"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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