64 research outputs found
Free-form Shape Modeling in XR: A Systematic Review
Shape modeling research in Computer Graphics has been an active area for
decades. The ability to create and edit complex 3D shapes has been of key
importance in Computer-Aided Design, Animation, Architecture, and
Entertainment. With the growing popularity of Virtual and Augmented Reality,
new applications and tools have been developed for artistic content creation;
real-time interactive shape modeling has become increasingly important for a
continuum of virtual and augmented reality environments (eXtended Reality
(XR)). Shape modeling in XR opens new possibilities for intuitive design and
shape modeling in an accessible way. Artificial Intelligence (AI) approaches
generating shape information from text prompts are set to change how artists
create and edit 3D models. There has been a substantial body of research on
interactive 3D shape modeling. However, there is no recent extensive review of
the existing techniques and what AI shape generation means for shape modeling
in interactive XR environments. In this state-of-the-art paper, we fill this
research gap in the literature by surveying free-form shape modeling work in
XR, with a focus on sculpting and 3D sketching, the most intuitive forms of
free-form shape modeling. We classify and discuss these works across five
dimensions: contribution of the articles, domain setting, interaction tool,
auto-completion, and collaborative designing. The paper concludes by discussing
the disconnect between interactive 3D sculpting and sketching and how this will
likely evolve with the prevalence of AI shape-generation tools in the future
Wire mesh design
We present a computational approach for designing wire meshes, i.e., freeform surfaces composed of woven wires arranged in a regular grid. To facilitate shape exploration, we map material properties of wire meshes to the geometric model of Chebyshev nets. This abstraction is exploited to build an efficient optimization scheme. While the theory of Chebyshev nets suggests a highly constrained design space, we show that allowing controlled deviations from the underlying surface provides a rich shape space for design exploration. Our algorithm balances globally coupled material constraints with aesthetic and geometric design objectives that can be specified by the user in an interactive design session. In addition to sculptural art, wire meshes represent an innovative medium for industrial applications including composite materials and architectural façades. We demonstrate the effectiveness of our approach using a variety of digital and physical prototypes with a level of shape complexity unobtainable using previous methods
Data-Driven Shape Analysis and Processing
Data-driven methods play an increasingly important role in discovering
geometric, structural, and semantic relationships between 3D shapes in
collections, and applying this analysis to support intelligent modeling,
editing, and visualization of geometric data. In contrast to traditional
approaches, a key feature of data-driven approaches is that they aggregate
information from a collection of shapes to improve the analysis and processing
of individual shapes. In addition, they are able to learn models that reason
about properties and relationships of shapes without relying on hard-coded
rules or explicitly programmed instructions. We provide an overview of the main
concepts and components of these techniques, and discuss their application to
shape classification, segmentation, matching, reconstruction, modeling and
exploration, as well as scene analysis and synthesis, through reviewing the
literature and relating the existing works with both qualitative and numerical
comparisons. We conclude our report with ideas that can inspire future research
in data-driven shape analysis and processing.Comment: 10 pages, 19 figure
Brain Structure Segmentation from MRI by Geometric Surface Flow
We present a method for semiautomatic segmentation of brain
structures such as thalamus from MRI images based on the concept
of geometric surface flow. Given an MRI image, the user can
interactively initialize a seed model within region of interest.
The model will then start to evolve by incorporating both boundary
and region information following the principle of variational
analysis. The deformation will stop when an equilibrium state is
achieved. To overcome the low contrast of the original image data,
a nonparametric kernel-based method is applied to simultaneously
update the interior probability distribution during the model
evolution. Our experiments on both 2D and 3D image data
demonstrate that the new method is robust to image noise and
inhomogeneity and will not leak from spurious edge gaps
A Multiresolution PDE-Based Deformable Surface for Medical Imaging Applications
We recently developed a multiresolution PDE-based deformable
surface whose deformation behavior is governed by partial
differential equations (PDEs) such as the weighted minimal surface
flow. Comparing with the level-set approach, our new model has
better control of the mesh quality and model resolution, and is
much simpler to implement since all the computations are local.
The new deformable model is very useful for a variety of medical
imaging applications including boundary reconstruction, surface
visualization, data segmentation, and topology discovery. In this
paper, we demonstrate both the accuracy and robustness of our
model on areas such as medical image segmentation through a number
of experiments on both real (MRI/CT) and synthetic volumetric
datasets
Automatic generation of dynamic skin deformation for animated characters
© 2018 by the authors. Since non-automatic rigging requires heavy human involvements, and various automatic rigging algorithms are less efficient in terms of computational efficiency, especially for current curve-based skin deformation methods, identifying the iso-parametric curves and creating the animation skeleton requires tedious and time-consuming manual work. Although several automatic rigging methods have been developed, but they do not aim at curve-based models. To tackle this issue, this paper proposes a new rigging algorithm for automatic generation of dynamic skin deformation to quickly identify iso-parametric curves and create an animation skeleton in a few milliseconds, which can be seamlessly used in curve-based skin deformation methods to make the rigging process fast enough for highly efficient computer animation applications
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