Large-scale Virtual Environments Research Articles

Does viewing an environment without occluders improve spatial learning of a large-scale virtual environment?

This study tested the effect of providing a vista view of a large-scale environment on spatial learning. During normal navigation, we can only perceive limited regions at a time. To learn the spatial layout, we would have to integrate information from multiple views. If an unoccluded view of the full environment was displayed (vista view), would this improve spatial learning? We tested this experimentally using VR in two pre-registered experiments. We created vista views of urban environments by compressing the height of most non-target buildings, allowing participants to see the whole space and configuration of target buildings from an egocentric perspective. In Experiment 1 (N = 32), the vista view was presented during travel to each target on learning trials. In Experiment 2 (N = 36), the vista view was presented for 10s in a preview period before each learning trial. After the learning phase, they were tested on judgments of relative direction (JRD) to measure survey knowledge, and wayfinding to measure route knowledge. We hypothesized that the vista views would improve survey knowledge by allowing participants to directly observe the locations of targets relative to each other and global landmarks, but there might be little or no benefit for route knowledge. Surprisingly, even though the vista view allowed participants to see the configuration of targets at once, there was no improvement in JRD or wayfinding performance compared to the normal condition where visibility is limited to local regions. Our results suggest that a street-level unoccluded view may have limited benefit for learning a large-scale environment through navigation.

Evaluating the effects of a programming error on a virtual environment measure of spatial navigation behavior.

Relying on shared tasks and stimuli to conduct research can enhance the replicability of findings and allow a community of researchers to collect large data sets across multiple experiments. This approach is particularly relevant for experiments in spatial navigation, which often require the development of unfamiliar large-scale virtual environments to test participants. One challenge with shared platforms is that undetected technical errors, rather than being restricted to individual studies, become pervasive across many studies. Here, we discuss the discovery of a software bug in a virtual environment platform used to investigate individual differences in spatial navigation: Virtual Silcton. The bug, which was difficult to detect for several reasons, resulted in storing the absolute value of a direction in a pointing task rather than the signed direction and rendered the original sign of the direction unrecoverable. To assess the impact of the bug on published findings, we collected a new data set for comparison. Results revealed that although the bug caused suppression in pointing errors and had different effects across people (less accurate navigators had more suppression), the effect of the bug on published data is small, partially explaining the difficulty in detecting the bug. We also used the new data set to develop a tool that allows researchers who have previously used Virtual Silcton to evaluate the impact of the bug on their findings. We summarize the ways that shared open materials, shared data, and collaboration can pave the way for better science to prevent errors in the future. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Linear kitchen layout design via machine learning

AbstractThe main objective of this paper is to develop a novel approach for linear kitchen layout design which utilizes information from existing layouts via machine learning algorithms. With the growing popularity of large-scale virtual 3D environments for architectural visualization and the game industry, the manual interior design of virtual scenes becomes prohibitively expensive in terms of time and resources. In our approach, the machine learning model automatically generates layout suggestions. The proposed procedural kitchen generation (PKG) model is a pipeline of six Machine Learning (ML) classifiers that are trained and tested on a kitchen layout dataset created by interior designers. The performances of the model are evaluated for the following classifiers: Random forest, Decision tree, AdaBoost, Naive Bayes, MLP, SVM, and L2 Logistic regression. Random forest, as the best performing classifier is used in the final PKG model, and integrated into Unity Engine for automatic 3D kitchen generation and presentation. The PKG model is evaluated in the quantitative and perceptual study, showing better performance than the prior rule-based method. The perceptual study results demonstrate that our tool can be used to speed up designer's work, improve communication with clients, and educate interior design students.

VISmaF: Synthetic Tree for Immersive Virtual Visualization in Smart Farming. Part I: Scientific Background Review and Model Proposal

Computer-Generated Imagery (CGI) has received increasing interest in both research and the entertainment industry. Recent advancements in computer graphics allowed researchers and companies to create large-scale virtual environments with growing resolution and complexity. Among the different applications, the generation of biological assets is a relevant task that implies challenges due to the extreme complexity associated with natural structures. An example is represented by trees, whose composition made by thousands of leaves, branches, branchlets, and stems with oriented directions is hard to be modeled. Realistic 3D models of trees can be exploited for a wide range of applications including decision-making support, visualization of ecosystem changes over time, and for simple visualization purposes. In this review, we give an overview of the most common approaches used to generate 3D tree models, discussing both methodologies and available commercial software. We focus on strategies for modeling and rendering of plants, highlighting their accordance or not with botanical knowledge and biological models. We also present a proof of concept to link biological models and 3D rendering engines through Ordinary Differential Equations.

Hierarchical and smoothed topographic path planning for large-scale virtual simulation environments

Virtual simulation systems ought to make the most of agents’ realistic behaviors so that users feel immersed in virtual scenarios that mimic the real-world environment. Usually used for training and instruction purposes, agent-based simulations have additional requirements to be considered by the Artificial Intelligence solutions often explored in the development of computer games. To provide a valuable impression of how the simulated agents navigate in the real-world terrain, one of the key requirements indicates that topographic terrain characteristics need to be considered in the path planning tasks. It means that important aspects of the agents’ navigation capabilities have to be properly handled by the used pathfinding algorithms. This problem is even more challenging when large-scale terrain scenarios are considered in state-of-the-art simulation systems as the path planning may be too time-consuming when handling terrain representations with large search spaces. To approach the challenge of computing safe and realistic path solutions for agents inserted in simulation-based learning environments, this work discusses a hierarchical pathfinding algorithm named HPATheta*, showing how to compute terrain relief-aware smoothed paths in reasonable computing time when dealing with path planning in large-scale real-world virtual terrains. Using different simulated real-world virtual terrains, the proposal is validated by performing an extensive experimental campaign with the use of large-scale virtual terrain representations. The experimental results indicate that the proposed approach is able to efficiently address the targeted problem, showing better results compared to other similar path planning algorithms.

Representing and Generating Maps of Large-Scale Virtual Environments for Intelligent Mobile Agents

This paper looks at the challenges and solutions for intelligent mobile agents existing in virtual environments. Representing and using a map of these very large-scale, dynamic environments is a key challenge in providing an autonomous agent for large, online worlds. We look at a method for improving the generation of probabilistic roadmaps by observing and using the movements of other avatars in an environment. We also look at methods for segmenting and scaling the map in very large environments. Finally we extend this to look at generating and updating maps in dynamic environments.

Open Source Framework for Enabling HPC and Cloud Geoprocessing Services

Geoprocessing is a set of tools that can be used to efficiently address several pressing chal-lenges for the global economy ranging from agricultural productivity, the design of transport networks, to the prediction of climate change and natural disasters. This paper describes an Open Source Framework developed, within three European projects, for Ena-bling High-Performance Computing (HPC) and Cloud geoprocessing services applied to agricultural challenges. The main goals of the European Union projects EUXDAT (EUro-pean e-infrastructure for eXtreme Data Analytics in sustainable developmenT), CYBELE (fostering precision agriculture and livestock farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable big data analytics), and EOPEN (opEn interOperable Platform for unified access and analysis of Earth observatioN data) are to enable the use of large HPC systems, as well as big data management, user-friendly access and visualization of results. In addition, these projects focus on the development of software frameworks, and fuse Earth-observation data, such as Copernicus data, with non-Earth-observation data, such as weather, environmental and social media information. In this paper, we describe the agroclimatic-zones pilot used to validate the framework. Finally, performance metrics collected during the execution (up to 182 times speedup with 256 MPI processes) of the pilot are presented.

Two Decades of Touchable and Walkable Virtual Reality for Blind and Visually Impaired People: A High-Level Taxonomy

Although most readers associate the term virtual reality (VR) with visually appealing entertainment content, this technology also promises to be helpful to disadvantaged people like blind or visually impaired people. While overcoming physical objects’ and spaces’ limitations, virtual objects and environments that can be spatially explored have a particular benefit. To give readers a complete, clear and concise overview of current and past publications on touchable and walkable audio supplemented VR applications for blind and visually impaired users, this survey paper presents a high-level taxonomy to cluster the work done up to now from the perspective of technology, interaction and application. In this respect, we introduced a classification into small-, medium- and large-scale virtual environments to cluster and characterize related work. Our comprehensive table shows that especially grounded force feedback devices for haptic feedback (‘small scale’) were strongly researched in different applications scenarios and mainly from an exocentric perspective, but there are also increasingly physically (‘medium scale’) or avatar-walkable (‘large scale’) egocentric audio-haptic virtual environments. In this respect, novel and widespread interfaces such as smartphones or nowadays consumer grade VR components represent a promising potential for further improvements. Our survey paper provides a database on related work to foster the creation process of new ideas and approaches for both technical and methodological aspects.

