Local and Global Comparison of Continuous Functions

We introduce local and global comparison measures for a collection of k ≤ d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k = d = 2 we relate the measures to the set of critical points of one function restricted to the level sets of the other. The definition of the...

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Published in2004 IEEE Visualization Conference pp. 275 - 280
Main Authors Edelsbrunner, Herbert, Harer, John, Natarajan, Vijay, Pascucci, Valerio
Format Conference Proceeding
LanguageEnglish
Published Washington, DC, USA IEEE Computer Society 10.10.2004
IEEE
SeriesACM Conferences
Subjects
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ISBN0780387880
9780780387881
DOI10.1109/VISUAL.2004.68

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Abstract We introduce local and global comparison measures for a collection of k ≤ d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k = d = 2 we relate the measures to the set of critical points of one function restricted to the level sets of the other. The definition of the measures extends to piecewise linear functions for which they are easy to compute. The computation of the measures forms the centerpiece of a software tool which we use to study scientific datasets.
AbstractList We introduce local and global comparison measures for a collection of k ≤ d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k = d = 2 we relate the measures to the set of critical points of one function restricted to the level sets of the other. The definition of the measures extends to piecewise linear functions for which they are easy to compute. The computation of the measures forms the centerpiece of a software tool which we use to study scientific datasets.
We introduce local and global comparison measures for a collection of k /spl les/ d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k = d = 2 we relate the measures to the set of critical points of one function restricted to the level sets of the other. The definition of the measures extends to piecewise linear functions for which they are easy to compute. The computation of the measures forms the centerpiece of a software tool which we use to study scientific datasets.
We introduce local and global comparison measures for a collection of k ? d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k = d = 2 we relate the measures to the set of critical points of one function restricted to the level sets of the other. The definition of the measures extends to piecewise linear functions for which they are easy to compute. The computation of the measures forms the centerpiece of a software tool which we use to study scientific datasets.
Author Natarajan, Vijay
Harer, John
Pascucci, Valerio
Edelsbrunner, Herbert
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  givenname: Valerio
  surname: Pascucci
  fullname: Pascucci, Valerio
  organization: Lawrence Livermore National Laboratory
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Keywords smooth functions
Visualization
Riemannian manifolds
differential forms
time-varying data
comparison measure
Software tool
Riemann manifold
Real function
Smooth function
Computer graphics
Contour line
piecewise function
Continuous function
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Snippet We introduce local and global comparison measures for a collection of k ≤ d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k =...
We introduce local and global comparison measures for a collection of k /spl les/ d real-valued smooth functions on a common d-dimensional Riemannian manifold....
We introduce local and global comparison measures for a collection of k ? d real-valued smooth functions on a common d-dimensional Riemannian manifold. For k =...
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SubjectTerms Applied sciences
Artificial intelligence
Combustion
comparison measure
Computational modeling
Computer science
Computer science; control theory; systems
differential forms
Exact sciences and technology
Fires
Ignition
Level set
Mathematical analysis
Mathematics
Pattern recognition. Digital image processing. Computational geometry
Real functions
Riemannian manifolds
Sciences and techniques of general use
smooth functions
Software measurement
Software performance
Strips
time-varying data
Visualization
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