Spatial data analysis is essential in domains such as construction, architecture, and geodesy, to check for differences between construction stages of a building. In this context, real-world environments are often digitally recorded as point clouds, providing a basis for digital processing and analysis. Furthermore, aspects of spatial cognition, often measured with eye tracking, are also relevant to many research questions related to how people perceive and understand space and spatial structures, e.g., in quality inspection of construction sites or buildings. We present a workflow to combine eye tracking and point cloud data to analyze user attention during inspection of spatial data in virtual environments. This type of data enrichment enables the deployment of established open-source software for cloud and mesh processing to analyze eye tracking data. Our workflow employs the investigation of point cloud data and simultaneous user gaze recording in virtual reality, followed by point-based gaze data analysis, interactive visualization, and authoring and production of high-quality dissemination materials for stakeholders. We showcase our approach with a usage scenario on how people investigate the construction of a pavilion building in virtual reality.
The eyes play an important role in human collaboration. Mutual and shared gaze help communicate visual attention to each other or to a specific object of interest. Shared gaze was typically investigated for pair collaborations in remote settings and with people in virtual and augmented reality. With our work, we expand this line of research by a new technique to communicate gaze between groups in tabletop workshop scenarios. To achieve this communication, we use an approach based on projection mapping to unify gaze data from multiple participants into a common visualization space on a tabletop. We showcase our approach with a collaborative puzzle-solving task that displays shared visual attention on individual pieces and provides hints to solve the problem at hand.
Point clouds are used to measure and assess building processes in areas such as architecture, engineering, and construction. Precise spatial measurements can inform about deviations from a baseline, and the increasing use of sensor data in the context of building information modeling leads to multiple scalar fields containing rich information of individual spatial points. We propose an immersive approach to investigate such multivariate point cloud data from scans of buildings. We compare a switching approach that provides an overview of individual scalar fields with a spotlight that provides local information about all fields simultaneously. Furthermore, locomotion is compared for such immersive analysis with teleportation and with an omnidirectional treadmill. Our results show a preference for free movement and a task-dependence of visualization approaches for the inspection of scalar fields.
The depiction of scanpaths from mobile eye-tracking recordings by thumbnails from the stimulus allows the application of visual computing to detect areas of interest in an unsupervised way. We suggest using nonnegative matrix factorization (NMF) to identify such areas in stimuli. For a user-defined integer k, NMF produces an explainable decomposition into k components, each consisting of a spatial representation associated with a temporal indicator. In the context of multiple eye-tracking recordings, this leads to k spatial representations, where the temporal indicator highlights the appearance within recordings. The choice of k provides an opportunity to control the refinement of the decomposition, i.e., the number of areas to detect. We combine our NMF-based approach with visualization techniques to enable an exploratory analysis of multiple recordings. Finally, we demonstrate the usefulness of our approach with mobile eye-tracking data of an art gallery.
Gaming consoles, whether stationary or handheld, are designed to provide a reasonably high level of computing power to run contemporary video games at an attractive price point, a compact form factor and modest energy consumption. While consoles have traditionally been closed-off systems, recent versions of the Xbox allow the development of apps for the Universal Windows Platform (UWP) on retail devices, making it potentially a suitable platform for bringing scientific visualisation (SciVis) applications to the masses. We describe how to run such applications, namely volume rendering and ray casting of spherical glyphs, on commodity gaming systems, not only on the Xbox Series X/S, but also on handheld devices like the Steam Deck. We detail the challenges and limitations we encountered during the implementation and provide the results of an extensive study of rendering performance, not only proving the viability of the approach but also allowing for a cost and benefit evaluation compared to standard desktop computers.
Data visualization relies on efficient rendering to allow users to interactively explore and understand their data. However, achieving interactive frame rates is often challenging, especially for high-resolution displays or large datasets. In computer graphics, several methods temporally reconstruct full-resolution images from multiple consecutive lower-resolution frames. Besides providing temporal image stability, they amortize the rendering costs over multiple frames and thus improve the minimum frame rate. We present a method that adopts this idea to accelerate 2D information visualization, without requiring any changes to the rendering itself. By exploiting properties of orthographic projection, our method significantly improves rendering performance while minimizing the loss of image quality during camera manipulation. For static scenes, it quickly converges to the full-resolution image. We discuss the characteristics and different modes of our method concerning rendering performance and image quality and the corresponding trade-offs. To improve ease of use, we provide automatic resolution scaling in our method to adapt to user-defined target frame rate. Finally, we present extensive rendering benchmarks to examine real-world performance for examples of parallel coordinates and scatterplot matrix visualizations, and discuss appropriate application scenarios and contraindications for usage.
