Case study: application of feature tracking to analysis of autoignition simulation data
作者： Wendy S. Koegler
关键词: Data visualization 、 Feature tracking 、 Data mining 、 Feature extraction 、 Feature detection (computer vision) 、 Computer science 、 Analysis tools 、 Focus (optics) 、 Process (computing) 、 Autoignition temperature
摘要: The focus of this paper is to evaluate the usefulness some basic feature tracking algorithms as analysis tools for combustion datasets by application a dataset modeling autoignition. Features defined areas high intermediate concentrations were examined explore initial phases in autoignition process.
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sci-hub.st 参考文章(8)
H.J.W. Spoelder, F. Reinders, F.H. Post, Visualization of Time-Dependent Data using Feature Tracking 5th Annual Conference of the Advanced School for Computing and Imaging, Heijen. pp. 150- 157 ,(1999)
R. Armstrong, D. Gannon, A. Geist, K. Keahey, S. Kohn, L. McInnes, S. Parker, B. Smolinski, Toward a common component architecture for high-performance scientific computing high performance distributed computing. pp. 13- ,(1999) , 10.1109/HPDC.1999.805289
William E. Lorensen, Will Schroeder, Kenneth M. Martin, The visualization toolkit (2nd ed.): an object-oriented approach to 3D graphics Prentice-Hall, Inc.. ,(1998)
Frits H. Post, Wim C. de Leeuw, I. Ari Sadarjoen, Freek Reinders, Theo van Walsum, Global, geometric, and feature-based techniques for vector field visualization Future Generation Computer Systems. ,vol. 15, pp. 87- 98 ,(1999) , 10.1016/S0167-739X(98)00050-8
D. Silver, Xin Wang, Tracking and visualizing turbulent 3D features IEEE Transactions on Visualization and Computer Graphics. ,vol. 3, pp. 129- 141 ,(1997) , 10.1109/2945.597796
R. Samtaney, D. Silver, N. Zabusky, J. Cao, Visualizing features and tracking their evolution IEEE Computer. ,vol. 27, pp. 20- 27 ,(1994) , 10.1109/2.299407
Deborah Silver, Xin Wang, Tracking scalar features in unstructured data sets ieee visualization. pp. 79- 86 ,(1998) , 10.5555/288216.288228
D. Silver, X. Wang, Tracking scalar features in unstructured data sets ieee visualization. pp. 79- 86 ,(1998) , 10.1109/VISUAL.1998.745288