| Localization of shapes using statistical models and stochastic optimization. | |
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MedLine Citation:
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PMID: 17627047 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In this paper, we present a new model for deformations of shapes. A pseudo-likelihood is based on the statistical distribution of the gradient vector field of the gray level. The prior distribution is based on the Probabilistic Principal Component Analysis (PPCA). We also propose a new model based on mixtures of PPCA that is useful in the case of greater variability in the shape. A criterion of global or local object specificity based on a preliminary color segmentation of the image, is included into the model. The localization of a shape in an image is then viewed as minimizing the corresponding Gibbs field. We use the Exploration/Selection (E/S) stochastic algorithm in order to find the optimal deformation. This yields a new unsupervised statistical method for localization of shapes. In order to estimate the statistical parameters for the gradient vector field of the gray level, we use an Iterative Conditional Estimation (ICE) procedure. The color segmentation of the image can be computed with an Exploration/Selection/Estimation (ESE) procedure. |
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Authors:
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Francois Destrempes; Max Mignotte; Jean-Francois Angers |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: 29 ISSN: 0162-8828 ISO Abbreviation: IEEE Trans Pattern Anal Mach Intell Publication Date: 2007 Sep |
Date Detail:
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Created Date: 2007-07-13 Completed Date: 2007-12-31 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: United States |
Other Details:
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Languages: eng Pagination: 1603-15 Citation Subset: IM |
Affiliation:
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DIRO, Université de Montréal, Montreal, Canada. destremp@iro.umontreal.ca |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Artificial Intelligence* Computer Simulation Data Interpretation, Statistical Image Enhancement / methods* Image Interpretation, Computer-Assisted / methods* Imaging, Three-Dimensional / methods Models, Statistical* Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity Stochastic Processes |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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