VOTS: VOlume doTS as a Point-Based Representation of Volumetric Data | TU Wien

Information

Replaced by: grimm-2004-volume
Publication Type: Technical Report
Workgroup(s)/Project(s): not specified
Date: April 2004
Number: TR-186-2-04-08
Keywords: Graphics Data Structures and Data Types

Abstract

We present Volume dots (Vots), a new primitive for volumetric data modelling, processing, and rendering. Vots are a point-based representation of volumetric data. An individual Vot is specified by the coefficients of a Taylor series expansion, i.e. the function value and higher order derivatives at a specific point. A Vot does not only represent a single sample point, it represents the underlying function within a region. With the Vots representation we have a more intuitive and high-level description of the volume data. This allows direct analytical examination and manipulation of volumetric datasets. Vots enable the representation of the underlying scalar function with specified precision. User-centric importance sampling is also possible, i.e., unimportant volume parts are still present but represented with just very few Vots. As proof of concept, we show Maximum Intensity Projection based on Vots.

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BibTeX

@techreport{GRIMM-2004-FDM,
  title =      "VOTS: VOlume doTS as a Point-Based Representation of
               Volumetric Data",
  author =     "S\"{o}ren Grimm and Stefan Bruckner and Armin Kanitsar and
               Eduard Gr\"{o}ller",
  year =       "2004",
  abstract =   "We present Volume dots (Vots), a new primitive for
               volumetric data modelling, processing, and rendering. Vots
               are a point-based representation of volumetric data. An
               individual Vot is specified by the coefficients of a Taylor
               series expansion, i.e. the function value and higher order
               derivatives at a specific point. A Vot does not only
               represent a single sample point, it represents the
               underlying function within a region. With the Vots
               representation we have a more intuitive and high-level
               description of the volume data. This allows direct
               analytical examination and manipulation of volumetric
               datasets. Vots enable the representation of the underlying
               scalar function with specified precision. User-centric
               importance sampling is also possible, i.e., unimportant
               volume parts are still present but represented with just
               very few Vots. As proof of concept, we show Maximum
               Intensity Projection based on Vots.",
  month =      apr,
  number =     "TR-186-2-04-08",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  keywords =   "Graphics Data Structures and Data Types",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2004/GRIMM-2004-FDM/",
}