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ORCID

http://orcid.org/0000-0002-9470-4353

Date of Award

Spring 5-15-2019

Author's School

School of Engineering & Applied Science

Author's Department

Computer Science & Engineering

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

Reconstructing surface from a set of spatial curves is a fundamental problem in computer graphics and computational geometry. It often arises in many applications across various disciplines, such as industrial prototyping, artistic design and biomedical imaging. While the problem has been widely studied for years, challenges remain for handling different type of curve inputs while satisfying various constraints. We study studied three related computational tasks in this thesis. First, we propose an algorithm for reconstructing multi-labeled material interfaces from cross-sectional curves that allows for explicit topology control. Second, we addressed the consistency restoration, a critical but overlooked problem in applying algorithms of surface reconstruction to real-world cross-sections data. Lastly, we propose the Variational Implicit Point Set Surface which allows us to robustly handle noisy, sparse and non-uniform inputs, such as samples from spatial curves.

Language

English (en)

Chair

Tao Ju

Committee Members

Nathan Carr, Ayan Chakrabarti, Ulugbek Kamilov, Caitlin Kelleher,

Comments

Permanent URL: https://doi.org/7936/fz30-pq36

Available for download on Saturday, April 17, 2021

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