Showing papers in "IEEE Computer Graphics and Applications in 2023"
TL;DR: MAGES as mentioned in this paper is a low-code metaverse authoring platform for developers to rapidly prototype high-fidelity and high-complexity medical simulations, since networked participants can also collaborate using different virtual/augmented reality as well as mobile and desktop devices.
Abstract: In this work, we propose MAGES 4.0, a novel Software Development Kit (SDK) to accelerate the creation of collaborative medical training applications in VR/AR. Our solution is essentially a low-code metaverse authoring platform for developers to rapidly prototype high-fidelity and high-complexity medical simulations. MAGES breaks the authoring boundaries across extended reality, since networked participants can also collaborate using different virtual/augmented reality as well as mobile and desktop devices, in the same metaverse world. With MAGES we propose an upgrade to the outdated 150-year-old master-apprentice medical training model. Our platform incorporates, in a nutsell, the following novelties: a) 5G edge-cloud remote rendering and physics dissection layer, b) realistic real-time simulation of organic tissues as soft-bodies under 10ms, c) a highly realistic cutting and tearing algorithm, d) neural network assessment for user profiling and, e) a VR recorder to record and replay or debrief the training simulation from any perspective.
3 citations
TL;DR: In this article , the problem of vertex splitting in 2-layer bipartite drawings is studied, where the vertices on one layer are replaced by two or more copies and suitably distributed their incident edges among these copies.
Abstract: Bipartite graphs model the relationships between two disjoint sets of entities in several applications and are naturally drawn as 2-layer graph drawings. In such drawings, the two sets of entities (vertices) are placed on two parallel lines (layers), and their relationships (edges) are represented by segments connecting vertices. Methods for constructing 2-layer drawings often try to minimize the number of edge crossings. We use vertex splitting to reduce the number of crossings, by replacing selected vertices on one layer by two (or more) copies and suitably distributing their incident edges among these copies. We study several optimization problems related to vertex splitting, either minimizing the number of crossings or removing all crossings with fewest splits. While we prove that some variants are ${\mathsf {NP}}$NP-complete, we obtain polynomial-time algorithms for others. We run our algorithms on a benchmark set of bipartite graphs representing the relationships between human anatomical structures and cell types.
2 citations
2 citations
TL;DR: In this paper , the authors focus on data workers who use dashboards as a primary interface to data, reporting on an interview study that characterizes their data practices and the accompanying barriers to seamless data interaction.
Abstract: Dashboards are the ubiquitous means of data communication within organizations. Yet we have limited understanding of how they factor into data practices in the workplace, particularly for data workers who do not self-identify as professional analysts. We focus on data workers who use dashboards as a primary interface to data, reporting on an interview study that characterizes their data practices and the accompanying barriers to seamless data interaction. While dashboards are typically designed for data consumption, our findings show that dashboard users have far more diverse needs. To capture these activities, we frame data workers’ practices as data conversations: conversations with data capture classic analysis (asking and answering data questions), while conversations through and around data involve constructing representations and narratives for sharing and communication. Dashboard users faced substantial barriers in their data conversations: their engagement with data was often intermittent, dependent on experts, and involved an awkward assembly of tools. We challenge the visualization and analytics community to embrace dashboard users as a population and design tools that blend seamlessly into their work contexts.
2 citations
TL;DR: In this article , the authors provide a personal take on a few research challenges and opportunities that lie ahead that may not be directly addressable by ML, and discuss the importance of this space in visualization research.
Abstract: Unsurprisingly, we have observed tremendous interests and efforts in the application of machine learning (ML) to many data visualization problems, which are having success and leading to new capabilities. However, there is a space in visualization research that is either completely or partly agnostic to ML that should not be lost in this current VIS+ML movement. The research that this space can offer is imperative to the growth of our field and it is important that we remind ourselves to invest in this research as well as show what it could bear. This Viewpoints article provides my personal take on a few research challenges and opportunities that lie ahead that may not be directly addressable by ML.
2 citations
TL;DR: In this article , the authors propose an interactive knowledge and learning environment (IKLE) that integrates three programming and modeling languages to support multiple downstream tasks in the analysis pipeline, such as information retrieval and interactive exploration.
