@inproceedings{wang14,
TITLE = {Pattern Search in Flows based on Similarity of Stream Line Segments},
AUTHOR = {Wang, Zhongjie and Martinez Esturo, Janick and Seidel, Hans-Peter and Weinkauf, Tino},
LANGUAGE = {eng},
DOI = {10.2312/vmv.20141272},
PUBLISHER = {Eurographics Association},
YEAR = {2014},
DATE = {2014-10},
ABSTRACT = {We propose a method that allows users to define flow features in form<br> of patterns represented as sparse sets of stream line segments. Our<br> approach finds similar occurrences in the same or other time steps.<br> Related approaches define patterns using dense, local stencils or<br> support only single segments. Our patterns are defined sparsely and<br> can have a significant extent, i.e., they are integration-based and<br> not local. This allows for a greater flexibility in defining features<br> of interest. Similarity is measured using intrinsic curve properties<br> only, which enables invariance to location, orientation, and scale.<br> Our method starts with splitting stream lines using globally-consistent<br> segmentation criteria. It strives to maintain the visually apparent<br> features of the flow as a collection of stream line segments. Most<br> importantly, it provides similar segmentations for similar flow structures.<br> For user-defined patterns of curve segments, our algorithm finds<br> similar ones that are invariant to similarity transformations. We<br> showcase the utility of our method using different 2D and 3D flow<br> fields.},
BOOKTITLE = {VMV 2014 Vision, Modeling and Visualization},
DEBUG = {author: von Landesberger, Tatiana; author: Theisel, Holger; author: Urban, Philipp},
EDITOR = {Bender, Jan and Kuijper, Arjan},
PAGES = {23--30},
ADDRESS = {Darmstadt, Germany},
}