Automatic Animation for Time‐Varying Data Visualization

This paper presents a digital storytelling approach that generates automatic animations for time‐varying data visualization. Our approach simulates the composition and transition of storytelling techniques and synthesizes animations to describe various event features. Specifically, we analyze information related to a given event and abstract it as an event graph, which represents data features as nodes and event relationships as links. This graph embeds a tree‐like hierarchical structure which encodes data features at different scales. Next, narrative structures are built by exploring starting nodes and suitable search strategies in this graph. Different stages of narrative structures are considered in our automatic rendering parameter decision process to generate animations as digital stories. We integrate this animation generation approach into an interactive exploration process of time‐varying data, so that more comprehensive information can be provided in a timely fashion. We demonstrate with a storm surge application that our approach allows semantic visualization of time‐varying data and easy animation generation for users without special knowledge about the underlying visualization techniques.     

Geometry‐driven Visualization of Microscopic Structures in Biology

At a microscopic resolution, biological structures are composed of cells, red blood corpuscles (RBCs), cytoplasm and other microstructural components. There is a natural pattern in terms of distribution, arrangement and packing density of these components in biological organization. In this work, we propose to use N‐point correlation functions to guide the analysis and exploration process in microscopic datasets. These functions provide useful feature spaces to aid segmentation and visualization tasks. We show 3D visualizations of mouse placenta tissue layers and mouse mammary ducts as well as 2D segmentation/tracking of clonal populations. Further confidence in our results stems from validation studies that were performed with manual ground‐truth for segmentation.     

From Web Data to Visualization via Ontology Mapping

In this paper, we propose a novel approach for automatic generation of visualizations from domain‐specific data available on the web. We describe a general system pipeline that combines ontology mapping and probabilistic reasoning techniques. With this approach, a web page is first mapped to a Domain Ontology, which stores the semantics of a specific subject domain (e.g., music charts). The Domain Ontology is then mapped to one or more Visual Representation Ontologies, each of which captures the semantics of a visualization style (e.g., tree maps). To enable the mapping between these two ontologies, we establish a Semantic Bridging Ontology, which specifies the appropriateness of each semantic bridge. Finally each Visual Representation Ontology is mapped to a visualization using an external visualization toolkit. Using this approach, we have developed a prototype software tool, SemViz, as a realisation of this approach. By interfacing its Visual Representation Ontologies with public domain software such as ILOG Discovery and Prefuse, SemViz is able to generate appropriate visualizations automatically from a large collection of popular web pages for music charts without prior knowledge of these web pages.     

Modal Locomotion: Animating Virtual Characters with Natural Vibrations

We present a general method to intuitively create a wide range of locomotion controllers for 3D legged characters. The key of our approach is the assumption that efficient locomotion can exploit the natural vibration modes of the body, where these modes are related to morphological parameters such as the shape, size, mass, and joint stiffness. The vibration modes are computed for a mechanical model of any 3D character with rigid bones, elastic joints, and additional constraints as desired. A small number of vibration modes can be selected with respect to their relevance to locomotion patterns and combined into a compact controller driven by very few parameters. We show that these controllers can be used in dynamic simulations of simple creatures, and for kinematic animations of more complex creatures of a variety of shapes and sizes.     

Distributed and Collaborative Visualization

Visualization is a powerful tool for analyzing data and presenting results in science, engineering and medicine. This paper reviews ways in which it can be used in distributed and/or collaborative environments. Distributed visualization addresses a number of resource allocation problems, including the location of processing close to data for the minimization of data traffic. The advent of the Grid Computing paradigm and the link to Web Services provides fresh challenges and opportunities for distributed visualization—including the close coupling of simulations and visualizations in a steering environment. Recent developments in collaboration have seen the growth of specialized facilities (such as Access Grid) which have supplemented traditional desktop video conferencing using the Internet and multicast communications. Collaboration allows multiple users—possibly at remote sites—to take part in the visualization process at levels which range from the viewing of images to the shared control of the visualization methods. In this review, we present a model framework for distributed and collaborative visualization and assess a selection of visualization systems and frameworks for their use in a distributed or collaborative environment. We also discuss some examples of enabling technology and review recent work from research projects in this field.     

