From Global to Local Statistical Shape Priors

Name: From Global to Local Statistical Shape Priors
Brand: Springer International Publishing AG
SKU: 9783319535074
Price: 551.7 RON
Availability: InStock

Autor: Carsten Last

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Legare: Copertă tare

Editura: Springer International Publishing AG

Disponibilitate: În depozitul extern

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551.70 lei

This book proposes a new approach to handle the problem of limited training data. Common approaches...

Informații despre carte

Autor

Carsten Last

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2017

Pagini

259

EAN

9783319535074

ISBN

3319535072

Enbook ID

15752729

Editura

Springer International Publishing AG

Greutate

5502

Dimensiuni

155 x 235 x 21

Descriere completă

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.

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From Global to Local Statistical Shape Priors

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