Abstract: The Internet of Food (IoF) is an emerging field in smart foodsheds, involving the creation of a knowledge graph (KG) about the environment, agriculture, food, diet, and health. However, the heterogeneity and size of the KG present challenges for downstream tasks, such as information retrieval and interactive exploration. To address those challenges, we propose an interactive knowledge and learning environment (IKLE) that integrates three programming and modeling languages to support multiple downstream tasks in the analysis pipeline. To make IKLE easier to use, we have developed algorithms to automate the generation of each language. In addition, we collaborated with domain experts to design and develop a dataflow visualization system, which embeds the automatic language generations into components and allows users to build their analysis pipeline by dragging and connecting components of interest. We have demonstrated the effectiveness of IKLE through three real-world case studies in smart foodsheds.
1 citations
TL;DR: In this article , the authors propose an interactive knowledge and learning environment (IKLE) that integrates three programming and modeling languages to support multiple downstream tasks in the analysis pipeline, such as information retrieval and interactive exploration.
Abstract: The Internet of Food (IoF) is an emerging field in smart foodsheds, involving the creation of a knowledge graph (KG) about the environment, agriculture, food, diet, and health. However, the heterogeneity and size of the KG present challenges for downstream tasks, such as information retrieval and interactive exploration. To address those challenges, we propose an interactive knowledge and learning environment (IKLE) that integrates three programming and modeling languages to support multiple downstream tasks in the analysis pipeline. To make IKLE easier to use, we have developed algorithms to automate the generation of each language. In addition, we collaborated with domain experts to design and develop a dataflow visualization system, which embeds the automatic language generations into components and allows users to build their analysis pipeline by dragging and connecting components of interest. We have demonstrated the effectiveness of IKLE through three real-world case studies in smart foodsheds.
1 citations
TL;DR: In this paper , the authors present parameterized models for adaptable simulation of geometrical defects, based on procedural methods, which are suitable for creating defected products in virtual surface inspection planning environments.
Abstract: Development of automated visual surface inspection systems heavily depends on the availability of defected product samples. Both inspection hardware configuration and training of defect detection models require diversified, representative, and precisely annotated data. Reliable training data of sufficient size are frequently challenging to obtain. Using virtual environments, it is possible to simulate defected products, which would serve both for configuration of acquisition hardware as well as for generation of required datasets. In this work, we present parameterized models for adaptable simulation of geometrical defects, based on procedural methods. The presented models are suitable for creating defected products in virtual surface inspection planning environments. As such, they enable inspection planning experts to assess defect visibility for various configurations of acquisition hardware. Finally, the presented method enables pixel-precise annotations alongside image synthesis for the creation of training-ready datasets.
1 citations
TL;DR: In this paper , the authors argue for an alternative, lightweight approach that documents the most relevant parameters with minimal overhead, and use the images produced by visualizations and seamlessly piggyback everyday communication and research collaborations, publication authoring, public outreach, and internal note-taking.
Abstract: Reproducibility is a cornerstone of good scientific practice; however, the ongoing “reproducibility crisis” shows that we still need to improve the way we are doing research currently. Reproducibility is crucial because it enables both the comparison to existing techniques as well as the composition and improvement of existing approaches. It can also increase trust in the respective results, which is paramount for adoption in further research and applications. While there are already many initiatives and approaches with different complexity aimed at enabling reproducible research in the context of visualization, we argue for an alternative, lightweight approach that documents the most relevant parameters with minimal overhead. It still complements complex approaches well, and integration with any existing tool or system is simple. Our approach uses the images produced by visualizations and seamlessly piggy-backs everyday communication and research collaborations, publication authoring, public outreach, and internal note-taking. We exemplify how our approach supports day-to-day work and discuss limitations and how they can be countered.
1 citations
TL;DR: In this article , a Computer-Supported Experiential Learning (CSEL) approach-based tool or mobile application that facilitates virtual reality-based serious role-playing scenarios to enhance the healthcare skills of healthcare professionals and for public awareness.
Abstract: Care experiences and health outcomes may suffer greatly because of healthcare professionals' deficient educational preparation and practices. The limited awareness about the impact of stereotypes, implicit/explicit biases, and Social Determinants of Health (SDH) may result in unpleasant care experiences and healthcare professional-patient relationships. Additionally, as healthcare professionals are no less prone to have biases than other people, it is essential to deliver the learning platform to enhance healthcare skills (e.g., awareness of the importance of cultural humility, inclusive communication proficiencies, awareness of the enduring impact of both SDH and implicit/explicit biases on health outcomes, and compassionate and empathetic attitude) of healthcare professionals which eventually help to raise health equity in society. Moreover, employing the "learning-by-doing" approach directly in real-life clinical practices is less preferable wherein high-risk care is essential. Thus, there is a huge scope to deliver virtual reality-based care practices by engaging the digital experiential learning and Human-Computer Interaction (HCI) approach to enhance patient care experiences, healthcare experiences, and healthcare skills. Thus, this research provides the Computer-Supported Experiential Learning (CSEL) approach-based tool or mobile application that facilitates virtual reality-based serious role-playing scenarios to enhance the healthcare skills of healthcare professionals and for public awareness.