Interactive Visualization of Function Fields by Range-Space Segmentation

We present a dimension reduction and feature extraction method for the visualization and analysis of function field data. Function fields are a class of high-dimensional, multi-variate data in which data samples are one-dimensional scalar functions. Our approach focuses upon the creation of high-dimensional range-space segmentations, from which we can generate meaningful visualizations and extract separating surfaces between features. We demonstrate our approach on high-dimensional spectral imagery, and particulate pollution data from air quality simulations.     

Automatic Registration of Multi‐Projector Domes Using a Single Uncalibrated Camera

In this paper we present a novel technique for easily calibrating multiple casually aligned projectors on spherical domes using a single uncalibrated camera. Using the prior knowledge of the display surface being a dome, we can estimate the camera intrinsic and extrinsic parameters and the projector to display surface correspondences automatically using a set of images. These images include the image of the dome itself and a projected pattern from each projector. Using these correspondences we can register images from the multiple projectors on the dome. Further, we can register displays which are not entirely visible in a single camera view using multiple pan and tilted views of an uncalibrated camera making our method suitable for displays of different size and resolution. We can register images from any arbitrary viewpoint making it appropriate for a single head‐tracked user in a 3D visualization system. Also, we can use several cartographic mapping techniques to register images in a manner that is appropriate for multi‐user visualization. Domes are known to produce a tremendous sense of immersion and presence in visualization systems. Yet, till date, there exists no easy way to register multiple projectors on a dome to create a high‐resolution realistic visualizations. To the best of our knowledge, this is the first method that can achieve accurate geometric registration of multiple projectors on a dome simply and automatically using a single uncalibrated camera.     

Visualization Mosaics for Multivariate Visual Exploration

We present a new model for creating composite visualizations of multidimensional data sets using simple visual representations such as point charts, scatterplots and parallel coordinates as components. Each visual representation is contained in a tile, and the tiles are arranged in a mosaic of views using a space‐filling slice‐and‐dice layout. Tiles can be created, resized, split or merged using a versatile set of interaction techniques, and the visual representation of individual tiles can also be dynamically changed to another representation. Because each tile is self‐contained and independent, it can be implemented in any programming language, on any platform and using any visual representation. We also propose a formalism for expressing visualization mosaics. A Web‐based implementation called MosaicJS supporting multidimensional visual exploration showcases the versatility of the concept and illustrates how it can be used to integrate visualization components provided by different toolkits.     

Dynamic Multi‐View Exploration of Shape Spaces

Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model models the distribution in a high dimensional shape space, where each shape is represented by a single point. We present a design study on the intuitive exploration and visualization of shape spaces and shape models. Our approach focuses on the dual‐space nature of these spaces. The high‐dimensional shape space represents the population, whereas object space represents the shape of the 3D object associated with a point in shape space. A 3D object view provides local details for a single shape. The high dimensional points in shape space are visualized using a 2D scatter plot projection, the axes of which can be manipulated interactively. This results in a dynamic scatter plot, with the further extension that each point is visualized as a small version of the object shape that it represents. We further enhance the population‐object duality with a new type of view aimed at shape comparison. This new “shape evolution view” visualizes shape variability along a single trajectory in shape space, and serves as a link between the two spaces described above. Our three‐view exploration concept strongly emphasizes linked interaction between all spaces. Moving the cursor over the scatter plot or evolution views, shapes are dynamically interpolated and shown in the object view. Conversely, camera manipulation in the object view affects the object visualizations in the other views. We present a GPU‐accelerated implementation, and show the effectiveness of the three‐view approach using a number of real‐world cases. In these, we demonstrate how this multi‐view approach can be used to visually explore important aspects of a statistical shape model, including specificity, compactness and reconstruction error.     

