KOUŘIL, David, Ladislav ČMOLÍK, Barbora KOZLÍKOVÁ, Hsiang-Yun WU, Graham JOHNSON, David S. GOODSELL, Arthur OLSON, Eduard M. GROELLER a Ivan VIOLA. Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments. IEEE Transactions on Visualization and Computer Graphics. 2019, roč. 25, č. 1, s. 977-986. ISSN 1077-2626. doi:10.1109/TVCG.2018.2864491.
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Základní údaje
Originální název Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments
Autoři KOUŘIL, David (203 Česká republika), Ladislav ČMOLÍK (203 Česká republika), Barbora KOZLÍKOVÁ (203 Česká republika, domácí), Hsiang-Yun WU, Graham JOHNSON (840 Spojené státy), David S. GOODSELL (840 Spojené státy), Arthur OLSON (840 Spojené státy), Eduard M. GROELLER (40 Rakousko) a Ivan VIOLA (703 Slovensko, garant).
Vydání IEEE Transactions on Visualization and Computer Graphics, 2019, 1077-2626.
Další údaje
Originální jazyk angličtina
Typ výsledku Článek v odborném periodiku
Obor 10200 1.2 Computer and information sciences
Stát vydavatele Spojené státy
Utajení není předmětem státního či obchodního tajemství
WWW URL
Impakt faktor Impact factor: 4.558
Kód RIV RIV/00216224:14330/19:00108862
Organizační jednotka Fakulta informatiky
Doi http://dx.doi.org/10.1109/TVCG.2018.2864491
UT WoS 000452640000093
Klíčová slova anglicky labeling;multi-scale;multi-scale;molecular visualization
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnil: RNDr. Pavel Šmerk, Ph.D., učo 3880. Změněno: 13. 4. 2020 23:04.
Anotace
Labeling is intrinsically important for exploring and understanding complex environments and models in a variety of domains. We present a method for interactive labeling of crowded 3D scenes containing very many instances of objects spanning multiple scales in size. In contrast to previous labeling methods, we target cases where many instances of dozens of types are present and where the hierarchical structure of the objects in the scene presents an opportunity to choose the most suitable level for each placed label. Our solution builds on and goes beyond labeling techniques in medical 3D visualization, cartography, and biological illustrations from books and prints. In contrast to these techniques, the main characteristics of our new technique are: 1) a novel way of labeling objects as part of a bigger structure when appropriate, 2) visual clutter reduction by labeling only representative instances for each type of an object, and a strategy of selecting those. The appropriate level of label is chosen by analyzing the scene's depth buffer and the scene objects' hierarchy tree. We address the topic of communicating the parent-children relationship between labels by employing visual hierarchy concepts adapted from graphic design. Selecting representative instances considers several criteria tailored to the character of the data and is combined with a greedy optimization approach. We demonstrate the usage of our method with models from mesoscale biology where these two characteristics—multi-scale and multi-instance—are abundant, along with the fact that these scenes are extraordinarily dense.
Návaznosti
MUNI/M/0822/2015, interní kód MUNázev: Expressive Visualization of Protein Complexes
Investor: Masarykova univerzita, Expressive Visualization of Protein Complexes, INTERDISCIPLINARY - Mezioborové výzkumné projekty
VytisknoutZobrazeno: 19. 3. 2024 06:45