1 citations
TL;DR: In this paper , the authors introduce a virtual flavor device to simulate real flavor experiences, using food-safe chemicals for the three components of a flavor (taste, aroma, mouthfeel), which are perceived as "indistinguishable" from the equivalent real experience.
Abstract: Food and drink are key parts of our lives. While virtual reality has the potential to provide a high-fidelity simulation of real experiences in virtual worlds, the incorporation of flavor appreciation within these virtual experiences has largely been ignored. This article introduces a virtual flavor device to simulate real flavor experiences. The goal is to provide virtual flavor experiences, using food-safe chemicals for the three components of a flavor (taste, aroma, mouthfeel), which are perceived as “indistinguishable” from the equivalent real experience. Furthermore, because we are delivering a simulation, the same device can be used to take a user on a “flavor discovery journey” from a start flavor to a new, preferred flavor by adding or removing any amount of the components. In the first experiment, participants (N = 28) were exposed to real and virtual samples of orange juice, and the health product, rooibos tea, and asked to rate their similarity. The second experiment investigated how participants (N = 6) could move within “flavor space” from one flavor to another. The results show that it is possible to simulate, with a high degree of precision, a real flavor experience, and precisely controlled “flavor discovery journeys” can be undertaken using virtual flavors.
TL;DR: In this paper , a serious video game to learn Scrum, a methodology widely used in the software industry, is presented in mobile Virtual Reality and Web (using WebGL) formats.
Abstract: Virtual Reality is widely used for many educational purposes. However, despite the increasing trend in the use of this technology, it is not yet clear whether it is more effective for learning than other technologies such as traditional computer video games. This paper presents a serious video game to learn Scrum, a methodology widely used in the software industry. The game is available in mobile Virtual Reality and Web (using WebGL) formats. Both versions of the game are compared in terms of knowledge acquisition and motivation enhancement through a robust empirical study involving 289 students and instruments such as pre-post tests and a questionnaire. The obtained results suggest that both formats of the game are useful for acquiring knowledge and promoting aspects such as fun, motivation, and engagement. The results also suggest, strikingly, that there is no difference in terms of learning effectiveness between the two versions of the game.
TL;DR: In this paper , the authors argue for an alternative, lightweight approach that documents the most relevant parameters with minimal overhead, and use the images produced by visualizations and seamlessly piggyback everyday communication and research collaborations, publication authoring, public outreach, and internal note-taking.
Abstract: Reproducibility is a cornerstone of good scientific practice; however, the ongoing “reproducibility crisis” shows that we still need to improve the way we are doing research currently. Reproducibility is crucial because it enables both the comparison to existing techniques as well as the composition and improvement of existing approaches. It can also increase trust in the respective results, which is paramount for adoption in further research and applications. While there are already many initiatives and approaches with different complexity aimed at enabling reproducible research in the context of visualization, we argue for an alternative, lightweight approach that documents the most relevant parameters with minimal overhead. It still complements complex approaches well, and integration with any existing tool or system is simple. Our approach uses the images produced by visualizations and seamlessly piggy-backs everyday communication and research collaborations, publication authoring, public outreach, and internal note-taking. We exemplify how our approach supports day-to-day work and discuss limitations and how they can be countered.
TL;DR: In this article , the authors provide a personal take on a few research challenges and opportunities that lie ahead that may not be directly addressable by ML, and discuss the importance of this space in visualization research.
Abstract: Unsurprisingly, we have observed tremendous interests and efforts in the application of machine learning (ML) to many data visualization problems, which are having success and leading to new capabilities. However, there is a space in visualization research that is either completely or partly agnostic to ML that should not be lost in this current VIS+ML movement. The research that this space can offer is imperative to the growth of our field and it is important that we remind ourselves to invest in this research as well as show what it could bear. This Viewpoints article provides my personal take on a few research challenges and opportunities that lie ahead that may not be directly addressable by ML.
