Kniha From Global to Local Statistical Shape Priors Carsten Last

From Global to Local Statistical Shape Priors

Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes

Autor: Carsten Last
Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: Skladem u dodavatele
Odesíláme za 5-8 dnů
2 286
This book proposes a new approach to handle the problem of limited training data. Common approaches...

Informace o knize

Autor
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2018
Stránek
259
EAN
9783319851693
Enbook ID
20093954
Hmotnost
4336
Rozměry
155 x 235 x 16

Kompletní popis

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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