EuroVisSTAR2019

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2632786

Browse

Browsing EuroVisSTAR2019 by Subject "centered computing"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    External Labeling Techniques: A Taxonomy and Survey
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Bekos, Michael A.; Niedermann, Benjamin; Nöllenburg, Martin; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, Michael
    External labeling is frequently used for annotating features in graphical displays and visualizations, such as technical illustrations, anatomical drawings, or maps, with textual information. Such a labeling connects features within an illustration by thin leader lines with their labels, which are placed in the empty space surrounding the image. Over the last twenty years, a large body of literature in diverse areas of computer science has been published that investigates many different aspects, models, and algorithms for automatically placing external labels for a given set of features. This state-of-the-art report introduces a first unified taxonomy for categorizing the different results in the literature and then presents a comprehensive survey of the state of the art, a sketch of the most relevant algorithmic techniques for external labeling algorithms, as well as a list of open research challenges in this multidisciplinary research field.
  • Thumbnail Image
    Item
    A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Ceneda, Davide; Gschwandtner, Theresia; Miksch, Silvia; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, Michael
    Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system-user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some time. However, this problem is still largely unsolved. As a result, users might be overwhelmed by powerful but complex visual analysis systems which also limits their ability to produce insightful results. In this context, guidance is a promising step towards enabling an effective mixed-initiative collaboration to promote the visual analysis. However, the way how guidance should be put into practice is still to be unravelled. Thus, we conducted a comprehensive literature research and provide an overview of how guidance is tackled by different approaches in visual analysis systems. We distinguish between guidance that is provided by the system to support the user, and guidance that is provided by the user to support the system. By identifying open problems, we highlight promising research directions and point to missing factors that are needed to enable the envisioned human-computer collaboration, and thus, promote a more effective visual data analysis.
  • Thumbnail Image
    Item
    State-of-the-art in Multi-Light Image Collections for Surface Visualization and Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Pintus, Ruggero; Dulecha, Tinsae Gebrechristos; Ciortan, Irina Mihaela; Gobbetti, Enrico; Giachetti, Andrea; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, Michael
    Multi-Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up-to-date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications.