Defocus Magnification

A blurry background due to shallow depth of field is often desired for photographs such as portraits, but, unfortunately, small point-and-shoot cameras do not permit enough defocus because of the small diameter of their lenses. We present an image-processing technique that increases the defocus in an image to simulate the shallow depth of field of a lens with a larger aperture. Our technique estimates the spatially-varying amount of blur over the image, and then uses a simple image-based technique to increase defocus. We first estimate the size of the blur kernel at edges and then propagate this defocus measure over the image. Using our defocus map, we magnify the existing blurriness, which means that we blur blurry regions and keep sharp regions sharp. In contrast to more difficult problems such as depth from defocus, we do not require precise depth estimation and do not need to disambiguate textureless regions.     

Visualisation of Sensor Data from Animal Movement

A new area of biological research is identifying and grouping patterns of behaviour in wild animals by analysing data obtained through the attachment of tri-axial accelerometers. As these recording devices become smaller and less expensive their use has increased. Currently acceleration data are visualised as 2D time series plots, and analyses are based on summary statistics and the application of Fourier transforms. We develop alternate visualisations of this data so as to analyse, explore and present new patterns of animal behaviour. Our visualisations include interactive spherical scatterplots, spherical histograms, clustering methods, and feature-based state diagrams of the data. We study the application of these visualisation methods to accelerometry data from animal movement. The reaction of biologists to these visualisations is also reported.     

Visual Supercomputing: Technologies, Applications and Challenges

If we were to have a Grid infrastructure for visualization, what technologies would be needed to build such an infrastructure, what kind of applications would benefit from it, and what challenges are we facing in order to accomplish this goal? In this survey paper, we make use of the term ‘visual supercomputing’ to encapsulate a subject domain concerning the infrastructural technology for visualization. We consider a broad range of scientific and technological advances in computer graphics and visualization, which are relevant to visual supercomputing. We identify the state‐of‐the‐art technologies that have prepared us for building such an infrastructure. We examine a collection of applications that would benefit enormously from such an infrastructure, and discuss their technical requirements. We propose a set of challenges that may guide our strategic efforts in the coming years.     

Visual Analysis and Semantic Exploration of Urban LIDAR Change Detection

Many previous approaches to detecting urban change from LIDAR point clouds interpolate the points into rasters, perform pixel‐based image processing to detect changes, and produce 2D images as output. We present a method of LIDAR change detection that maintains accuracy by only using the raw, irregularly spaced LIDAR points, and extracts relevant changes as individual 3D models. We then utilize these models, alongside existing GIS data, within an interactive application that allows the chronological exploration of the changes to an urban environment. A three‐tiered level‐of‐detail system maintains a scale‐appropriate, legible visual representation across the entire range of view scales, from individual changes such as buildings and trees, to groups of changes such as new residential developments, deforestation, and construction sites, and finally to larger regions such as neighborhoods and districts of a city that are emerging or undergoing revitalization. Tools are provided to assist the visual analysis by urban planners and historians through semantic categorization and filtering of the changes presented.     

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.     

Reusable Visualizations and Animations for Surgery Planning

For surgical planning, the exploration of 3D visualizations and 2D slice views is essential. However, the generation of visualizations which support the specific treatment decisions is very tedious. Therefore, the reuse of once designed visualizations for similar cases can strongly accelerate the process of surgical planning. We present a new technique that enables the easy reuse of both medical visualization types: 3D scenes and 2D slice views. We introduce the keystates as a concept to describe the state of a visualization in a general manner. They can be easily applied to new datasets to create similar visualizations. Keystates can be shared between surgeons of one specialization to reproduce and document the planning process for collaborative work. Furthermore, animations can support the surgeon on individual exploration and are also useful in collaborative environments, where complex issues must be presented in a short time. Therefore, we provide a framework, where animations can be visually designed by surgeons during their exploration process without any programming or authoring skills. We discuss several transitions between different visualizations and present an application from clinical routine.     

Energy‐scale Aware Feature Extraction for Flow Visualization

In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high‐energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.     

An Evaluation of Visualization Techniques to Illustrate Statistical Deformation Models

As collections of 2D/3D images continue to grow, interest in effective ways to visualize and explore the statistical morphological properties of a group of images has surged. Recently, deformation models have emerged as simple methods to capture the variability and statistical properties of a collection of images. Such models have proven to be effective in tasks such as image classification, generation, registration, segmentation, and analysis of modes of variation. A crucial element missing from most statistical models has been an effective way to summarize and visualize the statistical morphological properties of a group of images. This paper evaluates different visualization techniques that can be extended and used to illustrate the information captured by such statistical models. First, four illustration techniques are described as methods to summarize the statistical morphological properties as captured by deformation models. Second, results of a user study conducted to compare the effectiveness of each visualization technique are presented. After comparing the performance of 40 subjects, we found that statistical annotation techniques present significant benefits when analyzing the structural properties of a group of images.     

Over Two Decades of Integration‐Based,Geometric Flow Visualization

With ever increasing computing power, it is possible to process ever more complex fluid simulations. However, a gap between data set sizes and our ability to visualize them remains. This is especially true for the field of flow visualization, which deals with large, time‐dependent, multivariate simulation data sets. In this paper, geometry‐based flow visualization techniques form the focus of discussion. Geometric flow visualization methods place discrete objects in the velocity field whose characteristics reflect the underlying properties of the flow. A great amount of progress has been made in this field over the last two decades. However, a number of challenges remain, including placement, speed of computation and perception. In this survey, we review and classify geometric flow visualization literature according to the most important challenges when considering such a visualization, a central theme being the seeding algorithm upon which they are based. This paper details our investigation into these techniques with discussions on their applicability and their relative merits and drawbacks. The result is an up‐to‐date overview of the current state‐of‐the‐art that highlights both solved and unsolved problems in this rapidly evolving branch of research. It also serves as a concise introduction to the field of flow visualization research.     

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.     

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.     

Dental Inlay and Onlay Construction by Iterative Laplacian Surface Editing

We propose a new method for automatic construction of inlays and onlays. Mesh models from a small tooth library are adapted to the remaining healthy surface of the patient's tooth. In the area above the cavity, the general morphology of the model tooth (fissures, cusp tips, etc) is preserved, but precisely adjusted to the intra‐oral situation. Our approach uses iterative Laplacian Surface Editing to deform the model tooth. This allows the automatic generation of highly individual, functional and anatomically correct inlays/onlays, without having to resort to a large library of different tooth shapes.     

Embedded Implicit Stand-Ins for Animated Meshes: A Case of Hybrid Modelling

In this paper, we address shape modelling problems, encountered in computer animation and computer games development that are difficult to solve just using polygonal meshes. Our approach is based on a hybrid-modelling concept that combines polygonal meshes with implicit surfaces. A hybrid model consists of an animated polygonal mesh and an approximation of this mesh by a convolution surface stand-in that is embedded within it or is attached to it. The motions of both objects are synchronised using a rigging skeleton. We model the interaction between an animated mesh object and a viscoelastic substance, which is normally represented in an implicit form. Our approach is aimed at achieving verisimilitude rather than physically based simulation. The adhesive behaviour of the viscous object is modelled using geometric blending operations on the corresponding implicit surfaces. Another application of this approach is the creation of metamorphosing implicit surface parts that are attached to an animated mesh. A prototype implementation of the proposed approach and several examples of modelling and animation with near real-time preview times are presented.     

Topology‐based Visualization of Transformation Pathways in Complex Chemical Systems

Studying transformation in a chemical system by considering its energy as a function of coordinates of the system's components provides insight and changes our understanding of this process. Currently, a lack of effective visualization techniques for high‐dimensional energy functions limits chemists to plot energy with respect to one or two coordinates at a time. In some complex systems, developing a comprehensive understanding requires new visualization techniques that show relationships between all coordinates at the same time. We propose a new visualization technique that combines concepts from topological analysis, multi‐dimensional scaling, and graph layout to enable the analysis of energy functions for a wide range of molecular structures. We demonstrate our technique by studying the energy function of a dimer of formic and acetic acids and a LTA zeolite structure, in which we consider diffusion of methane.     

