Hybrid Touch/Tangible Spatial 3D Data Selection

We discuss spatial selection techniques for three‐dimensional datasets. Such 3D spatial selection is fundamental to exploratory data analysis. While 2D selection is efficient for datasets with explicit shapes and structures, it is less efficient for data without such properties. We first propose a new taxonomy of 3D selection techniques, focusing on the amount of control the user has to define the selection volume. We then describe the 3D spatial selection technique Tangible Brush, which gives manual control over the final selection volume. It combines 2D touch with 6‐DOF 3D tangible input to allow users to perform 3D selections in volumetric data. We use touch input to draw a 2D lasso, extruding it to a 3D selection volume based on the motion of a tangible, spatially‐aware tablet. We describe our approach and present its quantitative and qualitative comparison to state‐of‐the‐art structure‐dependent selection. Our results show that, in addition to being dataset‐independent, Tangible Brush is more accurate than existing dataset‐dependent techniques, thus providing a trade‐off between precision and effort.     

EnergyViz: an interactive system for visualization of energy systems

Energy systems are under pressure to transform to address concerns about climate change. The modeling and visualization of energy systems can play an important role in communicating the costs, benefits and trade-offs of energy systems choices. We introduce EnergyViz, a visualization system that provides an interface for exploring time-varying, multi-attribute and spatial properties of a particular energy system. EnergyViz integrates several visualization techniques to facilitate exploration of a particular energy system. These techniques include flow diagram representation to show energy flow, 3D interaction with flow diagrams for expanding viewable data attributes such as emissions and an interactive map integrated with flow diagrams for simultaneous exploration of spatial and abstract information. We also perform level-of-detail exploration on flow diagrams and use smooth animation across the visualizations to represent time-varying data. Finally, we include evaluation results of EnergyViz collected from expert and inexperienced participants.     

A taxonomy of 3D occlusion management for visualization

While an important factor in depth perception, the occlusion effect in 3D environments also has a detrimental impact on tasks involving discovery, access, and spatial relation of objects in a 3D visualization. A number of interactive techniques have been developed in recent years to directly or indirectly deal with this problem using a wide range of different approaches. In this paper, we build on previous work on mapping out the problem space of 3D occlusion by defining a taxonomy of the design space of occlusion management techniques in an effort to formalize a common terminology and theoretical framework for this class of interactions. We classify a total of 50 different techniques for occlusion management using our taxonomy and then go on to analyze the results, deriving a set of five orthogonal design patterns for effective reduction of 3D occlusion. We also discuss the "gaps" in the design space, areas of the taxonomy not yet populated with existing techniques, and use these to suggest future research directions into occlusion management.     

Survey of glyph-based visualization techniques for spatial multivariate medical data

In this survey article, we review glyph-based visualization techniques that have been exploited when visualizing spatial multivariate medical data. To classify these techniques, we derive a taxonomy of glyph properties that is based on classification concepts established in information visualization. Considering both the glyph visualization as well as the interaction techniques that are employed to generate or explore the glyph visualization, we are able to classify glyph techniques into two main groups: those supporting pre-attentive and those supporting attentive processing. With respect to this classification, we review glyph-based techniques described in the medical visualization literature. Based on the outcome of the literature review, we propose design guidelines for glyph visualizations in the medical domain.     

Hand pose estimation and tracking in real and virtual interaction:A review

Vision-based 3D hand tracking is a key and popular component for interaction studies in a broad range of domains such as virtual reality (VR), augmented reality (AR) and natural human-computer interaction (HCI). While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the surrounding environment. Even the common collaborative and strong interactions with the other hand have been ignored. However, many of today's computer applications require more and more hand-object interactions. Furthermore, employing contextual information about the object in the hand (e.g. the shape, the texture, and the pose) can remarkably constrain the tracking problem. The most studied contextual constraints involve interaction with real objects and not with virtual objects which is still a very big challenge. The goal of this survey is to develop an up-to-date taxonomy of the state-of-the-art vision-based hand pose estimation and tracking methods with a new classification scheme: hand-object interaction constraints. This taxonomy allows us to examine the strengths and weaknesses of the current state of the art and to highlight future trends in the domain.     