Searching for individual determinants of probabilistic cueing in large-scale immersive virtual environments

Large-scale search behaviour is an everyday occurrence, yet its underlying mechanisms are not commonly examined within experimental psychology. Key to efficient search behaviour is the sensitivity to environmental cues that might guide exploration, such as a target appearing with greater regularity in one region than another. Spatial cueing by probability has been examined in visual search paradigms, but the few studies that have addressed its contribution to large-scale search and foraging present contrasting accounts of the conditions under which a cueing effect can be reliably observed. In the present study, participants physically searched a virtual arena by inspecting identical locations until they found the target. The target was always present, although its location was probabilistically defined so that it appeared in the cued hemispace on 80% of trials. In Experiment 1, when participants’ starting positions were stable, a probabilistic cueing effect was observed, with a strong bias towards searching the cued side. In Experiment 2, the starting position changed across the experiment, such that the cued region was defined in allocentric co-ordinates only. In this case, a probabilistic cueing effect was not observed across the sample. Analysis of individual differences in Experiment 2 suggests, however, that some participants may have learned the contingency underpinning the target’s location, although these differences were unrelated to other tests of visuospatial ability. These results suggest that the ability to learn the likelihood of an item’s fixed location when starting from different perspectives is driven by individual differences in other cognitive or perceptual factors.

The role of perception and action on the use of allocentric information in a large-scale virtual environment

In everyday life, our brain constantly builds spatial representations of the objects surrounding us. Many studies have investigated the nature of these spatial representations. It is well established that we use allocentric information in real-time and memory-guided movements. Most studies relied on small-scale and static experiments, leaving it unclear whether similar paradigms yield the same results on a larger scale using dynamic objects. We created a virtual reality task that required participants to encode the landing position of a virtual ball thrown by an avatar. Encoding differed in the nature of the task in that it was either purely perceptual (“view where the ball landed while standing still”—Experiment 1) or involved an action (“intercept the ball with the foot just before it lands”—Experiment 2). After encoding, participants were asked to place a real ball at the remembered landing position in the virtual scene. In some trials, we subtly shifted either the thrower or the midfield line on a soccer field to manipulate allocentric coding of the ball’s landing position. In both experiments, we were able to replicate classic findings from small-scale experiments and to generalize these results to different encoding tasks (perception vs. action) and response modes (reaching vs. walking-and-placing). Moreover, we found that participants preferably encoded the ball relative to the thrower when they had to intercept the ball, suggesting that the use of allocentric information is determined by the encoding task by enhancing task-relevant allocentric information. Our findings indicate that results previously obtained from memory-guided reaching are not restricted to small-scale movements, but generalize to whole-body movements in large-scale dynamic scenes.

The MARquette Visualization Lab (MARVL): An Immersive Virtual Environment for Research, Teaching and Collaboration

The MARquette Visualization Lab (MARVL) is a large-scale immersive virtual environment for research, teaching, collaboration and outreach at our mid-sized liberal arts university. MARVL consists of multiple display surfaces including an extra wide front wall and floor, and two side walls. This resource includes stereoscopic viewing, motion tracking and space for a large audience. MARVL’s versatile configuration facilitates viewing of content by 30 people, while also projecting on the entire width of the floor. This feature uniquely facilitates comparative or separate content visible simultaneously via 'split mode' operation (two 3-sided environments), as well as detailed motion for applications such as gait analysis and performing arts. Since establishing the lab, its members have received numerous queries and requests pertaining to how system attributes and applications were determined, suggesting these and related decisions remain a challenge nearly 3 decades since the first CAVE was constructed. This paper provides an overview of MARVL including the processes used in identifying a diverse group of cross campus users, understanding their collective vision for potential use, and synthesizing this information to create the resource described above. The subsequent design, qualitative and quantitative approaches to vendor selection, and software decisions are then discussed. Steps implemented for dealing with simulator sickness and latency are presented along with current approaches being implemented for project development with end-users. Finally, we present results from the use of MARVL by several end-users identified in the early planning stages, and recent upgrades to the system.

Evaluating the user experience of omnidirectional VR walking simulators

Omnidirectional treadmills (ODTs) have been traditionally proposed as a promising solution for users’ navigation in large-scale virtual environments. These mechanical devices enable users to perform locomotive motion with 360-deg freedom, while keeping their position fixed in the physical world. However, most locomotion approaches based on omnidirectional treadmills have presented either high acquisition or maintenance costs, being the capabilities of the general public, or a limited reliability. In this paper, we present a comparative usability and acceptance study with real users evaluating the two most common approaches for the development of this type of Virtual Reality (VR) walking simulators, whether flat-based or bowl-based omnidirectional treadmills. The results of our study indicate that both design alternatives accomplish a similar performance and can be considered as personal, low-cost walking simulators for navigation in virtual environments. Nevertheless, when compared between themselves, the users preferred the bowl-based omnidirectional VR treadmill when following three different selection criteria: overall preference, recommendation, and usefulness. Last, a correlation analysis showed statically significant correspondences among the parameters concerning to the simulation presence, which in turn, are related to the global scores and responses given by the participants of the Virtual Reality experiment.