SDViz: A Context-Preserving Interactive Visualization System for Technical Diagrams

When performing daily maintenance and repair tasks, technicians require access to a variety of technical diagrams. As technicians trace components and diagrams from page-to-page, within and across manuals, the contextual information of the components they are analyzing can easily be lost. To overcome these issues, we have developed a Schematic Diagram Visualization System (SDViz) designed for maintaining and highlighting contextual information in technical documents, such as schematic and wiring diagrams. Our system incorporates various features to aid in the navigation and diagnosis of faults, as well as maintaining contextual information when tracing components/connections through multiple diagrams. System features include highlighting relationships between components and connectors, diagram annotation tools, the animation of flow through the system, a novel contextual blending method, and a variety of traditional focus+context visualization techniques. We have evaluated the usefulness of our system through a qualitative user study in which subjects utilized our system in diagnosing faults during a standard aircraft maintenance exercise.     

Visual Analytics for the Exploration of Tumor Tissue Characterization

Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization of these intra‐tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissue characterization could be performed non‐invasively, using medical imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging‐derived feature space is prohibiting for easy exploration and analysis ‐ especially when clinical researchers require to associate observations from the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing them and mentally reconstructing their relationships. This is a time consuming and tedious process, from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visual analysis of the feature space of imaging‐derived tissue characteristics and (2) knowledge discovery and hypothesis generation and confirmation, with respect to reference data used in clinical research. We employ, as central view, a 2D embedding of the imaging‐derived features. Multiple linked interactive views provide functionality for the exploration and analysis of the local structure of the feature space, enabling linking to patient anatomy and clinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreed that, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneous intra‐tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.     

Atomistic Visualization of Mesoscopic Whole‐Cell Simulations Using Ray‐Casted Instancing

Molecular visualization is an important tool for analysing the results of biochemical simulations. With modern GPU ray casting approaches, it is only possible to render several million of atoms interactively unless advanced acceleration methods are employed. Whole‐cell simulations consist of at least several billion atoms even for simplified cell models. However, many instances of only a few different proteins occur in the intracellular environment, which can be exploited to fit the data into the graphics memory. For each protein species, one model is stored and rendered once per instance. The proposed method exploits recent algorithmic advances for particle rendering and the repetitive nature of intracellular proteins to visualize dynamic results from mesoscopic simulations of cellular transport processes. We present two out‐of‐core optimizations for the interactive visualization of data sets composed of billions of atoms as well as details on the data preparation and the employed rendering techniques. Furthermore, we apply advanced shading methods to improve the image quality including methods to enhance depth and shape perception besides non‐photorealistic rendering methods. We also show that the method can be used to render scenes that are composed of triangulated instances, not only implicit surfaces.     

Visual Analysis of Trajectories in Multi‐Dimensional State Spaces

Multi‐dimensional data originate from many different sources and are relevant for many applications. One specific sub‐type of such data is continuous trajectory data in multi‐dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous‐time scatterplots and continuous‐time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration. We demonstrate the usefulness of our visualization approach for three case studies that cover examples of complex dynamic systems: cyber‐physical systems consisting of heterogeneous sensors and actuators networks (the collection of time‐dependent sensor network data of an exemplary smart home environment), the dynamics of robot arm movement and motion characteristics of humanoids.     

Cell lineage visualisation

Cell lineages describe the developmental history of Cell populations and are produced by combining time‐lapse imaging and image processing. Biomedical researchers study Cell lineages to understand fundamental processes such as Cell differentiation and the pharmacodynamic action of anticancer agents. Yet, the interpretation of Cell lineages is hindered by their complexity and insufficient capacity for visual analysis. We present a novel approach for interactive visualisation of Cell lineages. Based on an understanding of Cellular biology and live‐Cell imaging methodology, we identify three requirements: multimodality (Cell lineages combine spatial, temporal, and other properties), symmetry (related to lineage branching structure), and synchrony (related to temporal alignment of Cellular events). We address these by combining visual summaries of the spatiotemporal behaviour of an arbitrary number of lineages, including variation from average behaviour, with node‐link representations that emphasise the presence or absence of symmetry and synchrony. We illustrate the merit of our approach by presenting a real‐world case study where the cytotoxic action of the anticancer drug topotecan was determined.