TL;DR: The emerging practice of data-driven storytelling is framing data using familiar narrative mechanisms such as slideshows, videos, and comics to make even highly complex phenomena understandable as discussed by the authors , and a taxonomy focused specifically on media types for the purpose of widening the purview of Data-Driven storytelling by putting more tools into the hands of designers.
Abstract: The emerging practice of data-driven storytelling is framing data using familiar narrative mechanisms such as slideshows, videos, and comics to make even highly complex phenomena understandable. In this survey, we propose a taxonomy focused specifically on media types for the purpose of widening the purview of data-driven storytelling by putting more tools into the hands of designers. The classification shows that current data-driven storytelling practice does not yet leverage the full repertoire of media that can be used for storytelling, such as the spoken word, e-learning, and video games. Using our taxonomy as a generative tool, we also explore three novel storytelling mechanisms, including for live-streaming, gesture-driven oral presentations, and data-driven comics.
TL;DR: The authors compare human responses to perceptual aesthetics judgements on 3D shapes in pairs presented in different 3D shape representation such as voxels, points, wireframe, and polygon.
Abstract: Visual aesthetics of 3D shapes is a fundamental perceptual attribute. In this paper, we explore the question of how different shape representations affect the aesthetic judgments of shape pairs. Specifically, we compare human responses to perceptual aesthetics judgements on 3D shapes in pairs presented in different 3D shape representation such as voxels, points, wireframe, and polygon. In contrast to our own previous work [8] that explores this question for a few shape classes, this paper analyzes a larger number of shape classes. Our key finding is that human aesthetics judgements on relatively low resolution of points or voxels are comparable to polygon meshes, which implies that humans can often make their aesthetics decisions based on relatively coarse representations of the shapes. Our results have implications towards the data collection process of pairwise aesthetics data and the further use of such data in shape aesthetics and 3D modeling problems.
TL;DR: In this article , the authors present VRescue, a simulator for training Urban Search And Rescue (USAR) operators using the paradigm of immersive virtual reality (VR) for post-disaster scenarios.
Abstract: Urban Search And Rescue (USAR) personnel need to be appropriately trained to effectively operate in post-disaster conditions, as they need to quickly identify locations where the presence of survivors is more likely. Currently, the training procedure for this kind of triage is based on showing static pictures presenting different types of building collapses accompanied by cards providing additional environmental information. This article presents VRescue, a simulator for training USAR operators using the paradigm of immersive virtual reality (VR). VRescue recreates a range of operation conditions (day/night, presence of people, dangerous locations, etc.) experienced by real rescuers, and enables learning the use of the equipment commonly used in such scenarios.
TL;DR: The origins and successful evolution of computer graphics in Germany, starting in 1965, is described in this paper , including details of the people and subject matter of the earliest research groups, and efforts undertaken to establish computer graphics as a proper academic discipline, including the founding of EUROGRAPHICS, and creation of institutes for both basic and applied research in computer graphics.
Abstract: “The Origins of Computer Graphics in Europe,” is being published in two parts: Part 1, in this issue of IEEE Computer Graphics and Applications, is subtitled “The Beginnings in Germany”; Part 2, to be published in the May/June issue, is subtitled “The Spreading of Computer Graphics in Europe.” I was a participant, contributor, and witness to the events reported here and I relate my personal story along with the broader history. Part 1 describes the origins and successful evolution of computer graphics in Germany, starting in 1965, and includes details of the people and subject matter of the earliest research groups. It describes the efforts undertaken to establish computer graphics as a proper academic discipline, including the founding of EUROGRAPHICS, and creation of institutes for both basic and applied research in computer graphics. Part 2 continues the story with a focus on activities contributing to the growth of the academic and industrial computer graphics communities across Europe and documents the two IFIP workshops at Seillac and the development of the GKS Graphics Standard. Over these years, computer graphics gained respect and importance as a component of the computer science curricula and became an important tool and enabling technology for applications for industry and for the IT market in Europe.
TL;DR: DistAR as discussed by the authors is an android-based application for social distancing leveraging AR and smart sensing using on-device analysis of optical images and environment crowdedness from smart campus data.
Abstract: In a postpandemic world, remaining vigilant and maintaining social distancing are still crucial so societies can contain the virus and the public can avoid disproportionate health impacts. Augmented reality (AR) can visually assist users in understanding the distances in social distancing. However, integrating external sensing and analysis is required for social distancing beyond the users' local environment. We present DistAR, an android-based application for social distancing leveraging AR and smart sensing using on-device analysis of optical images and environment crowdedness from smart campus data. Our prototype is one of the first efforts to combine AR and smart sensing technologies to create a real-time social distancing application.