Illustrative Parallel Coordinates

Illustrative parallel coordinates (IPC) is a suite of artistic rendering techniques for augmenting and improving parallel coordinate (PC) visualizations. IPC techniques can be used to convey a large amount of information about a multidimensional dataset in a small area of the screen through the following approaches: (a) edge‐bundling through splines; (b) visualization of “branched ” clusters to reveal the distribution of the data; (c) opacity‐based hints to show cluster density; (d) opacity and shading effects to illustrate local line density on the parallel axes; and (e) silhouettes, shadows and halos to help the eye distinguish between overlapping clusters. Thus, the primary goal of this work is to convey as much information as possible in a manner that is aesthetically pleasing and easy to understand for non‐experts.     

Layered Performance Animation with Correlation Maps

Performance has a spontaneity and “aliveness” that can be difficult to capture in more methodical animation processes such as keyframing. Access to performance animation has traditionally been limited to either low degree of freedom characters or required expensive hardware. We present a performance-based animation system for humanoid characters that requires no special hardware, relying only on mouse and keyboard input. We deal with the problem of controlling such a high degree of freedom model with low degree of freedom input through the use of correlation maps which employ 2D mouse input to modify a set of expressively relevant character parameters. Control can be continuously varied by rapidly switching between these maps. We present flexible techniques for varying and combining these maps and a simple process for defining them. The tool is highly configurable, presenting suitable defaults for novices and supporting a high degree of customization and control for experts. Animation can be recorded on a single pass, or multiple layers can be used to increase detail. Results from a user study indicate that novices are able to produce reasonable animations within their first hour of using the system. We also show more complicated results for walking and a standing character that gestures and dances.     

GuideME: Slice‐guided Semiautomatic Multivariate Exploration of Volumes

Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State‐of‐the‐art tools allow users to interactively explore volumes with multiple linked parameter‐space views. However, interactions in the parameter space using trial‐and‐error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice‐guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty‐aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real‐world data demonstrate the usefulness, efficiency and ease‐of‐use of our method.     

Interactive Visualization of Multimodal Volume Data for Neurosurgical Tumor Treatment

We present novel interactive methods for the visualization of multimodal volume data as used in neurosurgical therapy planning. These methods allow surgeons to explore multimodal volumes and focus on functional data and lesions. Computer graphics techniques are proposed to create expressive visualizations at interactive frame rates to reduce time‐consuming and complex interaction with the medical data. Contributions of our work are the distance‐based enhancements of functional data and lesions which allows the surgeon to perceive functional and anatomical structures at once and relate them directly to the intervention. In addition we propose methods for the visual exploration of the path to the structures of interest, to enhance anatomical landmarks, and to provide additional depth indicators. These techniques have been integrated in a visualization prototype that provides interaction capabilities for finding the optimal therapeutic strategy for the neurosurgeon.     

Map Displays for the Analysis of Scalar Data on Cerebral Aneurysm Surfaces

Cerebral aneurysms result from a congenital or evolved weakness of stabilizing parts of the vessel wall and potentially lead to rupture and a life-threatening bleeding. Current medical research concentrates on the integration of blood flow simulation results for risk assessment of cerebral aneurysms. Scalar flow characteristics close to the aneurysm surface, such as wall shear stress, form an important part of the simulation results. Aneurysms exhibit variable surface shapes with only few landmarks. Therefore, the exploration and mental correlation of different surface regions is a difficult task. In this paper, we present an approach for the intuitive and interactive overview visualization of near wall flow data that is mapped onto the surface of a 3D model of a cerebral aneurysm. We combine a multi-perspective 2D projection map with a standard 3D visualization and present techniques to facilitate the correlation between a 3D model and a related 2D map. An informal evaluation with 4 experienced radiologists has shown that the map-based overview actually improves the surface exploration. Furthermore, different color schemes were discussed and, as a result, an appropriate color scheme for the visual analysis of the wall shear stress is presented.     

