Interactive Visual Categorization of Spinel-Group Minerals

Maria Lujan Ganuza, Gabriela Ferracutti, Maria Florencia Gargiulo, Silvia Castro, Ernesto Bjerg, Meister Eduard Gröller, Kresimir Matkovic
Interactive Visual Categorization of Spinel-Group Minerals
In Proceedings of the 33rd Spring Conference on Computer Graphics (SCCG 2017). May 2017.

Information

Abstract

Spinel-group minerals are excellent indicators of geological environments and are of invaluable help in the search for mineral deposits of economic interest. The geologists analyze them by means of Barnes and Roeder’s contours. In this paper, we present a collection of novel, interactive methods, which assist geologists in the categorization of spinel-group minerals. We fully integrate Barnes and Roeder’s contours using a polygonal representation. This makes it possible to efficiently superimpose user-provided point data over the contours, and to automatically rank the contours based on the number of enclosed points. We also allow the expert to create contours for the user-provided point data. Once user contours are created, they can be compared with Barnes and Roeder’s contours. During the analysis, the user can drill-down by means of brushing. As we deal with specific data, we apply two novel brushing techniques, i.e., the percentile brush and the contour brush. The novel brushing mechanisms along with the interactive comparison speed-up the analysis significantly. We evaluate the newly introduced approach and the resulting novel workflow using real-word data from different locations in Argentina. According to the domain experts, the classification of spinel minerals needs several minutes now, while it took a few days with the current state of the art approach in the domain.

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BibTeX

@inproceedings{Ganuza-2017-IVCSGM,
  title =      "Interactive Visual Categorization of Spinel-Group Minerals",
  author =     "Maria Lujan Ganuza and Gabriela Ferracutti and Maria
               Florencia Gargiulo and Silvia Castro and Ernesto Bjerg and
               Meister Eduard Gr{"o}ller and Kresimir Matkovic",
  year =       "2017",
  abstract =   "Spinel-group minerals are excellent indicators of geological
               environments and are of invaluable help in the search for
               mineral deposits of economic interest. The geologists
               analyze them by means of Barnes and Roeder’s contours. In
               this paper, we present a collection of novel, interactive
               methods, which assist geologists in the categorization of
               spinel-group minerals. We fully integrate Barnes and
               Roeder’s contours using a polygonal representation. This
               makes it possible to efficiently superimpose user-provided
               point data over the contours, and to automatically rank the
               contours based on the number of enclosed points. We also
               allow the expert to create contours for the user-provided
               point data. Once user contours are created, they can be
               compared with Barnes and Roeder’s contours. During the
               analysis, the user can drill-down by means of brushing. As
               we deal with specific data, we apply two novel brushing
               techniques, i.e., the percentile brush and the contour
               brush. The novel brushing mechanisms along with the
               interactive comparison speed-up the analysis significantly.
               We evaluate the newly introduced approach and the resulting
               novel workflow using real-word data from different locations
               in Argentina. According to the domain experts, the
               classification of spinel minerals needs several minutes now,
               while it took a few days with the current state of the art
               approach in the domain.",
  month =      may,
  booktitle =  "Proceedings of the 33rd Spring Conference on Computer
               Graphics (SCCG 2017)",
  event =      "33rd Spring Conference on Computer Graphics (SCCG 2017)",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2017/Ganuza-2017-IVCSGM/",
}