Overview

Part Decomposition of 3D Surfaces presents a rigorous exploration of methods for segmenting and understanding complex three-dimensional structures. Originally developed as a doctoral dissertation in 2003, this revised edition preserves the core research while presenting it in a format accessible to a broader technical audience. At the heart of the work lies a fundamental challenge in computer vision and geometric modeling: how to break a continuous surface into meaningful, interpretable components. This problem sits at the intersection of mathematics, computation, and perception. Effective solutions enable downstream tasks such as object recognition, simulation, and geometric analysis. The methods developed in this volume focus on identifying intrinsic structure within 3D meshes through algorithmic decomposition. Emphasis is placed on balancing mathematical rigor with practical implementation, offering approaches that remain relevant to modern applications in computer graphics, CAD, and 3D imaging. Beyond the algorithms themselves, the work reflects a moment in the evolution of computer vision when advances in computation began to make large-scale geometric processing feasible. Many of the underlying ideas continue to inform contemporary research in shape analysis, digital twins, and machine perception. This edition serves both as a historical record and a technical reference and is intended for researchers, graduate students, and practitioners seeking a deeper understanding of how complex surfaces can be reduced to their essential parts-revealing structure where complexity first appears to dominate.

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David L. Page, Ph.D., is a researcher and practitioner in computer vision and three-dimensional imaging, with a focus on the analysis and interpretation of geometric data. He earned his doctorate in Electrical Engineering from the University of Tennessee, Knoxville, in 2003, where his research centered on the decomposition of complex 3D surfaces into meaningful components. That work forms the foundation of this volume.Following his doctoral studies, Dr. Page continued to work at the intersection of computation and perception, applying principles of geometric modeling, image analysis, and algorithm design to real-world problems. His work has spanned areas such as 3D reconstruction, shape analysis, and large-scale processing of spatial data, contributing to the broader advancement of computer vision and imaging systems.In his current work, Dr. Page remains engaged in advancing methods for understanding structure in complex data, with particular interest in how modern computational approaches-including high-performance computing and machine learning-can extend earlier foundations in geometric analysis. His work reflects a consistent theme: extracting meaning from complexity through disciplined, algorithmic insight.Dr. Page is also an author of several books that explore both technical and civic themes, bringing a researcher's clarity to a wide range of subjects. Across these efforts, he maintains a commitment to clear thinking, practical application, and the enduring value of foundational ideas in a rapidly evolving technological landscape.

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