A Survey of Visual Analytics for Public Health

We describe visual analytics solutions aiming to support public health professionals, and thus, preventive measures. Prevention aims at advocating behaviour and policy changes likely to improve human health. Public health strives to limit the outbreak of acute diseases as well as the reduction of chronic diseases and injuries. For this purpose, data are collected to identify trends in human health, to derive hypotheses, e.g. related to risk factors, and to get insights in the data and the underlying phenomena. Most public health data have a temporal character. Moreover, the spatial character, e.g. spatial clustering of diseases, needs to be considered for decision-making. Visual analytics techniques involve (subspace) clustering, interaction techniques to identify relevant subpopulations, e.g. being particularly vulnerable to diseases, imputation of missing values, visual queries as well as visualization and interaction techniques for spatio-temporal data. We describe requirements, tasks and visual analytics techniques that are widely used in public health before going into detail with respect to applications. These include outbreak surveillance and epidemiology research, e.g. cancer epidemiology. We classify the solutions based on the visual analytics techniques employed. We also discuss gaps in the current state of the art and resulting research opportunities in a research agenda to advance visual analytics support in public health.     

A Survey on Multimodal Medical Data Visualization

Multi‐modal data of the complex human anatomy contain a wealth of information. To visualize and explore such data, techniques for emphasizing important structures and controlling visibility are essential. Such fused overview visualizations guide physicians to suspicious regions to be analysed in detail, e.g. with slice‐based viewing. We give an overview of state of the art in multi‐modal medical data visualization techniques. Multi‐modal medical data consist of multiple scans of the same subject using various acquisition methods, often combining multiple complimentary types of information. Three‐dimensional visualization techniques for multi‐modal medical data can be used in diagnosis, treatment planning, doctor–patient communication as well as interdisciplinary communication. Over the years, multiple techniques have been developed in order to cope with the various associated challenges and present the relevant information from multiple sources in an insightful way. We present an overview of these techniques and analyse the specific challenges that arise in multi‐modal data visualization and how recent works aimed to solve these, often using smart visibility techniques. We provide a taxonomy of these multi‐modal visualization applications based on the modalities used and the visualization techniques employed. Additionally, we identify unsolved problems as potential future research directions.     

3DGIS中空间数据可视化的研究与应用

空间数据可视化是当前3DGIS领域的研究热点之一。提出了一种面向对象的空间数据可视化模型,基于金字塔模型来组织和调度DEM（数字高程模型）、DOM（数字正射影像）等栅格数据,并引入矢量数据参数化3D建模思想,实现了矢量地物数据的三维建模与可视化。在此基础上,借助虚拟现实技术,基于OpenGL实现了一个3DGIS原型系统,具备空间数据的真实感可视化表达、3D场景实时漫游、交互查询等功能。最后给出了基于该原型系统为军事与民用领域开发的应用实例。     

3D segmentation of abdominal CT imagery with graphical models,conditional random fields and learning

Probabilistic graphical models have had a tremendous impact in machine learning and approaches based on energy function minimization via techniques such as graph cuts are now widely used in image segmentation. However, the free parameters in energy function-based segmentation techniques are often set by hand or using heuristic techniques. In this paper, we explore parameter learning in detail. We show how probabilistic graphical models can be used for segmentation problems to illustrate Markov random fields (MRFs), their discriminative counterparts conditional random fields (CRFs) as well as kernel CRFs. We discuss the relationships between energy function formulations, MRFs, CRFs, hybrids based on graphical models and their relationships to key techniques for inference and learning. We then explore a series of novel 3D graphical models and present a series of detailed experiments comparing and contrasting different approaches for the complete volumetric segmentation of multiple organs within computed tomography imagery of the abdominal region. Further, we show how these modeling techniques can be combined with state of the art image features based on histograms of oriented gradients to increase segmentation performance. We explore a wide variety of modeling choices, discuss the importance and relationships between inference and learning techniques and present experiments using different levels of user interaction. We go on to explore a novel approach to the challenging and important problem of adrenal gland segmentation. We present a 3D CRF formulation and compare with a novel 3D sparse kernel CRF approach we call a relevance vector random field. The method yields state of the art performance and avoids the need to discretize or cluster input features. We believe our work is the first to provide quantitative comparisons between traditional MRFs with edge-modulated interaction potentials and CRFs for multi-organ abdominal segmentation and the first to explore the 3D adrenal gland segmentation problem. Finally, along with this paper we provide the labeled data used for our experiments to the community.     

Visualization of Eye Tracking Data: A Taxonomy and Survey

This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state‐of‐the‐art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point‐based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.     

