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Ricci Flow for Shape Analysis and Surface Registration introduces the beautiful and profound Ricci flow theory in a discrete setting. By using basic tools in linear algebra and multivariate calculus, readers can deduce all the major theorems in surface Ricci flow by themselves. The authors adapt the Ricci flow theory to practical computational algorithms, apply Ricci flow for shape analysis and surface registration, and demonstrate the power of Ricci flow in many applications in medical imaging, computer graphics, computer vision and wireless sensor network. Due to minimal pre-requisites, this book is accessible to engineers and medical experts, including educators, researchers, students and industry engineers who have an interest in solving real problems related to shape analysis and surface registration.
This book introduces the theory of Ricci flow in a discrete setting, adapting it for practical computational algorithms in shape analysis and surface registration. The authors, Wei Zeng and Xianfeng David Gu, leverage fundamental tools from linear algebra and multivariate calculus to enable readers to derive key theorems in surface Ricci flow. The text demonstrates the application of Ricci flow in diverse fields such as medical imaging, computer graphics, computer vision, and wireless sensor networks, highlighting its utility in solving real-world problems. With minimal prerequisites, the book aims to be accessible to engineers and medical experts, including educators, researchers, students, and industry professionals.
The book is presented as an accessible introduction to Ricci flow theory for a broad audience, including engineers and medical experts. Its approach emphasizes self-deduction of theorems using foundational mathematical tools, suggesting a pedagogical focus. The practical applications across various technical fields indicate its relevance for researchers and industry professionals seeking to solve problems in shape analysis and surface registration. The minimal prerequisites further suggest an intention to bridge the gap between theoretical mathematics and applied computational science.
Page Count:
139
Publication Date:
2013-10-18
Publisher:
Springer Nature
ISBN-10:
1461487811
ISBN-13:
9781461487814
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