Pregled bibliografske jedinice broj: 958568
Interactive visual categorization of spinel-group minerals
Interactive visual categorization of spinel-group minerals // Proceedings of the 33rd Spring Conference on Computer Graphics
Mikulov, Češka Republika: The Association for Computing Machinery (ACM), 2017. 18, 11 doi:10.1145/3154353.3154359 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 958568 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Interactive visual categorization of spinel-group minerals
Autori
Ganuza, M. L. ; Ferracutti, G. ; Gargiulo, F. ; Castro, S. M. ; Bjerg, E. A. ; Gröller, E. ; Matković, K.
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 33rd Spring Conference on Computer Graphics
/ - : The Association for Computing Machinery (ACM), 2017
ISBN
978-1-4503-5107-2
Skup
33rd Spring Conference on Computer Graphics
Mjesto i datum
Mikulov, Češka Republika, 15.05.2017. - 17.05.2017
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
interaction techniques, interactive classification, spinel mineral analysis, visual analytics
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