Direct Visualization of Deformation in Volumes

Deformation is a topic of interest in many disciplines. In particular in medical research, deformations of surfaces and even entire volumetric structures are of interest. Clear visualization of such deformations can lead to important insight into growth processes and progression of disease.
We present new techniques for direct focus+context visualization of deformation fields representing transformations between pairs of volumetric datasets. Typically, such fields are computed by performing a non-rigid registration between two data volumes. Our visualization is based on direct volume rendering and uses the GPU to compute and interactively visualize features of these deformation fields in real-time. We integrate visualization of the deformation field with visualization of the scalar volume affected by the deformations. Furthermore, we present a novel use of texturing in volume rendered visualizations to show additional properties of the vector field on surfaces in the volume.     

A Shape Grammar for Developing Glyph‐based Visualizations

In this paper we address the question of how to quickly model glyph‐based Geographic Information System visualizations. Our solution is based on using shape grammars to set up the different aspects of a visualization, including the geometric content of the visualization, methods for resolving layout conflicts and interaction methods. Our approach significantly increases modelling efficiency over similarly flexible systems currently in use.     

Enclosing Surfaces for Point Clusters Using 3D Discrete Voronoi Diagrams

Point clusters occur in both spatial and non-spatial data. In the former context they may represent segmented particle data, in the latter context they may represent clusters in scatterplots. In order to visualize such point clusters, enclosing surfaces lead to much better comprehension than pure point renderings.
We propose a flexible system for the generation of enclosing surfaces for 3D point clusters. We developed a GPU-based 3D discrete Voronoi diagram computation that supports all surface extractions. Our system provides three different types of enclosing surfaces. By generating a discrete distance field to the point cluster and extracting an isosurface from the field, an enclosing surface with any distance to the point cluster can be generated. As a second type of enclosing surfaces, a hull of the point cluster is extracted. The generation of the hull uses a projection of the discrete Voronoi diagram of the point cluster to an isosurface to generate a polygonal surface. Generated hulls of non-convex clusters are also non-convex. The third type of enclosing surfaces can be created by computing a distance field to the hull and extracting an isosurface from the distance field. This method exhibits reduced bumpiness and can extract surfaces arbitrarily close to the point cluster without losing connectedness.
We apply our methods to the visualization of multidimensional spatial and non-spatial data. Multidimensional clusters are extracted and projected into a 3D visual space, where the point clusters are visualized. The respective clusters can also be visualized in object space when dealing with multidimensional particle data.     

Interactive Exploratory Visualization of 2D Vector Fields

In this paper we present several techniques to interactively explore representations of 2D vector fields. Through a set of simple hand postures used on large, touch‐sensitive displays, our approach allows individuals to custom‐design glyphs (arrows, lines, etc.) that best reveal patterns of the underlying dataset. Interactive exploration of vector fields is facilitated through freedom of glyph placement, glyph density control, and animation. The custom glyphs can be applied individually to probe specific areas of the data but can also be applied in groups to explore larger regions of a vector field. Re‐positionable sources from which glyphs—animated according to the local vector field—continue to emerge are used to examine the vector field dynamically. The combination of these techniques results in an engaging visualization with which the user can rapidly explore and analyze varying types of 2D vector fields, using a virtually infinite number of custom‐designed glyphs.     

Perception of Visual Artifacts in Image‐Based Rendering of Façades

Image‐based rendering (IBR) techniques allow users to create interactive 3D visualizations of scenes by taking a few snapshots. However, despite substantial progress in the field, the main barrier to better quality and more efficient IBR visualizations are several types of common, visually objectionable artifacts. These occur when scene geometry is approximate or viewpoints differ from the original shots, leading to parallax distortions, blurring, ghosting and popping errors that detract from the appearance of the scene. We argue that a better understanding of the causes and perceptual impact of these artifacts is the key to improving IBR methods. In this study we present a series of psychophysical experiments in which we systematically map out the perception of artifacts in IBR visualizations of façades as a function of the most common causes. We separate artifacts into different classes and measure how they impact visual appearance as a function of the number of images available, the geometry of the scene and the viewpoint. The results reveal a number of counter‐intuitive effects in the perception of artifacts. We summarize our results in terms of practical guidelines for improving existing and future IBR techniques.