A Study of Transfer Function Generation for Time-Varying Volume Data

T. J. Jankun-Kelly, Kwan Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Scopus citations

Abstract

The proper usage and creation of transfer functions for time-varying data sets is an often ignored problem in volume visualization. Although methods and guidelines exist for time-invariant data, little formal study for the timevarying case has been performed. This paper examines this problem, and reports the study that we have conducted to determine how the dynamic behavior of time-varying data may be captured by a single or small set of transfer functions. The criteria which dictate when more than one transfer function is needed were also investigated. Four data sets with different temporal characteristics were used for our study. Results obtained using two different classes of methods are discussed, along with lessons learned. These methods, including a new multiresolution opacity map approach, can be used for semi-automatic generation of transfer functions to explore large-scale time-varying data sets.

Original languageEnglish (US)
Title of host publication2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001
EditorsK. Mueller, A. Kaufman
PublisherThe Eurographics Association
Pages51-66
Number of pages16
ISBN (Electronic)321183737X, 9783211837375
StatePublished - 2001
Event2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001 - Stony Brook, United States
Duration: Jun 21 2001Jun 22 2001

Publication series

Name2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001

Conference

Conference2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001
Country/TerritoryUnited States
CityStony Brook
Period6/21/016/22/01

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Mathematics(all)
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'A Study of Transfer Function Generation for Time-Varying Volume Data'. Together they form a unique fingerprint.

Cite this