Encoding uncertainty in timelines can provide more precise and informative visualizations (e.g., visual representations of unsure times or locations in event planning timelines). To evaluate the effectiveness of different temporal and categorical uncertainty representations on timelines, we conducted a mixed-methods user study with 81 participants on uncertainty in activity recall timelines (ARTs). We find that participants’ accuracy is better when temporal uncertainty is encoded using transparency instead of dashing, and that a participant’s visual encoding preference does not always align with their performance (e.g., they performed better with a less-preferred visual encoding technique). Additionally, qualitative findings show that existing biases of an individual alter their interpretation of ARTs. A copy of our study materials is available at https://osf.io/98p6m/.
We introduce a modified dendrogram (MD) (with sub-trees to represent the feature space clusters) and display it in continuous space for multi-dimensional transfer function (TF) design and modification. Such a TF for direct volume rendering often employs a multi-dimensional feature space. In an n-dimensional (nD) feature space, each voxel is described using n attributes and represented by a vector of n values. The MD reveals the hierarchical structure information of the high-dimensional feature space clusters. Using the MD user interface (UI), the user can design and modify the TF in 2D in an intuitive and informative manner instead of designing it directly in multi-dimensional space where it is complicated and harder to understand the relationship of the feature space vectors. In addition, we provide the capability to interactively change the granularity of the MD. The coarse-grained MD shows primarily the global information of the feature space while the fine-grained MD reveals the finer details, and the separation ability of the high-dimensional feature space is completely preserved in the finest granularity. With the so called multi-grained method, the user can efficiently create a TF using the coarse-grained MD, then fine tune it with the finer-grained MDs to improve the quality of the volume rendering. Furthermore, we propose a fast interactive hierarchical clustering (FIHC) algorithm for accelerating the MD computation and supporting the interactive multi-grained TF design. In the FIHC, the finest-grained MD is established by linking the feature space vectors, then the feature space vectors being the leaves of this tree are clustered using a hierarchical leaf clustering (HLC) algorithm forming a leaf vector hierarchical tree (LVHT). The granularity of the MD can be changed by setting the precision of the LVHT. Our method is independent on the type of the attributes and supports arbitrary-dimension feature space.
We present the conformal magnifier, a novel interactive Focus+Context visualization technique to magnify a region of interest (ROI) using conformal mapping. Our framework allows the user to design an arbitrary magnifier to enlarge the features of interest while deforming part of the remaining areas without any cropping. By using conformal mapping, the ROI is magnified with minimal distortion, while the transition region is a smooth and continuous deformation between the focus and context regions. An interactive interface is designed for the user to select important features, design focus models of arbitrary shape and set deformation constraints to satisfy his/her specified requirements. We demonstrate the effectiveness, robustness and efficiency of our method using several applications: texts, maps, geographic images, data structures and multi-media visualization.
We describe a visualization system designed for interactive study of proteins in the field of computational biology. Our system incorporates multiple, custom, three-dimensional and two-dimensional linked views of the proteins. We take advantage of modem commodity graphics cards, which are typically designed for games rather than scientific visualization applications, to provide instantaneous linking between views and three-dimensional interactivity on standard personal computers. Furthermore, we anticipate the usefulness of game techniques such as bump maps and skinning for scientific applications.
For psychophysical studies in spatial cognition a virtual model of the picturesque old town of Tubingen has been constructed. In order to perform psychophysical experiments in highly realistic virtual environments the model is based on high quality texture maps adding up to several hundreds of MBytes. To accomplish the required real-time frame updates, view frustum and occlusion culling without visibility pre-processing, levels of detail, and texture compression are applied in an interleaved manner. Shared memory communication and a standard PC with two commodity graphics cards is used to enable the powerful combination of those techniques because this combination is not yet available on a single graphics card.
In this case study we discuss an interactive feature tracking system and its use for the analysis of chromatin decondensation. Features are described as points in a multidimensional attribute space. Distances between points are used as a measure for feature correspondence. Users can interactively experiment with the correspondence measure in order to gain insight in chromatin movement. In addition, by defining time as an attribute, tracking problems related to noisy confocal data can be circumvented.
