Name
Abstract | ||
|---|---|---|
The challenge of tensor field visualization is to provide simple and comprehensible representations of data which vary both directionally and spatially. We explore the use of differential operators to extract features from tensor fields. These features can be used to generate skeleton representations of the data that accurately characterize the global field structure. Previously, vector field operators such as gradient, divergence, and curl have previously been used to visualize of flow fields. In this paper, we use generalizations of these operators to locate and classify tensor field degenerate points and to partition the field into regions of homogeneous behavior. We describe the implementation of our feature extraction and demonstrate our new techniques on synthetic data sets of order 2, 3 and 4. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1155/2011/142923 | JOURNAL OF APPLIED MATHEMATICS |
Keywords | Field | DocType |
feature extraction,differential operators,vector field,synthetic data | Tensor,Tensor (intrinsic definition),Mathematical analysis,Vector calculus identities,Cartesian tensor,Tensor field,Symmetric tensor,Tensor contraction,Curl (mathematics),Mathematics | Journal |
Volume | ISSN | Citations |
2011 | 1110-757X | 1 |
PageRank | References | Authors |
0.37 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tim Mcgraw | 1 | 43 | 10.14 |
| Takamitsu Kawai | 2 | 16 | 4.39 |
| Inas Yassine | 3 | 9 | 1.54 |
| Lierong Zhu | 4 | 3 | 0.76 |