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Über dieses Buch

This book presents recent advances in the field of shape analysis. Written by experts in the fields of continuous-scale shape analysis, discrete shape analysis and sparsity, and numerical computing who hail from different communities, it provides a unique view of the topic from a broad range of perspectives.

Over the last decade, it has become increasingly affordable to digitize shape information at high resolution. Yet analyzing and processing this data remains challenging because of the large amount of data involved, and because modern applications such as human-computer interaction require real-time processing. Meeting these challenges requires interdisciplinary approaches that combine concepts from a variety of research areas, including numerical computing, differential geometry, deformable shape modeling, sparse data representation, and machine learning. On the algorithmic side, many shape analysis tasks are modeled using partial differential equations, which can be solved using tools from the field of numerical computing. The fields of differential geometry and deformable shape modeling have recently begun to influence shape analysis methods. Furthermore, tools from the field of sparse representations, which aim to describe input data using a compressible representation with respect to a set of carefully selected basic elements, have the potential to significantly reduce the amount of data that needs to be processed in shape analysis tasks. The related field of machine learning offers similar potential.

The goal of the Dagstuhl Seminar on New Perspectives in Shape Analysis held in February 2014 was to address these challenges with the help of the latest tools related to geometric, algorithmic and numerical concepts and to bring together researchers at the forefront of shape analysis who can work together to identify open problems and novel solutions. The book resulting from this seminar will appeal to researchers in the field of shape analysis, image and vision, from those who want to become more familiar with the field, to experts interested in learning about the latest advances.​

Inhaltsverzeichnis

Frontmatter

Numerical Computing for Shape Analysis

Frontmatter

2016 | OriginalPaper | Buchkapitel

Chapter 1. Ornament Analysis with the Help of Screened Poisson Shape Fields

Sibel Tari

2016 | OriginalPaper | Buchkapitel

Chapter 2. A Comparison of Non-Lambertian Models for the Shape-from-Shading Problem

Silvia Tozza, Maurizio Falcone

2016 | OriginalPaper | Buchkapitel

Chapter 3. Direct Variational Perspective Shape from Shading with Cartesian Depth Parametrisation

Yong Chul Ju, Daniel Maurer, Michael Breuß, Andrés Bruhn

2016 | OriginalPaper | Buchkapitel

Chapter 4. Amoeba Techniques for Shape and Texture Analysis

Martin Welk

2016 | OriginalPaper | Buchkapitel

Chapter 5. Increasing the Power of Shape Descriptor Based Object Analysis Techniques

Joviša Žunić, Paul L. Rosin, Mehmet Ali Aktaş

2016 | OriginalPaper | Buchkapitel

Chapter 6. Shape Distances for Binary Image Segmentation

Frank R. Schmidt, Lena Gorelick, Ismail Ben Ayed, Yuri Boykov, Thomas Brox

2016 | OriginalPaper | Buchkapitel

Chapter 7. Segmentation in Point Clouds from RGB-D Using Spectral Graph Reduction

Margret Keuper, Thomas Brox

Sparse Data Representation and Machine Learning for Shape Analysis

Frontmatter

2016 | OriginalPaper | Buchkapitel

Chapter 8. Shape Compaction

Honghua Li, Hao Zhang

2016 | OriginalPaper | Buchkapitel

Chapter 9. Homological Shape Analysis Through Discrete Morse Theory

Leila De Floriani, Ulderico Fugacci, Federico Iuricich

2016 | OriginalPaper | Buchkapitel

Chapter 10. Sparse Models for Intrinsic Shape Correspondence

Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro

2016 | OriginalPaper | Buchkapitel

Chapter 11. Applying Random Forests to the Problem of Dense Non-rigid Shape Correspondence

Matthias Vestner, Emanuele Rodolà, Thomas Windheuser, Samuel Rota Bulò, Daniel Cremers

2016 | OriginalPaper | Buchkapitel

Chapter 12. Accelerating Deformable Part Models with Branch-and-Bound

Iasonas Kokkinos

Deformable Shape Modeling

Frontmatter

2016 | OriginalPaper | Buchkapitel

Chapter 13. Non-rigid Shape Correspondence Using Surface Descriptors and Metric Structures in the Spectral Domain

Anastasia Dubrovina, Yonathan Aflalo, Ron Kimmel

2016 | OriginalPaper | Buchkapitel

Chapter 14. The Perspective Face Shape Ambiguity

William A. P. Smith

2016 | OriginalPaper | Buchkapitel

Chapter 15. On Shape Recognition and Language

Petros Maragos, Vassilis Pitsikalis, Athanasios Katsamanis, George Pavlakos, Stavros Theodorakis

2016 | OriginalPaper | Buchkapitel

Chapter 16. Tongue Mesh Extraction from 3D MRI Data of the Human Vocal Tract

Alexander Hewer, Stefanie Wuhrer, Ingmar Steiner, Korin Richmond

Backmatter

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