The visualization of time-dependent flow is an important and challenging topic in scientific visualization. Its aim is to represent transport phenomena governed by time-dependent vector fields in an intuitively understandable way, using images and animations. Here we pick up the recently presented anisotropic diffusion method, expand and generalize it to allow a multiscale visualization of long-term, complex transport problems. Instead of streamline type patterns generated by the original method now streakline patterns are generated and advected. This process obeys a nonlinear transport diffusion equation with typically dominant transport. Starting from some noisy initial image, the diffusion actually generates and enhances patterns which are then transported in the direction of the flow field. Simultaneously the image is again sharpened in the direction orthogonal to the flow field. A careful adjustment of the models parameters is derived to balance diffusion and transport effects in a reasonable way. Properties of the method can be discussed for the continuous model, which is solved by an efficient upwind finite element discretization. As characteristic for the class of multiscale image processing methods, we can in advance select a suitable scale for representing the flow field.
In this paper we address the problem of interactively resampling unstructured grids. Three algorithms are presented. They all allow adaptive resampling of an unstructured grid on a multiresolution hierarchy of arbitrarily sized cartesian grids according to a varying element size. Two of the algorithms presented take advantage of hardware accelerated polygon rendering and 2D texture mapping. In exploiting new features of modem PC graphics adapters, the first algorithm tries to significantly minimize the number of polygons to be rendered. Reducing rasterization requirements is the main goal of the second algorithm, which distributes the computational workload differently between the main processor and the graphics chip. By comparing them to a new pure software approach, an optimal software-hardware balance is studied. We end up with a hybrid approach which greatly improves the performance of hardware assisted resampling by involving the main processor to a higher degree and thus enabling resampling at nearly interactive rates.
Commonly-used subdivision schemes require manifold control meshes and produce manifold surfaces. However, it is often necessary to model nonmanifold surfaces, such as several surface patches meeting at a common boundary.In this paper, we describe a subdivision algorithm that makes it possible to model nonmanifold surfaces. Any triangle mesh, subject only to the restriction that no two vertices of any triangle coincide, can serve as an input to the algorithm. Resulting surfaces consist of collections of manifold patches joined along nonmanifold curves and vertices. If desired, constraints may be imposed on the tangent planes of manifold patches sharing a curve or a vertex.The algorithm is an extension of a well-known Loop subdivision scheme, and uses techniques developed for piecewise smooth surfaces.
This paper presents a new algorithm for the calculation of stream surfaces for tetrahedral grids. It propagates the surface through the tetrahedra, one at a time, calculating the intersections with the tetrahedral faces. The method allows us to incorporate topological information from the cells, e.g., critical points. The calculations are based on barycentric coordinates, since this simplifies theory and algorithm. The stream surfaces are ruled surfaces inside each cell, and their construction is started with line segments on the faces. Our method supports the analysis of velocity fields resulting from computational fluid dynamics (CFD) simulations.
Vector fields can present complex structural behavior, especially in turbulent computational fluid dynamics. The topological analysis of these datasets reduces the information but one is usually still left with too many details for interpretation. In this paper, we present a simplification approach that removes pairs of critical points from the dataset, based on relevance measures. In contrast to earlier methods, no grid changes are necessary since the whole method uses small local changes of the vector values defining the vector field. An interpretation in terms of bifurcations underlines the continuous, natural flavor of the algorithm.
We present an elegant and simple to implement framework for performing out-of-core visualization and view-dependent refinement of large terrain surfaces. Contrary to the recent trend of increasingly elaborate algorithms for large-scale terrain visualization, our algorithms and data structures have been designed with the primary goal of simplicity and efficiency of implementation. Our approach to managing large terrain data also departs from more conventional strategies based on data tiling. Rather than emphasizing how to segment and efficiently bring data in and out of memory, we focus on the manner in which the data is laid out to achieve good memory coherency for data accesses made in a top-down (coarse-to-fine) refinement of the terrain. We present and compare the results of using several different data indexing schemes, and propose a simple to compute index that yields substantial improvements in locality and speed over more commonly used data layouts.Our second contribution is a new and simple, yet easy to generalize method for view-dependent refinement. Similar to several published methods in this area, we use longest edge bisection in a top-down traversal of the mesh hierarchy to produce a continuous surface with subdivision connectivity. In tandem with the refinement, we perform view frustum culling and triangle stripping. These three components are done together in a single pass over the mesh. We show how this framework supports virtually any error metric, while still being highly memory and compute efficient.
