A normalized-cut algorithm for hierarchical vector field data segmentation

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In the context of vector field data visualization, it is often desirable to construct a hierarchical data representation. One possibility to construct a hierarchy is based on clustering vectors using certain similarity criteria. We combine two fundamental approaches to cluster vectors and construct hierarchical vector field representations. For clustering, a locally constructed linear least-squares approximation is incorporated into a similarity measure that considers both Euclidean distance between point pairs (for which dependent vector data are given) and difference in vector values. A modified normalized cut (NC) method is used to obtain a near-optimal clustering of a given discrete vector field ... continued below

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Chen, Jiann-Liang; Bai, Zhaojun; Hamann, Bernd & Ligocki, Terry J. January 13, 2003.

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In the context of vector field data visualization, it is often desirable to construct a hierarchical data representation. One possibility to construct a hierarchy is based on clustering vectors using certain similarity criteria. We combine two fundamental approaches to cluster vectors and construct hierarchical vector field representations. For clustering, a locally constructed linear least-squares approximation is incorporated into a similarity measure that considers both Euclidean distance between point pairs (for which dependent vector data are given) and difference in vector values. A modified normalized cut (NC) method is used to obtain a near-optimal clustering of a given discrete vector field data set. To obtain a hierarchical representation, the NC method is applied to simple, analytically defined vector fields as well as discrete vector field data generated by turbulent flow simulation. Our test results indicate that our proposed adaptation of the original NC method is a promising method as it leads to segmentation results that capture the qualitative and topological nature of the vector field data.

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OSTI as DE00809305

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  • SPIE/IS&T Visual Data Exploration and Analysis, San Jose, CA (US), 01/29/2003

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  • Report No.: LBNL--52025
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 809305
  • Archival Resource Key: ark:/67531/metadc739909

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  • January 13, 2003

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  • Oct. 18, 2015, 6:40 p.m.

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  • April 4, 2016, 1:46 p.m.

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Chen, Jiann-Liang; Bai, Zhaojun; Hamann, Bernd & Ligocki, Terry J. A normalized-cut algorithm for hierarchical vector field data segmentation, article, January 13, 2003; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc739909/: accessed September 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.