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IEEE Computer Graphics and Applications

Wolfgang Buschel, Stefan Vogt, Raimund Dachselt
3D Node-link diagrams are an important class of visualization for immersive analysis. Yet, there is little knowledge on how to visualize edges to support efficient analysis. We present an exploration of the design space for edge styles and discuss the results of a user study comparing six different edge variants.
February 6, 2019: IEEE Computer Graphics and Applications
Christina Gillmann, Tobias Post, Thomas Wischgoll, Hans Hagen, Ross Maciejewski
Image segmentation is an important subtask in biomedical research applications, such as estimating the position and shape of a tumor. Unfortunately, advanced image segmentation methods are not widely applied in research applications as they often miss features, such as uncertainty communication, and may lack an intuitive approach for the use of the underlying algorithm. To solve this problem, this work fuses a fuzzy and a hierarchical segmentation approach together, thus providing a flexible multi-class segmentation method based on probabilistic path propagations...
January 18, 2019: IEEE Computer Graphics and Applications
Zizhao Wu, Ming Zeng, Feiwei Qin, Yigang Wang, Jiri Kosinka
We present a novel active learning approach for shape co-segmentation based on graph convolutional networks (GCN). The premise of our approach is to represent the collections of 3D shapes as graph-structured data, where each node in the graph corresponds to a primitive patch of an over-segmented shape, and is associated with a representation initialized by extracting features. Then, the GCN operates directly on the graph to update the representation of each node based on a layer-wise propagation rule, which aggregates information from its neighbors, and predicts the labels for unlabeled nodes...
January 14, 2019: IEEE Computer Graphics and Applications
Johannes Novotny, Wesley R Miller, Francois I Luks, Derek Merck, Scott Collins, David H Laidlaw
We present a case study evaluating the potential for interactively identifying placental surface blood vessels using magnetic resonance imaging (MRI) scans in virtual reality (VR) environments. We visualized the MRI data using direct volume rendering in a high-fidelity CAVE-like VR system, allowing medical professionals to identify relevant placental vessels directly from volume visualizations in the VR system, without prior vessel segmentation. Participants were able to trace most of the observable vascular structure, and consistently identified blood vessels down to diameters of 1 mm, an important requirement in diagnosing vascular diseases...
December 24, 2018: IEEE Computer Graphics and Applications
Cheng Xu, Cheng Zhang, Xiaochen Zhou, Biao Leng
In view-based 3D model retrieval task, extracting discriminative high-level features of models from projected images is considered an effective approach. The challenge of view-based 3D shape retrieval is that shape information of each view is limited due to information deficiency in projection. Traditional methods in this direction mostly convert the model into a panoramic view, making it hard to recognize the original shape. To resolve this problem, we propose a novel deep neural network, Recurrent Panorama Network (RePanoNet), which can learn to build panoramic representation from view sequences...
December 6, 2018: IEEE Computer Graphics and Applications
Lei Li, Hongbo Fu, Chiew-Lan Tai
We present a simple and efficient method based on deep learning to automatically decompose sketched objects into semantically valid parts. We train a deep neural network to transfer existing segmentations and labelings from 3D models to freehand sketches without requiring numerous well-annotated sketches as training data. The network takes the binary image of a sketched object as input and produces a corresponding segmentation map with per-pixel labelings as output. A subsequent post-process procedure with multi-label graph cuts further refines the segmentation and labeling result...
December 6, 2018: IEEE Computer Graphics and Applications
Xiaodong Cun, Feng Xu, Chi-Man Pun, Hao Gao
Researches in novel viewpoint synthesis are majorly based on multi-view input images. In this paper, we focus on a more challenging and ill-posed problem that is to synthesize surrounding novel viewpoints from a single image. To achieve this goal, we design a full resolution network to extract fine-scale image fea-tures, which contributes to prevent blurry artifacts. We also involve a pre-trained relative depth estima-tion network, thus 3D information is utilized to infer the flow field between the input and target image...
December 6, 2018: IEEE Computer Graphics and Applications
Jens Grubert, Eyal Ofek, Michel Pahud, Per Ola Kristensson
Virtual reality has the potential to change the way we work. We envision the future office worker to be able to work productively everywhere solely using portable standard input devices and immersive head-mounted displays. Virtual reality has the potential to enable this, by allowing users to create working environments of their choice and by relieving them from physical world limitations, such as constrained space or noisy environments. In this paper, we investigate opportunities and challenges for realizing this vision and discuss implications from recent findings of text entry in virtual reality as a core office task...
November 2018: IEEE Computer Graphics and Applications
Mingran Li, Wenjie Wu, Junhan Zhao, Keyuan Zhou, David Perkis, Timothy N Bond, Kevin Mumford, David Hummels, Yingjie Victor Chen
We present our CareerVis system, an interactive visualization tool to aid career education for high school and freshman college students. In additional to its practical use, we believe our design approach has potential to inspire the design community to develop simple visualizations that convey complex information to novice users.