We advocate the use of point sets to represent shapes. We provide a definition of a smooth manifold surface from a set of points close to the original surface. The definition is based on local maps from differential geometry, which are approximated by the method of moving least squares (MLS). We present tools to increase or decrease the density of the points, thus, allowing an adjustment of the spacing among the points to control the fidelity of the representation. To display the point set surface, we introduce a novel point rendering technique. The idea is to evaluate the local maps according to the image resolution. This results in high quality shading effects and smooth silhouettes at interactive frame rates.
In this paper, we propose a new technique to visualize dense representations of time-dependent vector fields based on a Lagrangian-Eulerian Advection (LEA) scheme. The algorithm produces animations with high spatio-temporal correlation at interactive rates. With this technique, every still frame depicts the instantaneous structure of the flow, whereas an animated sequence of frames reveals the motion a dense collection of particles would take when released into the flow. The simplicity of both the resulting data structures and the implementation suggest that LEA could become a useful component of any scientific visualization toolkit concerned with the display of unsteady flows.
We review several schemes for dividing cubical cells into simplices (tetrahedra) in 3-D for interpolating from sampled data to R/sup 3/ or for computing isosurfaces by barycentric interpolation. We present test data that reveal the geometric artifacts that these subdivision schemes generate, and discuss how these artifacts relate to the filter kernels that correspond to the subdivision schemes.
Animal dissection for the scientific examination of organ subsystems is a delicate procedure. Performing this procedure under the complex environment of microgravity presents additional challenges because of the limited training opportunities available that can recreate the altered gravity environment. Traditional astronaut crew training often occurs several months in advance of experimentation, provides limited realism, and involves complicated logistics. We have developed an interactive virtual environment that can simulate several common tasks performed during animal dissection. In this paper, we describe the imaging modality used to reconstruct the rat, provide an overview of the simulation environment and briefly discuss some of the techniques used to manipulate the virtual rat.
The focus of this paper is to evaluate the usefulness of some basic feature tracking algorithms as analysis tools for combustion datasets by application to a dataset modeling autoignition. Features defined as areas of high intermediate concentrations were examined to explore the initial phases in the autoignition process.
We describe a method to visualize the connectivity graph of a mesh using a natural embedding in 3D space. This uses a 3D shape representation that is based solely on mesh connectivity: the connectivity shape. Given a connectivity, we define its natural geometry as a smooth embedding in space with uniform edge lengths and describe efficient techniques to compute it. Our main contribution is to demonstrate that a surprising amount of geometric information is implicit in the connectivity. We also show how to generate connectivity shapes that approximate given 3D shapes. Potential applications of connectivity shapes to modeling and mesh coding are described.
Automatic detection of meaningful isosurfaces is important for producing informative visualizations of volume data, especially when no information about the data origin and imaging protocol is available. We propose a computationally efficient method for the automated detection of intensity transitions in volume data. In this approach, the dominant transitions correspond to clear maxima in cumulative Laplacian-weighted gray value histograms. Only one pass through the data volume is required to compute the histogram. Several other features which may be useful for exploration of data of unknown origin can be efficiently computed in a similar manner. The detected intensity transitions can be used for setting of visualization parameters for surface rendering, as well as for direct volume rendering of 3D datasets. When using surface rendering, the detected dominant intensity transition values correspond to the optimal surface isovalues for extraction of boundaries of the objects of interest. In direct volume rendering, such transitions are important for generation of the transfer functions, which are used to assign visualization properties to data voxels and determine the appearance of the rendered image. The proposed method is illustrated by examples with synthetic data as well as real biomedical datasets.
