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Multiscale Vector Volumes
Lvdi Wang Yizhou Yu Kun Zhou Baining Guo
Tsinghua University University of Illinois at Urbana-Champaign Zhejiang University Microsoft Research Asia
The University of Hong Kong Tsinghua University
Abstract
We introduce multiscale vector volumes, a compact vector repre-
sentation for volumetric objects with complex internal structures
spanning a wide range of scales. With our representation, an object
is decomposed into components and each component is modeled as
an SDF tree, a novel data structure that uses multiple signed dis-
tance functions (SDFs) to further decompose the volumetric com-
ponent into regions. Multiple signed distance functions collectively
can represent non-manifold surfaces and deliver a powerful vector
representation for complex volumetric features. We use multiscale
embedding to combine object components at different scales into
one complex volumetric object. As a result, regions with dramat-
ically different scales and complexities can co-exist in an object.
To facilitate volumetric object authoring and editing, we have also
developed a scripting language and a GUI prototype. With the help
of a recursively defined spatial indexing structure, our vector repre-
sentation supports fast random access, and arbitrary cross sections
of complex volumetric objects can be visualized in real time.
Keywords: volumetric modeling, multiscale representations
1 Introduction
Most natural organisms and materials, such as the human body,
fruits and sedimentary rocks, have rich and complex volumetric
structures, patterns and color variations. Constructing high-quality
digital models for such natural organisms and materials is of vital
importance because they exist everywhere, and literally everything
we see is either a living being, a natural material or something made
from these two. Since volumetric models allow us to visualize the
internal structure of an object, they are valuable graphical contents
that can be used in biomedical research, scientific visualization as
well as educational and training activities.
Nevertheless, constructing high-quality digital models of natural or-
ganisms and materials with complex volumetric properties is an ex-
tremely challenging task. First, how can we compactly represent
volumetric structures and patterns spanning a wide range of scales?
Taking the human body as an example, it has a skeleton, organs
and tissues at the macroscopic scale, cellular structures and neu-
ronal fibers at an intermediate scale as well as proteins and genes at
the molecular scale. Second, how can we represent high-frequency
features in a resolution-independent way? Physical and appearance
properties (e.g. color) change abruptly across different materials or
volumetric components. Such discontinuities typically form thin
surface sheets, which may join or split following an irregular pat-
tern, giving rise to a non-manifold structure (Figure 2). To prevent
visual artifacts when zooming into these high-frequency structures,
a resolution-independent vector representation is desired. A volu-
metric object representation not only needs to depict complex mul-
tiscale structures, but also should be easy to use, which means it
should be easy to create novel objects and easy to view existing ob-
jects in this representation. Thus, a volumetric object representation
should have the following desired properties:
Expressiveness: It should be able to represent volumetric
objects with spatial structures spanning a wide range of
scales and including complex non-manifold features. High-
frequency features should remain sharp during magnification.
Ease of editing: It should be easy and intuitive to create novel
objects and edit existing ones using this representation.
Random access: To be able to provide a timely response to
user interactions, fast visualization is required, which further
demands efficient random access to the volumetric content.
Compactness: Given the limited memory on current graphics
cards, the representation should be as compact as possible.
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