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Author, Editor(s)

Author(s):

Weinkauf, Tino
Theisel, Holger
Van Gelder, Allen
Pang, Alex

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Not MPG Author(s):

Theisel, Holger
Van Gelder, Allen
Pang, Alex

BibTeX cite key*:

weinkauf11b

Title

Title*:

Stable Feature Flow Fields

Journal

Journal Title*:

IEEE Transactions on Visualization and Computer Graphics

Journal's URL:


Download URL
for the article:

http://www.mpi-inf.mpg.de/~weinkauf/publications/documents/weinkauf11b.pdf

Language:

English

Publisher

Publisher's
Name:


Publisher's URL:


Publisher's
Address:


ISSN:


Vol, No, pp, Date

Volume*:

17

Number:

6

Publishing Date:

2011

Pages*:

770-780

Number of
VG Pages:


Page Start:


Page End:


Sequence Number:


DOI:


Note, Abstract, ©

Note:


(LaTeX) Abstract:

Feature Flow Fields are a well-accepted approach for extracting and tracking features. In particular, they are often used to track critical points in time-dependent vector fields and to extract and track vortex core lines. The general idea is to extract the feature or its temporal evolution using a stream line integration in a derived vector field - the so-called Feature Flow Field (FFF). Hence, the desired feature line is a stream line of the FFF. As we will carefully analyze in this paper, the stream lines around this feature line may diverge from it. This creates an unstable situation: if the integration moves slightly off the feature line due to numerical errors, then it will be captured by the diverging neighborhood and carried away from the real feature line. The goal of this paper is to define a new FFF with the guarantee that the neighborhood of a feature line has always converging behavior. This way, we have an automatic correction of numerical errors: if the integration moves slightly off the feature line, it automatically moves back to it during the ongoing integration. This yields results which are an order of magnitude more accurate than the results from previous schemes. We present new stable FFF formulations for the main applications of tracking critical points and solving the Parallel Vectors operator. We apply our method to a number of data sets.

URL for the Abstract:


Categories,
Keywords:

feature extraction, feature flow fields, topology, parallel vectors, time-dependent vector fields

HyperLinks / References / URLs:


Copyright Message:


Personal Comments:


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Access Level:

Internal

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Computer Graphics Group

Audience:

experts only

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{weinkauf11b,
AUTHOR = {Weinkauf, Tino and Theisel, Holger and Van Gelder, Allen and Pang, Alex},
TITLE = {Stable Feature Flow Fields},
JOURNAL = {IEEE Transactions on Visualization and Computer Graphics},
YEAR = {2011},
NUMBER = {6},
VOLUME = {17},
PAGES = {770--780},
}


Entry last modified by Tino Weinkauf, 02/04/2013
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Editor(s)
[Library]
Created
01/27/2013 01:57:12 PM
Revision
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Editor
Tino Weinkauf
Tino Weinkauf


Edit Date
01/27/2013 01:57:49 PM
01/27/2013 01:57:12 PM