In architecture, engineering, and construction (AEC), load-bearing truss structures are commonly modeled as a set of connected beam elements. For complex 3D structures, rendering beam elements as line segments presents several challenges due densely overlapping elements, including visual clutter, and general depth perception issues. Furthermore, line segments provide very little area for displaying additional element attributes. In this paper, we investigate the effectiveness of rendering effects for reducing visual clutter and improving depth perception for truss structures specifically, such as distance-based brightness attenuation and screen-space ambient occlusion (SSAO). Additionally, we provide multiple options for multi-attribute visualization directly on the structure and evaluate both aspects with two expert interviews. CCS Concepts • Computing methodologies → Rendering; • Human-centered computing → Visualization;
Augmented reality (AR) technology provides means for embedding visualization in a real-world context. Such techniques allow situated analyses of live data in their spatial domain. However, as existing techniques have to be adapted for this context and new approaches will be developed, the evaluation thereof poses new challenges for researchers. Apart from established performance measures, eye tracking has proven to be a valuable means to assess visualizations qualitatively and quantitatively. We discuss the challenges and opportunities of eye tracking for the evaluation of situated visualizations. We envision that an extension of gaze-based evaluation methodology into this field will provide new insights on how people perceive and interact with visualizations in augmented reality.
Modern machines continuously log status reports over long periods of time, which are valuable data to optimize working routines. Data visualization is a commonly used tool to gain insights into these data, mostly in retrospective (e.g., to determine causal dependencies between the faults of different machines). We present an approach to bring such visual analyses to the shop floor to support reacting to faults in real time. This approach combines spatio-temporal analyses of time series using a handheld touch device with augmented reality for live monitoring. Important information augments machines directly in their real-world context, and detailed logs of current and historical events are displayed on the handheld device. In collaboration with an industry partner, we designed and tested our approach on a live production line to obtain feedback from operators. We compare our approach for monitoring and analysis with existing solutions that are currently deployed.
Our built world is one of the most important factors for a livable future, accounting for massive impact on resource and energy use, as well as climate change, but also the social and economic aspects that come with population growth. The architecture, engineering, and construction industry is facing the challenge that it needs to substantially increase its productivity, let alone the quality of buildings of the future. In this article, we discuss these challenges in more detail, focusing on how digitization can facilitate this transformation of the industry, and link them to opportunities for visualization and augmented reality research. We illustrate solution strategies for advanced building systems based on wood and fiber.
Simulations of cosmic evolution are a means to explain the formation of the universe as we see it today. The resulting data of such simulations comprise numerous physical quantities, which turns their analysis into a complex task. Here, we analyze such high-dimensional and time-varying particle data using various visualization techniques from the fields of particle visualization, flow visualization, volume visualization, and information visualization. Our approach employs specialized filters to extract and highlight the development of so-called active galactic nuclei and filament structures formed by the particles. Additionally, we calculate X-ray emission of the evolving structures in a preprocessing step to complement visual analysis. Our approach is integrated into a single visual analytics framework to allow for analysis of star formation at interactive frame rates. Finally, we lay out the methodological aspects of our work that led to success at the 2019 IEEE SciVis Contest.
We introduce inverted stippling , a method to mimic an inversion technique used by artists when performing stippling. To this end, we extend Linde-Buzo-Gray (LBG) stippling to multi-class LBG (MLBG) stippling with multiple layers. MLBG stippling couples the layers stochastically to optimize for per-layer and overall blue-noise properties. We propose a stipple-based filling method to generate solid color backgrounds for inverting areas. Our experiments demonstrate the effectiveness of MLBG in terms of reducing overlapping and intensity accuracy. In addition, we showcase MLBG with color stippling and dynamic multi-class blue-noise sampling, which is possible due to its support for temporal coherence.
Visualization in virtual 3D environments can provide a natural way for users to explore data. Often, arm and short head movements are required for interaction in augmented reality, which can be tiring and strenuous though. In an effort toward more user-friendly interaction, we developed a prototype that allows users to manipulate virtual objects using a combination of eye gaze and an external clicker device. Using this prototype, we performed a user study comparing four different input methods of which head gaze plus clicker was preferred by most participants.
Gaze tracking in 3D has the potential to improve interaction with objects and visualizations in augmented reality. However, previous research showed that subjective perception of distance varies between real and virtual surroundings. We wanted to determine whether objectively measured 3D gaze depth through eye tracking also exhibits differences between entirely real and augmented environments. To this end, we conducted an experiment (N = 25) in which we used Microsoft HoloLens with a binocular eye tracking add-on from Pupil Labs. Participants performed a task that required them to look at stationary real and virtual objects while wearing a HoloLens device. We were not able to find significant differences in the gaze depth measured by eye tracking. Finally, we discuss our findings and their implications for gaze interaction in immersive analytics, and the quality of the collected gaze data.
