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» A probabilistic framework for image segmentation
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CVIU
2006
162views more  CVIU 2006»
14 years 9 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
ECCV
2008
Springer
15 years 11 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
RECOMB
2010
Springer
14 years 8 months ago
Predicting Nucleosome Positioning Using Multiple Evidence Tracks
Abstract. We describe a probabilistic model, implemented as a dynamic Bayesian network, that can be used to predict nucleosome positioning along a chromosome based on one or more g...
Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, ...
ICVS
1999
Springer
15 years 1 months ago
3-D Modelling and Robot Localization from Visual and Range Data in Natural Scenes
Abstract. This paper concerns the exploration of a natural environment by a mobile robot equipped with both a video camera and a range sensor (stereo or laser range finder); we fo...
Carlos Parra, Rafael Murrieta-Cid, Michel Devy, Ma...
PAMI
2010
205views more  PAMI 2010»
14 years 8 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille