
Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets
Abstract. We present a new algorithm for segmenting a scene consisting of multiple moving dynamic textures. We model the spatial statistics of a dynamic texture with a set of secon...
Atiyeh Ghoreyshi, René Vidal
ICPR
2010
IEEE
15 years 4 months ago
Building Detection in a Single Remotely Sensed Image with a Point Process of Rectangles
Abstract--In this paper we introduce a probabilistic approach of building extraction in remotely sensed images. To cope with data heterogeneity we construct a flexible hierarchical...
Csaba Benedek, Xavier Descombes, Josiane Zerubia
IPMI
2009
Springer
16 years 7 months ago
Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
CVPR
2009
IEEE
17 years 2 months ago
Recognition using Regions
This paper presents a unified framework for object detection, segmentation, and classification using regions. Region features are appealing in this context because: (1) they enco...
Chunhui Gu, Joseph J. Lim, Pablo Arbelaez, Jitendr...
196
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DAGM
2004
Springer
16 years 5 days ago
Fast Statistically Geometric Reasoning About Uncertain Line Segments in 2D- and 3D-Space
This work addresses the two major drawbacks of current statistical uncertain geometric reasoning approaches. In the first part a framework is presented, that allows to represent u...
Christian Beder