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IEEE Transactions on Visualization and Computer Graphics

Gennady Andrienko, Natalia Andrienko, Georg Fuchs, Jo Wood
Origin-destination (OD) movement data describe moves or trips between spatial locations by specifying the origins, destinations, start, and end times, but not the routes travelled. For studying the spatio-temporal patterns and trends of mass mobility, individual OD moves of many people are aggregated into flows (collective moves) by time intervals. Time-variant flow data pose two difficult challenges for visualization and analysis. First, flows may connect arbitrary locations (not only neighbors), thus making a graph with numerous edge intersections, which is hard to visualize in a comprehensible way...
October 11, 2016: IEEE Transactions on Visualization and Computer Graphics
Petra Isenberg, Florian Heimerl, Steffen Koch, Tobias Isenberg, Panpan Xu, Charles Stolper, Michael Sedlmair, Jian Chen, Torsten Moller, John T Stasko
We have created and made available to all a dataset with information about every paper that has appeared at the IEEE Visualization (VIS) set of conferences: InfoVis, SciVis, VAST, and Vis. The information about each paper includes its title, abstract, authors, and citations to other papers in the conference series, among many other attributes. This article describes the motivation for creating the dataset, as well as our process of coalescing and cleaning the data, and a set of three visualizations we created to facilitate exploration of the data...
October 5, 2016: IEEE Transactions on Visualization and Computer Graphics
Paolo Federico, Florian Heimerl, Steffen Koch, Silvia Miksch
The increasingly large number of available writings describing technical and scientific progress, calls for advanced analytic tools for their efficient analysis. This is true for many application scenarios in science and industry and for different types of writings, comprising patents and scientific articles. Despite important differences between patents and scientific articles, both have a variety of common characteristics that lead to similar search and analysis tasks. However, the analysis and visualization of these documents is not a trivial task due to the complexity of the documents as well as the large number of possible relations between their multivariate attributes...
September 16, 2016: IEEE Transactions on Visualization and Computer Graphics
Jong-Hyun Kim, Jung Lee, Sungdeok Cha, Chang-Hun Kim
We propose an efficient framework to realistically simulate foam effects in which 3D water particles from a base water solver are first projected onto 2D screen space in order to reduce computational complexity of finding foam particles. Because foam effects are often created primarily in fast and complicated water flows, we analyze acceleration and curvature values to identify the areas exhibiting such flow patterns. Identified foam particles are emitted in 3D simulation space, and each foam particle is advected by its classified type based on its velocity, thereby capturing the essential characteristics of foam wave motions (e...
September 14, 2016: IEEE Transactions on Visualization and Computer Graphics
Andrea Baldacci, Fabio Ganovelli, Massimiliano Corsini, Roberto Scopigno
Using synthetic videos to present a 3D scene is a common requirement for architects, designers, engineers or Cultural Heritage professionals however it is usually time consuming and, in order to obtain high quality results, the support of a film maker/computer animation expert is necessary. We introduce an alternative approach that takes the 3D scene of interest and an example video as input, and automatically produces a video of the input scene that resembles the given video example. In other words, our algorithm allows the user to "replicate" an existing video, on a different 3D scene...
September 13, 2016: IEEE Transactions on Visualization and Computer Graphics
Emanuel Zgraggen, Alex Galakatos, Andrew Crotty, Jean-Daniel Fekete, Tim Kraska
The stated goal for visual data exploration is to operate at a rate that matches the pace of human data analysts, but the ever increasing amount of data has led to a fundamental problem: datasets are often too large to process within interactive time frames. Progressive analytics and visualizations have been proposed as potential solutions to this issue. By processing data incrementally in small chunks, progressive systems provide approximate query answers at interactive speeds that are then refined over time with increasing precision...
