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An interesting aspect in graph analysis is the notion of (structural) centrality, which pertains to quantifying importance of entities (or vertices, nodes) within the context of the graph structure as defined by it's relationships (or edges). The need to compute centrality and convey it through visualization is seen in many areas. In this work, we propose a method to visualize node centrality information in the context of overall graph structure, which we capture through intervertex (graph theoretical) distances. |
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The problem of visualizing graphs becomes more complex as we consider the growing diversity of visualization tasks on graphs. For instance, in the domain of neuroscience, there is a need to gain insight into how a graph (representing a brain network) compares to another, or how a graph ensemble (brain networks associated with a specific group) compares to an individual graph or another ensemble. The goal of this project is to develop a method to visualize graph ensembles in a way that is able to convey the underlying structure (both the center and variability of the underlying distribution of edge weights) in context of the relationships between nodes in the graph. |
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Graphs are powerful and versatile data structures that can be used to represent a wide range of different types of information. We introduce a method to analyze and then visualize an important class of data described over a graph—namely, ensembles of paths. Analysis of such path ensembles is useful in a variety of applications, such as molecular dynamics, computer networks and transportation. The proposed method generalizes the concept of band depth to an ensemble of paths on a graph, which provides an center-outward ordering on the paths. This ordering is, in turn, used to construct a generalization of the conventional boxplot or whisker plot, called a path boxplot, which applies to paths on a graph. |
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The visualization of variability in 3D shapes or surfaces, which is a type of ensemble uncertainty visualization for volume data, provides a means of understanding the underlying distribution for a collection or ensemble of surfaces. While ensemble visualization for surfaces is already described in the literature, we conduct an expert-based evaluation in a particular medical imaging application: the construction of atlases or templates from a population of images. In this work, we extend contour boxplots to 3D, allowing us to evaluate it against an enumeration-style visualization of the ensemble members and also other conventional visualizations used by atlas builders, namely examining the atlas image and the corresponding images/data provided as part of the construction process. |
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Animated avatars are becoming increasingly prevalent in three-dimensional virtual environments due to modern motion tracking hardware and their falling cost. As this opens up new possibilities and ways of interaction within such virtual worlds, an important question that arises is how does the presence of an avatar alter the perception and performance of an action in a virtual environment when a user interacts with an object in the virtual environment through their avatar. This research attempts to answer this question by studying the effects of presence of an animated self-avatar in an object manipulation task in a virtual environment. |
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