We investigate the usability of functional surface optimization for the design of free-form shapes. The optimal shape is subject to only a few constraints and is influenced largely by the choice of the energy functional. Among the many possible functionals that could be minimized, we focus on third-order functionals that measure curvature variation over the surface.
We provide a simple explanation of the third-order surface behavior and decompose the curvature-variation function into its Fourier components. We extract four geometrically intuitive, parameterization-independent parameters that completely define the third order shape at a surface point. We formulate third-order energy functionals as functions of these third-order shape parameters.
By computing the energy minimizers for a number of canonical input shapes, we provide a catalog of diverse functionals that span a reasonable domain of aesthetic styles. The functionals can be linearly combined to obtain new functionals with intermediate aesthetic styles. Our side-by-side tabular comparison of functionals helps to develop an intuition for the preferred aesthetic styles of the functionals and to predict the aesthetic styles preferred by a new combination of the functionals.
To compare the shapes preferred by the functionals, we built a robust surface optimization system. We represent shapes using Catmull--Clark subdivision surfaces, with the control mesh vertices acting as degrees of freedom for the optimization. The energy is minimized by an off-the-shelf implementation of a quasi-Newton method. We discuss some future work for further improving the optimization system and end with some conclusions on the use of optimization for aesthetic design.
Title
Minimizing Curvature Variation for Aesthetic Surface Design
Published
2008-10-07
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
EECS-2008-129
Type
Text
Extent
109 p
Archive
The Engineering Library
Usage Statement
Researchers may make free and open use of the UC Berkeley Library’s digitized public domain materials. However, some materials in our online collections may be protected by U.S. copyright law (Title 17, U.S.C.). Use or reproduction of materials protected by copyright beyond that allowed by fair use (Title 17, U.S.C. § 107) requires permission from the copyright owners. The use or reproduction of some materials may also be restricted by terms of University of California gift or purchase agreements, privacy and publicity rights, or trademark law. Responsibility for determining rights status and permissibility of any use or reproduction rests exclusively with the researcher. To learn more or make inquiries, please see our permissions policies (https://www.lib.berkeley.edu/about/permissions-policies).