The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


"Differential Methods for Intuitive 3D Shape Modeling"

By

Mr. Hongbo Fu


Abstract

Modeling 3D digital shapes, such as curves and meshes, manually is
challenging for three main reasons. First, realistic shapes are generally
complex and involve many unknown degrees of freedom. Second, users usually
only have 2D input devices, which are inadequate for manipulating 3D
shapes. Third, unlike sculptors, ordinary people usually have no precise
space perception, making precisely adjusting relative positions of 3D
shapes even harder.

This thesis presents several novel intuitive techniques that make the
modeling process significantly less labor-intensive. We achieve a balance
between the control ntuitiveness of tools and the geometric complexity of
modeling output. Our techniques allow the user to intuitively control the
modeling effect through only a small set of easy-to-use manipulators. The
unknown vertex positions of the final models are then computed by solving
a system of linear partial differential equations (i.e., the Laplace or
Poisson equations) subject to the constraints derived from the
manipulators. These differential-based techniques contribute to three
important modeling applications: mesh deformation, mesh merging and
hairstyle design. The differential mesh deformation technique allows the
user to manipulate a small set of handles to deform highly detailed meshes
interactively and to achieve physically plausible deformation effects. The
differential mesh merging framework relieves the user's burden of both
precise locating of 3D models and precise specification of merging
boundaries over the meshes to be merged. For hairstyle modeling, we design
a sketching interface and adapt an incremental solver to allow users to
design compelling hairstyles by drawing only a small set of strokes. For
all these algorithms, we pre-compute the most computationally expensive
components to achieve interactive modeling with fast response. Extensive
experiments demonstrate the robustness and usefulness of our techniques.


Date:			Friday, 20 July 2007

Time:			10:00a.m.-12:00noon

Venue:			Room 3501
			Lifts 25-26

Chairman:		Prof. Jimmy Fung (MATH)

Committee Members:	Prof. Chiew-Lan Tai (Supervisor)
			Prof. Huamin Qu
			Prof. Long Quan
			Prof. Beifang Chen (MATH)
			Prof. Pheng-Ann Heng (Comp. Sci. & Engg., CUHK)


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