TY - GEN
T1 - A Study of Transfer Function Generation for Time-Varying Volume Data
AU - Jankun-Kelly, T. J.
AU - Ma, Kwan Liu
N1 - Funding Information:
This work was supported by NASA Ames Research Center, the National Science Foundation, and Lawrence Livermore National Laboratory. The authors are grateful for those responsible for providing the data sets for our study. Finally, we thank the reviewers and the attendees of the Volume Graphics Workshop for their input.
Publisher Copyright:
© VG 2001. All rights reserved.
PY - 2001
Y1 - 2001
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:85022110863
T3 - 2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001
SP - 51
EP - 66
BT - 2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001
A2 - Mueller, K.
A2 - Kaufman, A.
PB - The Eurographics Association
T2 - 2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001
Y2 - 21 June 2001 through 22 June 2001
ER -