TL;DR: Borland and Taylor as discussed by the authors argue that Rainbow Colormaps have properties that are underappreciated by existing design conventions and explore key critiques of the rainbow in the context of recent research to understand where and how rainbows might be misunderstood.
Abstract: Some 15 years ago, Visualization Viewpoints published an influential article titled Rainbow Color Map (Still) Considered Harmful (Borland and Taylor, 2007). The paper argued that the “rainbow colormap’s characteristics of confusing the viewer, obscuring the data and actively misleading interpretation make it a poor choice for visualization.” Subsequent articles often repeat and extend these arguments, so much so that avoiding rainbow colormaps, along with their derivatives, has become dogma in the visualization community. Despite this loud and persistent recommendation, scientists continue to use rainbow colormaps. Have we failed to communicate our message, or do rainbow colormaps offer advantages that have not been fully appreciated? We argue that rainbow colormaps have properties that are underappreciated by existing design conventions. We explore key critiques of the rainbow in the context of recent research to understand where and how rainbows might be misunderstood. Choosing a colormap is a complex task, and rainbow colormaps can be useful for selected applications.
TL;DR: The authors in this paper presented a curated multiscale geospatial dataset with an interactive visualization dashboard under the context of COVID-19, which enables users to visualize the spread of the disease at different scales and allow users to interact with the policies enforced at these scales to observe their impacts on the epidemiology.
Abstract: The coronavirus disease (COVID-19) continued to strike as a highly infectious and fast-spreading disease in 2020 and 2021. As the research community actively responded to this pandemic, we saw the release of many COVID-19-related datasets and visualization dashboards. However, existing resources are insufficient to support multiscale and multifaceted modeling or simulation, which is suggested to be important by the computational epidemiology literature. This work presents a curated multiscale geospatial dataset with an interactive visualization dashboard under the context of COVID-19. This open dataset will allow researchers to conduct numerous projects or analyses relating to COVID-19 or simply geospatial-related scientific studies. The interactive visualization platform enables users to visualize the spread of the disease at different scales (e.g., country level to individual neighborhoods), and allows users to interact with the policies enforced at these scales (e.g., the closure of borders and lockdowns) to observe their impacts on the epidemiology.
TL;DR: In this article , mobile phone activity-based digital contact tracing (DCT) via Bluetooth low energy technology has been considered a powerful pandemic monitoring tool, yet it sparked a controversial debate about privacy risks for people.
Abstract: The COVID-19 pandemic and its dramatic worldwide impact has required global multidisciplinary actions to mitigate its effects. Mobile phone activity-based digital contact tracing (DCT) via Bluetooth low energy technology has been considered a powerful pandemic monitoring tool, yet it sparked a controversial debate about privacy risks for people. In order to explore the potential benefits of a DCT system in the context of occupational risk prevention, this article presents the potential of visual analytics methods to summarize and extract relevant information from complex DCT data collected during a long-term experiment at our research center. Visual tools were combined with quantitative metrics to provide insights into contact patterns among volunteers. Results showed that crucial actors, such as participants acting as bridges between groups could be easily identified—ultimately allowing for making more informed management decisions aimed at containing the potential spread of a disease.
TL;DR: The authors in this paper presented a curated multiscale geospatial dataset with an interactive visualization dashboard under the context of COVID-19, which enables users to visualize the spread of the disease at different scales and allow users to interact with the policies enforced at these scales to observe their impacts on the epidemiology.
Abstract: The coronavirus disease (COVID-19) continued to strike as a highly infectious and fast-spreading disease in 2020 and 2021. As the research community actively responded to this pandemic, we saw the release of many COVID-19-related datasets and visualization dashboards. However, existing resources are insufficient to support multiscale and multifaceted modeling or simulation, which is suggested to be important by the computational epidemiology literature. This work presents a curated multiscale geospatial dataset with an interactive visualization dashboard under the context of COVID-19. This open dataset will allow researchers to conduct numerous projects or analyses relating to COVID-19 or simply geospatial-related scientific studies. The interactive visualization platform enables users to visualize the spread of the disease at different scales (e.g., country level to individual neighborhoods), and allows users to interact with the policies enforced at these scales (e.g., the closure of borders and lockdowns) to observe their impacts on the epidemiology.