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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.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "preview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 580, "image_height": 416, "name": "kouril-2018-LoL-preview.png", "type": "image/png", "size": 528337, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1383, 1246, 1248, 1464, 1379, 1365, 1475, 166, 171 ], "cfp": { "name": "IEEE VIS 2018.pdf", "type": "application/pdf", "error": "0", "size": "91184", "orig_name": "IEEE VIS 2018.pdf", "ext": "pdf" }, "date_from": "2018-11", "date_to": "2018-03", "doi": "10.1109/TVCG.2018.2864491", "event": "IEEE VIS", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 1383 ], "location": "Berlin, Germany", "note": "SciVis Best Paper Honorable Mention", "open_access": "yes", "pages_from": "977", "pages_to": "986", "volume": "25", "research_areas": [], "keywords": [ "labeling", "multi-scale data", "multi-instance data" ], "weblinks": [ { "href": "https://www.youtube.com/watch?v=zqJmJfaLiDw", "caption": "Process video", "description": "Video showing the progress of the implementation of the method described in the paper.", "main_file": 0 }, { "href": "https://vimeo.com/303245396", "caption": "Conference Talk Recording", "description": "Recording of the talk delivered at IEEE VIS 2018 in Berlin", "main_file": 1 } ], "files": [ { "description": "Conference presentation of the paper", "filetitle": "LoL-conference-presentation", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kouril-2018-LoL-LoL-conference-presentation.pptx", "type": "application/vnd.openxmlformats-officedocument.presentationml.presentation", "size": 202678696, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-LoL-conference-presentation.pptx", "thumb_image_sizes": [] }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "kouril-2018-LoL-paper.pdf", "type": "application/pdf", "size": 18362171, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "preview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 580, "image_height": 416, "name": "kouril-2018-LoL-preview.png", "type": "image/png", "size": 528337, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1272, "image_height": 416, "name": "kouril-2018-LoL-teaser.png", "type": "image/png", "size": 1506129, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ "Illustrare", "BioNetIllustration" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/", "__class": "Publication" }, { "id": "Miao2018FDN", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Preview to Adenita: Visualization and Modeling of DNA Nanostructures", "date": "2018-06-08", "abstract": "We present Adenita, an open-source software that aims to provide an integrated in silico\ndesign toolkit for DNA Nanostructures. It facilitates the modular assembly of pre-existing\nand de novo designs, regardless of the used approach. Adenita is being developed in the\ncontext of the MARA project [1], a highly ambitious project aiming to produce a DNA\nnanorobot capable of targeted cell lyses. Currently, the existing design and visualization\ntools are insufficient to solve the specific challenges in our project. We aim to overcome\nthese limitations with Adenita, a new semi-automated approach that we are developing as\nthe MARA project advances. Adenita integrates visualizations [2] with user interactions and\nalgorithms in a semi-manual approach. At the core, we use a hierarchical data model that\nenables us to combine both a top-down (DAEDALUS [3]) and a bottom-up (caDNAno [4])\ndesign approach of the DNA Nanostructure. From the DNA data model, we create smooth\nvisualizations that depict the structure in multiple scales from its atomic details to a highlevel\ngeometric representation of the target shape. In addition, we employ different layouts\nfor the same structure [5]: 3D structural representations, 2D caDNAno-style diagrams, and\n1D display of the linear sequences. Creators enable the parametrized generation of\nstructural motifs, while Manipulators facilitate the advanced modifications of the structural\nproperties, such as connecting components and adding bridging strands. Analysis of the\ndesigns is still in a preliminary phase, but it already enables the straightforward estimation\nof distances and the melting temperatures [6] of binding regions. The first DNA\nnanostructures that we designed with the new tool are now under experimental evaluation.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 857, "image_height": 1242, "name": "Miao2018FDN-image.png", "type": "image/png", "size": 1074408, "path": "Publication:Miao2018FDN", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 1474, 1263, 960, 166, 171, 1473 ], "cfp": { "name": "fdn2018_abstracts.pdf", "type": "application/pdf", "error": "0", "size": "3495981", "orig_name": "fdn2018_abstracts.pdf", "ext": "pdf" }, "date_from": "2018-06-06", 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