State of the Art Report on Video‐Based Graphics and Video Visualization

In recent years, a collection of new techniques which deal with video as input data, emerged in computer graphics and visualization. In this survey, we report the state of the art in video‐based graphics and video visualization. We provide a review of techniques for making photo‐realistic or artistic computer‐generated imagery from videos, as well as methods for creating summary and/or abstract visual representations to reveal important features and events in videos. We provide a new taxonomy to categorize the concepts and techniques in this newly emerged body of knowledge. To support this review, we also give a concise overview of the major advances in automated video analysis, as some techniques in this field (e.g. feature extraction, detection, tracking and so on) have been featured in video‐based modelling and rendering pipelines for graphics and visualization.     

Interactive exploration of uncertainty in fuzzy classifications by isosurface visualization of class clusters

Uncertainty and vagueness are important concepts when dealing with transition zones between vegetation communities or land-cover classes. In this study, classification uncertainty is quantified by applying a supervised fuzzy classification algorithm. New visualization techniques are proposed and presented in order to come to a better understanding of the relationship between uncertainty in the spatial extent of image classes and their thematic uncertainty. The thematic extent of a class is visualized as a three-dimensional (3D) class cluster shape in a feature-space plot, and the spatial extent of the class is highlighted in an image display based on a user-defined uncertainty threshold. Changing this threshold updates both visualizations, showing the effect of uncertainty on the spatial extent of a class and its shape in feature space. Spheres, ellipsoids, convex hulls, α-shapes and isosurfaces are compared for visualization of 3D class clusters. Isosurfaces are implemented to facilitate real-time rendering and interaction with class clusters in feature space. The visualization tool is illustrated with a fuzzy classification of a Quickbird image of Macquarie Island, one of the unique sub-Antarctic World Heritage Areas that is characterized by vegetation transition zones. This study shows that visualization techniques are valuable for the interpretation and exploration of image classification results and associated uncertainty.     

A Survey of Flattening‐Based Medical Visualization Techniques

In many areas of medicine, visualization research can help with task simplification, abstraction or complexity reduction. A common visualization approach is to facilitate parameterization techniques which flatten a usually 3D object into a 2D plane. Within this state of the art report (STAR), we review such techniques used in medical visualization and investigate how they can be classified with respect to the handled data and the underlying tasks. Many of these techniques are inspired by mesh parameterization algorithms which help to project a triangulation in ?³ to a simpler domain in ?². It is often claimed that this makes complex structures easier to understand and compare by humans and machines. Within this STAR we review such flattening techniques which have been developed for the analysis of the following medical entities: the circulation system, the colon, the brain, tumors, and bones. For each of these five application scenarios, we have analyzed the tasks and requirements, and classified the reviewed techniques with respect to a developed coding system. Furthermore, we present guidelines for the future development of flattening techniques in these areas.     

3D/4DGIS/TGIS现状研究及其发展动态

3D-GIS是目前GIS界最热门的研究项目之一,论文从三维数据获取方式、三维数据模型和结构、三维可视化和三维空间分析等几个方面的研究现状进行评述;在此基础上描述了4DGIS/TGIS的特征、相关技术和发展前景;最后对3D/4DGIS在未来发展中面临的问题进行了探讨。     

Generation and Visual Exploration of Medical Flow Data: Survey,Research Trends and Future Challenges

Simulations and measurements of blood and airflow inside the human circulatory and respiratory system play an increasingly important role in personalized medicine for prevention, diagnosis and treatment of diseases. This survey focuses on three main application areas. (1) Computational fluid dynamics (CFD) simulations of blood flow in cerebral aneurysms assist in predicting the outcome of this pathologic process and of therapeutic interventions. (2) CFD simulations of nasal airflow allow for investigating the effects of obstructions and deformities and provide therapy decision support. (3) 4D phase‐contrast (4D PC) magnetic resonance imaging of aortic haemodynamics supports the diagnosis of various vascular and valve pathologies as well as their treatment. An investigation of the complex and often dynamic simulation and measurement data requires the coupling of sophisticated visualization, interaction and data analysis techniques. In this paper, we survey the large body of work that has been conducted within this realm. We extend previous surveys by incorporating nasal airflow, addressing the joint investigation of blood flow and vessel wall properties and providing a more fine‐granular taxonomy of the existing techniques. From the survey, we extract major research trends and identify open problems and future challenges. The survey is intended for researchers interested in medical flow but also more general, in the combined visualization of physiology and anatomy, the extraction of features from flow field data and feature‐based visualization, the visual comparison of different simulation results and the interactive visual analysis of the flow field and derived characteristics.     

