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|a Diffusion-driven wavelet design for shape analysis /
|c Tingbo Hou, Hong Qin.
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|a Introduction -- Part I. Theories -- Wavelet Theory -- Heat Diffusion Theory -- Admissible Diffusion Wavelets -- Mexican Hat Wavelet -- Anisotropic Wavelet -- Wavelet Generation -- Part II. Applications -- Implementation -- Shape Representation -- Geometry Processing -- Feature Definition and Detection -- Shape Matching, Registration, and Retrieval.
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|a From Design Methods and Generation Schemes to State-of-the-Art ApplicationsWavelets are powerful tools for functional analysis and geometry processing, enabling researchers to determine the structure of data and analyze 3D shapes. Suitable for researchers in computer graphics, computer vision, visualization, medical imaging, and geometric modeling as well as graduate and senior undergraduate students in computer science, Diffusion-Driven Wavelet Design for Shape Analysis presents recent research results in wavelet designs on 3D shapes and their applications in shape analysis. It explains how to apply the design methods to various types of 3D data, such as polygonal meshes, point clouds, manifolds, and volumetric images.
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