Using optimized gaussian mixture model rules and global tracking graph for feature extraction and tracking in time-varying data

Author:

Ma JiORCID,Chen Jinjin,Yang Chang

Funder

national natural science foundation of china

state key laboratory of computer aided design and computer graphics

Publisher

Springer Science and Business Media LLC

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software

Reference38 articles.

1. Bai, Z.H., Tao, Y.B., Lin, H.: Time-varying volume visualization: a survey. J. Vis. 23, 745–761 (2020)

2. Saikia, H., Weinkauf, T.: Global feature fracking and similarity estimation in time-dependent scalar fields. Comput. Graph. Forum 26(3), 1–11 (2017)

3. Wang, Y.H., Chen, W., Zhang, J., Dong, T.X., Shan, G.H., Chi, X.B.: Efficient volume exploration using the gaussian mixture model. IEEE Trans. Vis. Comput. Graph. 17(11), 1560–1573 (2011)

4. Liu, S., Levine, J., Bremer, P., Pascucci, V.: Gaussian mixture model based volume visualization. In: IEEE Symposium on Large-Scale Data Analysis and Visualization, pp. 73–77 (2012)

5. Obermaier, H., Joy, K.I.: Local data models for probabilistic transfer function design. In: EuroVis, pp. 43–47 (2013)

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