A multimodal virtual reality interface for 3D interaction with VTK

The object-oriented visualization Toolkit (VTK) is widely used for scientific visualization. VTK is a visualization library that provides a large number of functions for presenting three-dimensional data. Interaction with the visualized data is controlled with two-dimensional input devices, such as mouse and keyboard. Support for real three-dimensional and multimodal input is non-existent. This paper describes VR-VTK: a multimodal interface to VTK on a virtual environment. Six degree of freedom input devices are used for spatial 3D interaction. They control the 3D widgets that are used to interact with the visualized data. Head tracking is used for camera control. Pedals are used for clutching. Speech input is used for application commands and system control. To address several problems specific for spatial 3D interaction, a number of additional features, such as more complex interaction methods and enhanced depth perception, are discussed. Furthermore, the need for multimodal input to support interaction with the visualization is shown. Two existing VTK applications are ported using VR-VTK to run in a desktop virtual reality system. Informal user experiences are presented. Arjan J. F. Kok is an assistant professor at the Department of Computer Science at the Open University of the Netherlands. He studied Computer Science at the Delft University of Technology, The Netherlands. He received his Ph.D. from the same university. He worked as a Scientist for TNO (Netherlands Organization for Applied Scientific Research) and as assistant professor at the Eindhoven University of Technology before he joined the Open University. His research interests are visualization, virtual reality, and computer graphics. Robert van Liere studied Computer Science at the Delft University of Technology, the Netherlands. He received his Ph.D. with the thesis “Studies in Interactive Scientific Visualization” at the University of Amsterdam. Since 1985, he has worked at CWI, the Center for Mathematics and Computer Science in Amsterdam in which he is the head of CWI’s visualization research group. Since 2004, he holds a part-time position as full professor at the Eindhoven University of Technology. His research interests are in interactive data visualization and virtual reality. He is a member of IEEE.     

Visual Analysis of Biomolecular Cavities: State of the Art

In this report we review and structure the branch of molecular visualization that is concerned with the visual analysis of cavities in macromolecular protein structures. First the necessary background, the domain terminology, and the goals of analytical reasoning are introduced. Based on a comprehensive collection of relevant research works, we present a novel classification for cavity detection approaches and structure them into four distinct classes: grid‐based, Voronoi‐based, surface‐based, and probe‐based methods. The subclasses are then formed by their combinations. We match these approaches with corresponding visualization technologies starting with direct 3D visualization, followed with non‐spatial visualization techniques that for example abstract the interactions between structures into a relational graph, straighten the cavity of interest to see its profile in one view, or aggregate the time sequence into a single contour plot. We also discuss the current state of methods for the visual analysis of cavities in dynamic data such as molecular dynamics simulations. Finally, we give an overview of the most common tools that are actively developed and used in the structural biology and biochemistry research. Our report is concluded by an outlook on future challenges in the field.     

Advances in Interaction with 3D Environments

Various interaction techniques have been developed for interactive 3D environments. This paper presents an up‐to‐date and comprehensive review of the state of the art of non‐immersive interaction techniques for Navigation, Selection & Manipulation, and System Control, including a basic introduction to the topic, the challenges and an examination of a number of popular approaches. We also introduce 3D Interaction Testbed (3DIT) to firstly allow a ‘hands‐on' understanding of 3D interaction principles, and secondly to create an open platform for defining evaluation methods, stimuli as well as representative tasks akin to those found in other disciplines of science. We hope that this survey can aid both researchers and developers of interactive 3D applications in having a clearer overview of the topic and in particular can be useful for practitioners and researchers that are new to the field of interactive 3D graphics.     

behaviorism: a framework for dynamic data visualization

While a number of information visualization software frameworks exist, creating new visualizations, especially those that involve novel visualization metaphors, interaction techniques, data analysis strategies, and specialized rendering algorithms, is still often a difficult process. To facilitate the creation of novel visualizations we present a new software framework, behaviorism, which provides a wide range of flexibility when working with dynamic information on visual, temporal, and ontological levels, but at the same time providing appropriate abstractions which allow developers to create prototypes quickly which can then easily be turned into robust systems. The core of the framework is a set of three interconnected graphs, each with associated operators: a scene graph for high-performance 3D rendering, a data graph for different layers of semantically linked heterogeneous data, and a timing graph for sophisticated control of scheduling, interaction, and animation. In particular, the timing graph provides a unified system to add behaviors to both data and visual elements, as well as to the behaviors themselves. To evaluate the framework we look briefly at three different projects all of which required novel visualizations in different domains, and all of which worked with dynamic data in different ways: an interactive ecological simulation, an information art installation, and an information visualization technique.