November 2018: IEEE Computer Graphics and Applications
Yang Shi, Ying Zhao, Fangfang Zhou, Ronghua Shi, Yaoxue Zhang
Intrusion detection systems (IDSs) generally produce an overwhelming amount of alerts, which are commonly plagued by issues of false positives. It is cumbersome for network administrators to manually traverse text-based alert logs in order to detect threats. In this work, we present a novel radial visualization of IDSs alerts, IDSPlanet, which helps administrators identify false positives, analyze attack patterns, and understand evolving network situations. Using a planet's geology as a metaphor for the design, IDSPlanet is composed of chrono rings, alert continents, and an interactive core...
November 2018: IEEE Computer Graphics and Applications
Ji Hwan Park, Arie Kaufman, Klaus Mueller
Graphoto is a framework that automatically generates a photo or adjusts an existing one to match a line graph. Since aesthetics is an important element in visualizing personal data, Graphoto provides users with aesthetically pleasing displays for casual line graph information visualization. More specifically, after creating a line graph of the input data, a photo that resembles the input data on the line graph is selected from a photo archive. If a selected photo does not match the line graph, we deform the photo to match the line graph...
November 2018: IEEE Computer Graphics and Applications
Adam Gardner, Ludovic Autin, Brett Barbaro, Arthur J Olson, David S Goodsell
CellPAINT allows nonexpert users to create interactive mesoscale illustrations that integrate a variety of biological data. Like popular digital painting software, scenes are created using a palette of molecular "brushes." The current release allows creation of animated scenes with an HIV virion, blood plasma, and a simplified T-cell.
November 2018: IEEE Computer Graphics and Applications
Dylan Cashman, Genevieve Patterson, Abigail Mosca, Nathan Watts, Shannon Robinson, Remco Chang
We present RNNbow, an interactive tool for visualizing the gradient flow during backpropagation in training of recurrent neural networks. By visualizing the gradient, as opposed to activations, RNNbow offers insight into how the network is learning. We show how it illustrates the vanishing gradient and the training process.
November 2018: IEEE Computer Graphics and Applications
Adam James Bradley, Mennatallah El-Assady, Katharine Coles, Eric Alexander, Min Chen, Christopher Collins, Stefan Janicke, David Joseph Wrisley
For the past two years, researchers from the visualization community and the digital humanities have come together at the IEEE VIS conference to discuss how both disciplines can work together to push research goals in their respective disciplines. In this paper, we present our experiences as a result of this collaboration.
November 2018: IEEE Computer Graphics and Applications
David Borland, Wenyuan Wang, David Gotz
Unseen information can lead to various "threats to validity" when analyzing complex datasets using visual tools, resulting in potentially biased findings. We enumerate sources of unseen information and argue that a new focus on contextual visualization methods is needed to inform users of these threats and to mitigate their effects.
November 2018: IEEE Computer Graphics and Applications
Miriah Meyer, Jason Dykes
Reflection is a core method used by visualization researchers to generate knowledge from design practice. There is, however, a lack of standards to inform reflective practice and through which we can judge the quality of the reflection used in visualization research. Reflecting on this gap, we offer priorities for researchers looking to improve the use of reflection in applied visualization research.
November 2018: IEEE Computer Graphics and Applications
Jordi Linares-Pellicer, Jorge Orta-Lopez, Juan Izquierdo-Domenech
This work describes the implementation of a flip teaching alternative in an introductory game development course, using resources from a MOOC (Massive Open On-Line Course). The results proved to achieve better grades and higher satisfaction to previous and similar lecture-based courses.
October 17, 2018: IEEE Computer Graphics and Applications
Felix Heide
While traditional imaging systems directly measure scene properties, computational imaging systems add computation to the measurement process, allowing such systems to extract non-trivially encoded scene features. This work demonstrates that exploiting structure in this process allows to recover information that is conventionally considered to be "lost". Relying on temporally and spatially convolutional structure, we extract a novel image modality that was essentially "invisible" before: a new temporal dimension of light propagation, obtained with consumer depth cameras...
October 3, 2018: IEEE Computer Graphics and Applications
Jorge Posada, Mikel Zorrilla, Ana Dominguez, Bruno Simoes, Peter Eisert, Didier Stricker, Jason Rambach, Jurgen Dollner, Miguel Guevara
Visual computing technologies have an important role in manufacturing and production, particularly in new Industry 4.0 scenarios with intelligent machines, human-robot collaboration and learning factories. In this article, we explore challenges and examples on how the fusion of graphics, vision and media technologies can enhance the role of operators in this new context.
September 2018: IEEE Computer Graphics and Applications
Alexander Bock, Charles Hansen, Anders Ynnerman
This viewpoint presents OpenSpace, an open-source astrovisualization software project designed to bridge the gap between scientific discoveries and their public dissemination. A wealth of data exists for space missions from NASA and other sources. OpenSpace brings together this data and combines it in a range of immersive settings. Through non-linear storytelling and guided exploration, interactive immersive experiences help the public to engage with advanced space mission data and models, and thus be better informed and educated about NASA missions, the solar system and outer space...
September 2018: IEEE Computer Graphics and Applications
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