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Interactive Vector Field Feature Identification
November/December 2010 (vol. 16 no. 6)
pp. 1560-1568
ASCII Text
x 
 
Joel Daniels II, Erik W. Anderson, Luis Gustavo Nonato, Cláudio T. Silva, "Interactive Vector Field Feature Identification," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1560-1568, November/December, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2010.170,
author = {Joel Daniels II and Erik W. Anderson and Luis Gustavo Nonato and Cláudio T. Silva},
title = {Interactive Vector Field Feature Identification},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {16},
number = {6},
issn = {1077-2626},
year = {2010},
pages = {1560-1568},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.170},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Interactive Vector Field Feature Identification
IS - 6
SN - 1077-2626
SP1560
EP1568
EPD - 1560-1568
A1 - Joel Daniels II,
A1 - Erik W. Anderson,
A1 - Luis Gustavo Nonato,
A1 - Cláudio T. Silva,
PY - 2010
KW - vector field
KW - data clustering
KW - feature classification
KW - high-dimensional data
KW - user interaction
VL - 16
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
We introduce a flexible technique for interactive exploration of vector field data through classification derived from userspecified feature templates. Our method is founded on the observation that, while similar features within the vector field may bespatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactivelyhighlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation ofattributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enableinteractive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field pointswithin the distances computed between their associated attribute points. The proposed method is performed at interactive rates forenhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

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Index Terms:
vector field, data clustering, feature classification, high-dimensional data, user interaction
Citation:
Joel Daniels II, Erik W. Anderson, Luis Gustavo Nonato, Cláudio T. Silva, "Interactive Vector Field Feature Identification," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1560-1568, Nov.-Dec. 2010, doi:10.1109/TVCG.2010.170
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