From Global to Local Statistical Shape Priors Novel Methods to Obtain Accurate Reconstruction Results with a Limited Amount of Training Shapes /

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...

Ful tanımlama

Detaylı Bibliyografya
Yazar: Last, Carsten (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2017.
Imprint: Springer,
Edisyon:1st ed. 2017.
Seri Bilgileri:Studies in Systems, Decision and Control, 98
Konular:
Computational intelligence.
Artificial intelligence.
Image processing > Digital techniques.
Computer vision.
Computational Intelligence.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Online Erişim:Full-text access
İçindekiler:
  • Basics
  • Statistical Shape Models (SSMs)
  • A Locally Deformable Statistical Shape Model (LDSSM)
  • Evaluation of the Locally Deformable Statistical Shape Model
  • Global-To-Local Shape Priors for Variational Level Set Methods
  • Evaluation of the Global-To-Local Variational Formulation
  • Conclusion and Outlook.

Benzer Materyaller