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"title": "Illustrative Motion Smoothing for Attention Guidance in Dynamic Visualizations",
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"abstract": "3D animations are an effective method to learn about complex dynamic phenomena, such as mesoscale biological processes. The animators’ goals are to convey a sense of the scene’s overall complexity while, at the same time, visually guiding the user through a story of subsequent events embedded in the chaotic environment. Animators use a variety of visual emphasis techniques to guide the observers’ attention through the story, such as highlighting, halos – or by manipulating motion parameters of the scene. In this paper, we investigate the effect of smoothing the motion of contextual scene elements to attract attention to focus elements of the story exhibiting high-frequency motion. We conducted a crowdsourced study with 108 participants observing short animations with two illustrative motion smoothing strategies: geometric smoothing through noise reduction of contextual motion trajectories and visual smoothing through motion blur of context items. We investigated the observers’ ability to follow the story as well as the effect of the techniques on speed perception in a molecular scene. Our results show that moderate motion blur significantly improves users’ ability to follow the story. Geometric motion smoothing is less effective but increases the visual appeal of the animation. However, both techniques also slow down the perceived speed of the animation. We discuss the implications of these results and derive design guidelines for animators of complex dynamic visualizations.",
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"event": "EuroVis 2023",
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"abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n",
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"byska-2019-mdfc",
"cellVIEW_2015",
"cmolik-2020-tvcg",
"Dietrich_1",
"dietrich-2016-viseq2",
"Ehlers_PhD",
"eschner-2023-ims",
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"kouril-2021-phdthesis",
"Kozlikova-Visualization-2016b",
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"lemuzic_2015_timelapse",
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"manylands_award",
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"raidou_2019_springer",
"raidou_shonan167",
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"rasch-2016-imgses",
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"sturl_2016_dynlabels",
"trautner-2018-imd",
"unger-2019_vcp",
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"Viola_Ivan_2015_MCT",
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"Viola_Ivan_CLD",
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"Weissenboeck_2019",
"wu-2017-dagstuhl",
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"wu-2018-story",
"wu-2019-bmc",
"wu-2019-report",
"wu-2019-vcbm",
"wu-2019-visworkshop",
"wu-2020-tvcg"
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"Illustrare",
"illvisation"
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"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis",
"__class": "ResearchArea"
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"name": "Illustrative Visualization",
"short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.",
"abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.",
"website": "https://www.cg.tuwien.ac.at/research/area/IllVis",
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"Bayat_2019",
"Bechtold2020",
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"horvath-2018-ism",
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"Koeppel2020",
"kolesar-ivan-2014-polymers",
"Konev-FCV2018",
"Koszticsak-2017-ewt",
"Kouril_2017_11",
"kouril-2020-hyperlabels",
"kouril-2021-molecumentary",
"kouril-2021-phdthesis",
"kroesl_x_card_2017",
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"Langer_Edith_IR1",
"lawonn-2018-illvisstar",
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"szabo_patrik-2022-tour",
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"TR-186-2-07-08",
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"Viola_Ivan_CLD",
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"wu-2019-bmc",
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"zechmeister2020",
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"title": "Visualization working group at TU Wien: Visibile Facimus Quod Ceteri Non Possunt",
"date": "2021-03",
"abstract": "Building-up and running a university-based research group is a multi-faceted undertaking. The visualization working group at TU Wien (vis-group) has been internationally active over more than 25 years. The group has been acting in a competitive scientific setting where sometimes contradicting multiple objectives require trade-offs and optimizations. Research-wise the group has been performing basic and applied research in visualization and visual computing. Teaching-wise the group has been involved in undergraduate and graduate lecturing in (medical) visualization and computer graphics. To be scientifically competitive requires to constantly expose the group and its members to a strong international competition at the highest level. This necessitates to shield the members against the ensuing pressures and demands and provide (emotional) support and encouragement. Internally, the vis-group has developed a unique professional and social interaction culture: work and celebrate, hard and together. This has crystallized into a nested, recursive, and triangular organization model, which concretizes what it takes to make a research group successful. The key elements are the creative and competent vis-group members who collaboratively strive for (scientific) excellence in a socially enjoyable environment.",
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"abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n",
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"abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
"website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
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{
"id": "Rendering",
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"name": "Rendering",
