Téléchargez le livre : From Global to Local Statistical Shape Priors

From Global to Local Statistical Shape Priors

Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes
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Paru le : 2017-03-14

This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both o...
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Description du livre

This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.

À propos

Auteur
Carsten Last
Éditeur
Springer
Collection
Studies in Systems, Decision and Control
Parution
2017-03-14
Pages
259 pages
EAN papier
9783319535074

Auteur(s) du livre


Defaut-Illustration Carsten Last

Caractéristiques détaillées - droits

EAN PDF
9783319535081
Prix
94,94 €
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
13855 Ko
Ce livre est accessible aux handicaps informations d'accessibilité
EAN EPUB
9783319535081
Prix
94,94 €
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
11622 Ko
Ce livre est accessible aux handicaps informations d'accessibilité

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