September 9, 2016: IEEE Transactions on Visualization and Computer Graphics
Le Liu, Alexander Boone, Ian Ruginski, Lace Padilla, Mary Hegarty, Sarah H Creem-Regehr, William B Thompson, Cem Yuksel, Donald H House
Data ensembles are often used to infer statistics to be used for a summary display of an uncertain prediction. In a spatial context, these summary displays have the drawback that when uncertainty is encoded via a spatial spread, display glyph area increases in size with prediction uncertainty. This increase can be easily confounded with an increase in the size, strength or other attribute of the phenomenon being presented. We argue that by directly displaying a carefully chosen subset of a prediction ensemble, so that uncertainty is conveyed implicitly, such misinterpretations can be avoided...
September 8, 2016: IEEE Transactions on Visualization and Computer Graphics
Philipp von Radziewsky, Thomas Kroes, Martin Eisemann, Elmar Eisemann
Stochastically solving the rendering integral (particularly visibility) is the de-facto standard for physically-based light transport but it is computationally expensive, especially when displaying heterogeneous volumetric data. In this work, we present efficient techniques to speed-up the rendering process via a novel visibility-estimation method in concert with an unbiased importance sampling (involving environmental lighting and visibility inside the volume), filtering, and update techniques for both static and animated scenes...
September 7, 2016: IEEE Transactions on Visualization and Computer Graphics
Fei Hou, Ying He, Hong Qin, Aimin Hao
Biharmonic B-splines, proposed by Feng and Warren, are an elegant generalization of univariate B-splines to planar and curved domains with fully irregular knot configuration. Despite the theoretic breakthrough, certain technical difficulties are imperative, including the necessity of Voronoi tessellation, the lack of analytical formulation of bases on general manifolds, expensive basis re-computation during knot refinement/removal, being applicable for simple domains only (e.g., such as Euclidean planes, spherical and cylindrical domains, and tori)...
September 1, 2016: IEEE Transactions on Visualization and Computer Graphics
Orestis Vantzos, Omri Azencot, Max Wardetzky, Martin Rumpf, Mirela Ben-Chen
The motion of a thin viscous film of fluid on a curved surface exhibits many intricate visual phenomena, which are challenging to simulate using existing techniques. A possible alternative is to use a reduced model, involving only the temporal evolution of the mass density of the film on the surface. However, in this model, the motion is governed by a fourth-order nonlinear PDE, which involves geometric quantities such as the curvature of the underlying surface, and is therefore difficult to discretize. Inspired by a recent variational formulation for this problem on smooth surfaces, we present a corresponding model for triangle meshes...
September 1, 2016: IEEE Transactions on Visualization and Computer Graphics
Jingfan Fan, Jian Yang, Yitian Zhao, Danni Ai, Yonghuai Liu, Ge Wang, Yongtian Wang
Non-rigid registration finds many applications such as photogrammetry, motion tracking, model retrieval, and object recognition. In this paper we propose a novel convex hull aided registration method (CHARM) to match two point sets subject to a non-rigid transformation. Firstly, two convex hulls are extracted from the source and target respectively. Then, all points of the point sets are projected onto the reference plane through each triangular facet of the hulls. From these projections, invariant features are extracted and matched optimally...
August 31, 2016: IEEE Transactions on Visualization and Computer Graphics
Jun Wang, Kevin Kai Xu
LiDAR scanning has become a prevalent technique for digitalizing large-scale outdoor scenes. However, the raw LiDAR data often contain imperfections, e.g., missing large regions, anisotropy of sampling density, and contamination of noise and outliers, which are the major obstacles that hinder its more ambitious and higher level applications in digital city modeling. Observing that 3D urban scenes can be locally described with several low dimensional subspaces, we propose to locally classify the neighborhoods of the scans to model the substructures of the scenes...
August 31, 2016: IEEE Transactions on Visualization and Computer Graphics
Tatiana von Landesberger, Dieter Fellner, Roy Ruddle
The rising quantity and complexity of data creates a need to design and optimize data processing pipelines - the set of data processing steps, parameters and algorithms that perform operations on the data. Visualization can support this process but, although there are many examples of systems for visual parameter analysis, there remains a need to systematically assess users' requirements and match those requirements to exemplar visualization methods. This article presents a new characterization of the requirements for pipeline design and optimization...