"short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.",
"abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.",
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"d9259",
"d9275",
"Desiree",
"EVOCATION",
"GameTools",
"GPV",
"Harvest4D",
"Mofa",
"OpenData",
"PathSpace",
"REPLICATE",
"RESHADE",
"Scanopy",
"TERAPOINTS",
"Treelumination"
],
"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering",
"__class": "ResearchArea"
}
],
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"short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.",
"abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.",
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"title": "Interactive Integrated Exploration and Management of Visualization Parameters",
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"abstract": "Visualization algorithms are parameterized to offer universality in terms of handling various data types, showing different aspects of the visualized data, or producing results useful for domain experts from different fields. Hence, input parameters are an important aspect of the visualization process. Their exploration and management are tasks which enable the visualization reusability, portability, and interdisciplinary communication.\n\nWith increasing availability of visualization systems, which are suitable for a great variety of tasks, their complexity increases as well. This usually involves many input parameters necessary for the meaningful visualization of data. Multiple input parameters form parameter spaces which are too large to be explored by brute-force. Knowing the properties of a parameter space is often beneficial for improving data visualization. Therefore, it is important for domain experts utilizing data visualization to have tools for automatic parameter specification and for aiding the manual parameter setting.\n\nIn this thesis, we review existing approaches for parameter-space visualization, exploration, and management. These approaches are used with a great variety of underlying algorithms. We focus on their applicability to visualization algorithms. We propose three methods solving specific problems arising from the fact that the output of a visualization algorithm is an image, which is challenging to process automatically and often needs to be analyzed by a human.\n\nFirst, we propose a method for the exploration of parameter-spaces of visualization algorithms. The method is used to understand effects of combinations of parameters and parts of the internal structure of the visualization algorithms on the final image result. The exploration is carried out by specifying semantics for localized parts of the visualization images in the form of positive and negative examples influenced by a set of input parameters or parts of the visualization algorithm itself. After specifying the localized semantics, global effects of the specified components of the visualization algorithm can be observed. The method itself is independent from the underlying algorithm.\n\nSubsequently, we present a method for managing image-space selections in visualizations and automatically link them with the context in which they were created. The context is described by the values of the visualization parameters influencing the output image. The method contains a mechanism for linking additional views to the selections, allowing the user an effective management of the visualization parameters whose effects are localized to certain areas of the visualizations. We present various applications for the method, as well as an implementation in the form of a library, which is ready to be used in existing visualization systems.\n\nOur third method is designed to integrate dynamic parameters stored during a multiplayer video game session by the individual participating players. For each player, the changing parameter values of the game describe their view of the gameplay. Integrating these multiple views into a single continuous visual narrative provides means for effective summarization of gameplays, useful for entertainment, or even gameplay analysis purposes by semi-professional or professional players. We demonstrate the utility of our approach on an existing video game by producing a gameplay summary of a multiplayer game session. The proposed method opens possibilities for further research in the areas of storytelling, or at a more abstract level, parameter integration for visual computing algorithms.\n",
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"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis",
"__class": "Workgroup"
}
],
"url": "https://www.cg.tuwien.ac.at/research/publications/2013/karimov-2013-vivisection/",
"__class": "Publication"
},
{
"id": "mindek-2013-csl",
"type_id": "inproceedings",
"tu_id": null,
"repositum_id": null,
"title": "Contextual Snapshots: Enriched Visualization with Interactive Spatial Annotations",
"date": "2013-05",
"abstract": "Spatial selections are a ubiquitous concept in visualization. By localizing particular features, they can be analyzed and compared in different views. However, the semantics of such selections are often dependent on other parameter settings and it can be difficult to reconstruct them without additional information. In this paper, we present the concept of contextual snapshots as an effective means for managing spatial selections in visualized data. The selections are automatically associated with the context in which they have been created. Contextual snapshots can be also used as the basis for interactive integrated and linked views, which enable in-place investigation and comparison of multiple visual representations of data. Our approach is implemented as a flexible toolkit with welldefined interfaces for integration into existing systems. We demonstrate the power and generality of our techniques by applying them to several distinct scenarios such as the visualization of simulation data and the analysis of historical documents.",
"authors_et_al": false,
"substitute": null,
"main_image": {
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"short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.",
"abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.",
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