3D Surface Reconstruction: Multi-Scale Hierarchical Approaches

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Springer Science & Business Media, Oct 28, 2012 - Computers - 162 pages
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3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. The configuration of the model parameters, the rationale and solutions are described and discussed in detail so the reader has a strong understanding of the methodology. Modeling starts from data captured by 3D digitizers and makes the process even more clear and engaging.

Innovative approaches, based on two popular machine learning paradigms, namely Radial Basis Functions and the Support Vector Machines, are also introduced. These paradigms are innovatively extended to a multi-scale incremental structure, based on a hierarchical scheme. The resulting approaches allow readers to achieve high accuracy with limited computational complexity, and makes the approaches appropriate for online, real-time operation. Applications can be found in any domain in which regression is required.

3D Surface Reconstruction: Multi-Scale Hierarchical Approaches is designed as a secondary text book or reference for advanced-level students and researchers in computer science. This book also targets practitioners working in computer vision or machine learning related fields.

 

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Contents

Chapter 1 Introduction
1
Chapter 2 Scanner systems
21
Chapter 3 Reconstruction
43
Chapter 4 Surface fitting as a regression problem
61
Chapter 5 Hierarchical Radial Basis Functions Networks
77
Chapter 6 Hierarchical Support Vector Regression
111
Chapter 7 Conclusion
143
Glossary
149
References
151
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