August 25, 2016: IEEE Transactions on Visualization and Computer Graphics
Eric D Ragan, Siroberto Scerbo, Felipe Bacim, Doug A Bowman
Many types of virtual reality (VR) systems allow users to use natural, physical head movements to view a 3D environment. In some situations, such as when using systems that lack a fully surrounding display or when opting for convenient low-effort interaction, view control can be enabled through a combination of physical and virtual turns to view the environment, but the reduced realism could potentially interfere with the ability to maintain spatial orientation. One solution to this problem is to amplify head rotations such that smaller physical turns are mapped to larger virtual turns, allowing trainees to view the entire surrounding environment with small head movements...
August 19, 2016: IEEE Transactions on Visualization and Computer Graphics
Wenguan Wang, Jianbing Shen, Yizhou Yu, Kwan-Liu Ma
Existing algorithms generate thumbnails from single images. In this paper, we propose a framework for automatically producing thumbnails from stereo image pairs. It has two components focusing respectively on stereo saliency detection and stereo thumbnail generation. The first component analyzes stereo saliency through various saliency stimuli, stereoscopic perception and the relevance between two stereo views. The second component uses stereo saliency to guide stereo thumbnail generation. We develop two types of thumbnail generation methods, both changing image size automatically...
August 16, 2016: IEEE Transactions on Visualization and Computer Graphics
Shiqing He, Eytan Adar
Shifts in information visualization practice are forcing a reconsideration of how infovis is taught. Traditional curricula that focused on conveying research-derived knowledge are slowly integrating design thinking as a key learning objective. In part, this is motivated by the realization that infovis is a wicked design problem, requiring a different kind of design work. In this paper we describe, VIZITCARDS, a card-driven workshop developed for our graduate infovis class. The workshop is intended to provide practice with good design techniques and to simultaneously reinforce key concepts...
August 10, 2016: IEEE Transactions on Visualization and Computer Graphics
Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu
Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification. However, the development of high-quality deep models typically relies on a substantial amount of trial-and-error, as there is still no clear understanding of when and why a deep model works. In this paper, we present a visual analytics approach for better understanding, diagnosing, and refining deep CNNs. We formulate a deep CNN as a directed acyclic graph. Based on this formulation, a hybrid visualization is developed to disclose the multiple facets of each neuron and the interactions between them...
August 9, 2016: IEEE Transactions on Visualization and Computer Graphics
Aritra Dasgupta, Joon-Yong Lee, Ryan Wilson, Robert Lafrance, Nick Cramer, Kristin Cook, Samuel Payne
Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust...
August 8, 2016: IEEE Transactions on Visualization and Computer Graphics
Cong Xie, Wen Zhong, Klaus Mueller
Oftentimes multivariate data are not available as sets of equally multivariate tuples, but only as sets of projections into subspaces spanned by subsets of these attributes. For example, one may find data with five attributes stored in six tables of two attributes each, instead of a single table of five attributes. This prohibits the visualization of these data with standard high-dimensional methods, such as parallel coordinates or MDS, and there is hence the need to reconstruct the full multivariate (joint) distribution from these marginal ones...
August 5, 2016: IEEE Transactions on Visualization and Computer Graphics
Xinsong Yang, Lei Shi, Madelaine Daianu, Hanghang Tong, Qingsong Liu, Paul Thompson
Visually comparing human brain networks from multiple population groups serves as an important task in the field of brain connectomics. The commonly used brain network representation, consisting of nodes and edges, may not be able to reveal the most compelling network differences when the reconstructed networks are dense and homogeneous. In this paper, we leveraged the block information on the Region Of Interest (ROI) based brain networks and studied the problem of blockwise brain network visual comparison...
August 5, 2016: IEEE Transactions on Visualization and Computer Graphics
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