TY - JOUR
T1 - Complementary space for enhanced uncertainty and dynamics visualization
AU - Bajaj, Chandrajit
AU - Gillette, Andrew
AU - Goswami, Samrat
AU - Kwon, Bong June
AU - Rivera, Jose
N1 - Funding Information:
We would like to thank previous members of the CCV lab who worked on these projects, including Katherine Claridge, Vinay Siddavanahalli, and Bong-Soo Sohn. This research was supported in part by NSF grants DMS-0636643, CNS-0540033 and NIH contracts R01-EB00487, R01-GM074258, R01-GM07308.
Funding Information:
ACKNOWLEDGMENTS We would like to thank previous members of the CCV lab who worked on these projects, including Katherine Claridge, Vinay Siddavanahalli, and Bong-Soo Sohn. This research was supported in part by NSF grants DMS-0636643, CNS-0540033 and NIH contracts R01-EB00487, R01-GM074258, R01-GM07308.
Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2011.
PY - 2011
Y1 - 2011
N2 - Many computational modeling pipelines for geometry processing and visualization focus on topologically and geometrically accurate shape reconstruction of “primal” space, meaning the surface of interest and the volume it contains. Certain features of a surface such as pockets, tunnels, and voids (small, closed components) often represent important properties of the model and yet are difficult to detect or visualize in a model of primal space alone. It is natural, then, to consider what information can be gained from a model and visualization of complementary space, i.e. the space exterior to but still “near” the surface in question. In this paper, we show how complementary space can be used as a tool for both uncertainty and dynamics visualizations and analysis.
AB - Many computational modeling pipelines for geometry processing and visualization focus on topologically and geometrically accurate shape reconstruction of “primal” space, meaning the surface of interest and the volume it contains. Certain features of a surface such as pockets, tunnels, and voids (small, closed components) often represent important properties of the model and yet are difficult to detect or visualize in a model of primal space alone. It is natural, then, to consider what information can be gained from a model and visualization of complementary space, i.e. the space exterior to but still “near” the surface in question. In this paper, we show how complementary space can be used as a tool for both uncertainty and dynamics visualizations and analysis.
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U2 - 10.1007/978-3-642-15014-2_18
DO - 10.1007/978-3-642-15014-2_18
M3 - Conference article
AN - SCOPUS:84946011655
SP - 217
EP - 228
JO - Mathematics and Visualization
JF - Mathematics and Visualization
SN - 1612-3786
IS - 202489
T2 - 3rd Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis 2009
Y2 - 23 February 2009 through 24 February 2009
ER -