Deforming and Animating Discretely Sampled Object Representations

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Date
2005
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
A discretely sampled object representation (DSOR) defines a graphical model using data obtained by a sampling process, which takes a collection of samples at discrete positions in space in order to capture certain geometrical and physical properties of one or more objects of interest. Examples of DSORs include images, videos, volume datasets and point datasets. Unlike many commonly used data representations in computer graphics, DSORs lack in geometrical, topological and semantic information, which is much needed for controlling deformation and animation. Hence it poses a significant scientific and technical challenge to develop deformation and animation methods that operate upon DSORs. Such methods can enable computer graphics and computer animation to benefit enormously from the advances of digital imaging technology. In this state of the art report, we survey a wide-range of techniques that have been developed for manipulating, deforming and animating DSORs. We consider a collection of elementary operations for manipulating DSORs, which can serve as building blocks of deformation and animation techniques. We examine a collection of techniques that are designed to transform the geometry shape of deformable DSORs and pay particular attention to their deployment in surgical simulation. We review a collection of techniques for animating digital characters in DSORs, focusing on recent developments in volume animation.
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@inproceedings{
10.2312:egst.20051047
, booktitle = {
Eurographics 2005 - State of the Art Reports
}, editor = {
Yiorgos Chrysanthou and Marcus Magnor
}, title = {{
Deforming and Animating Discretely Sampled Object Representations
}}, author = {
Chen, M.
and
Correa, C.
and
Islam, S.
and
Jones, M. W.
and
Shen, P.-Y.
and
Silver, D.
and
Walton, S. J.
and
Willis, P. J.
}, year = {
2005
}, publisher = {
The Eurographics Association
}, ISBN = {}, DOI = {
10.2312/egst.20051047
} }
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