The IEEE SciVis 2019 Contest targets the visual analysis of structure formation in the cosmic evolution of the universe from when the universe was five million years old up to now. In our submission, we analyze high-dimensional data to get an overview, then investigate the impact of Active Galactic Nuclei (AGNs) using various visualization techniques, for instance, an adapted filament filtering method for detailed analysis and particle flow in the vicinity of filaments. Based on feedback from domain scientists on these initial visualizations, we also analyzed X-ray emissions and star formation areas. The conversion of star-forming gas to stars and the resulting increasing molecular weight of the particles could be observed.
We present MegaMol, a low-overhead prototyping framework for interactive visualization of large scientific data sets. We give a brief summary of related work for context and then focus on a comprehensive overview of the core architecture of the framework. This is followed by the existing and novel features and techniques in MegaMol that define its current functionality. MegaMol has originally been developed to support the visualization and analysis of particle-based data sets that, for instance, come from molecular dynamics simulations. Meanwhile, the software has evolved beyond that. New algorithms and techniques have been implemented to handle many diverse tasks, including information visualization. Additionally, improvements have been made on the software engineering side to make MegaMol more accessible for domain scientists, like an easy-to-handle scripting interface.
Two-dimensional height fields are the most common data structure used for storing and rendering of terrain in offline rendering and especially real-time computer graphics. By its very nature, a height field cannot store terrain structures with multiple vertical layers such as overhanging cliffs, caves, or arches. This restriction does not apply to volumetric data structures. However, the workflow of manual modelling and editing of volumetric terrain usually is tedious and very time-consuming. Therefore, we propose to use three-dimensional curve-based primitives to efficiently model prominent, large-scale terrain features. We present a technique for volumetric generation of a complete terrain surface from the sparse input data by means of diffusion-based algorithms. By combining an efficient, feature-based toolset with a volumetric terrain representation, the modelling workflow is accelerated and simplified while retaining the full artistic freedom of volumetric terrains. Feature Curves also contain material information that can be complemented with local details by using per-face texture mapping. All stages of our method are GPU-accelerated using compute shaders to ensure interactive editing of terrain. Please note that this paper is an extended version of our previously published work [1] .
In this paper, we present the design considerations of a scientific exhibition we recently realized. The exhibition presented the work of two large research projects related to computer simulations, which include scientific visualization as an essential part of the involved research. Consequently, visualization was also of central importance for our exhibition. It was not only used to illustrate the complex simulation data to convey information about the results from the application domains, but we also wanted to teach visitors about visualization itself. Therefore, explaining the purpose and the challenges of visualization research was a significant part of the exhibition. We describe how we developed an engaging experience of a highly theoretic topic using the same visualization tools we developed for the application scientists and how we integrated the venue into our design. Finally, we discuss our insights from the project as well as visitor feedback.
Given a set of prioritized balls with fixed centers in ℝd whose radii grow linearly over time, we want to compute the elimination order of these balls assuming that when two balls touch, the one with lower priority is 'crushed'. A straightforward algorithm has running time O(n2 log n) which we improve to expected O(Δdn(log n + Δd)) where Δ = rmax/rmin is the ratio between largest and smallest radius amongst the balls. For a natural application of this problem, namely drawing labels on the globe, we have Δ = O(1). An efficient implementation based on a spherical Delaunay triangulation allows to compute the elimination order for millions of labels on commodity Desktop hardware. Dealing with rounding error induced robustness issues turned out to be one of the major challenges in the implementation.
Visualization of dynamic data from molecular dynamics simulations is crucial for understanding the functioning of molecules. Many existing visualization tools have mainly focused on supporting a single user working on a desktop computer. Technical advancements in browser features increase the potential for the development of web-based collaborative visualization tools. Although web-based molecular viewers already exist, their support for dynamic molecular data at interactive rates is lacking. To address this gap, we present an efficient web application for visualization of dynamic molecular data using WebGL that exploits HTML5 technologies like WebSockets and Web Workers. GPU-based ray casting techniques offer fast rendering times and produce images with higher visual quality. Efficient data encoding techniques are used to minimize the data transferred to the client; therefore saving bandwidth and improving the transfer times. We demonstrate the feasibility of visualizing large dynamic molecular data with more than one million atoms in the browser at interactive frame rates. Our approach allows scientists at arbitrary locations to concurrently visually analyze the same data. The interactive parameterization of the visualization can be shared among multiple clients, providing the basis for collaborative research. Moreover, the application can be employed for remote simulation monitoring on mobile devices. (C) 2016 Elsevier Inc. All rights reserved.