User perspective and higher cognitive task-loads influence movement and performance in immersive training environments

BackgroundIn virtual reality (VR) applications such as games, virtual training, and interactive neurorehabilitation, one can employ either the first-person user perspective or the third-person perspective to perceive the virtual environment; however, applications rarely offer both perspectives for the same task. We used a targeted-reaching task in a large-scale virtual reality environment (N=30 healthy volunteers) to evaluate the effects of user perspective on the head and upper extremity movements, and on user performance. We further evaluated how different cognitive challenges would modulate these effects. Finally, we obtained the user-reported engagement level under the different perspectives.ResultsWe found that first-person perspective resulted in larger head movements (3.52±1.3m) than the third-person perspective (2.41±0.7m). First-person perspective also resulted in more upper-extremity movement (30.08±7.28m compared to 26.66±4.86m) and longer completion times (61.3±16.4s compared to 53±10.4s) for more challenging tasks such as the “flipped mode”, in which moving one arm causes the opposite virtual arm to move. We observed no significant effect of user perspective alone on the success rate. Subjects reported experiencing roughly the same level of engagement in both first-person and third-person perspectives (F(1.58)=0.9,P=.445).ConclusionUser perspective and its interaction with higher-cognitive load tasks influences the extent of movement and user performance in a virtual theater environment, and may influence the choice of the interface type (first or third person) in immersive training depending on the user conditions and exercise requirements.

Learning-dependent evolution of spatial representations in large-scale virtual environments.

An important question regards how we use environmental boundaries to anchor spatial representations during navigation. Behavioral and neurophysiological models appear to provide conflicting predictions, and this question has been difficult to answer because of technical challenges with testing navigation in novel, large-scale, realistic spatial environments. We conducted an experiment in which participants freely ambulated on an omnidirectional treadmill while viewing novel, town-sized environments in virtual reality on a head-mounted display. Participants performed interspersed judgments of relative direction (JRD) to assay their spatial knowledge and to determine when during learning they employed environmental boundaries to anchor their spatial representations. We designed JRD questions that assayed directions aligned and misaligned with the axes of the surrounding rectangular boundaries and employed structural equation modeling to better understand the learning-dependent dynamics for aligned versus misaligned pointing. Pointing accuracy showed no initial directional bias to boundaries, although such "alignment effects" did emerge after the fourth block of learning. Preexposure to a map in Experiment 2 led to similar overall findings. A control experiment in which participants studied a map but did not navigate the environment, however, demonstrated alignment effects after a brief, initial learning experience. Our results help to bridge the gap between neurophysiological models of location-specific firing in rodents and human behavioral models of spatial navigation by emphasizing the experience-dependent accumulation of route-specific knowledge. In particular, our results suggest that the use of spatial boundaries as an organizing schema during navigation of large-scale space occurs in an experience-dependent fashion. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Selective resetting position and heading estimations while driving in a large-scale immersive virtual environment.

Two experiments investigated how self-motion cues and landmarks interact in determining a human's position and heading estimations while driving in a large-scale virtual environment by controlling a gaming wheel and pedals. In an immersive virtual city, participants learned the locations of five buildings in the presence of two proximal towers and four distal scenes. Then participants drove two streets without viewing these buildings, towers, or scenes. When they finished driving, either one tower with displacement to the testing position or the scenes that had been rotated reappeared. Participants pointed in the directions of the five buildings. The least squares fitting method was used to calculate participants' estimated positions and headings. The results showed that when the displaced proximal tower reappeared, participants used this tower to determine their positions, but used self-motion cues to determine their headings. When the rotated distal scenes reappeared, participants used these scenes to determine their headings. If they were instructed to continuously keep track of the origin of the path while driving, their position estimates followed self-motion cues, whereas if they were not given instructions, their position estimates were undetermined. These findings suggest that when people drive in a large-scale environment, relying on self-motion cues, path integration calculates headings continuously but calculates positions only when they are required; relying on the displaced proximal landmark or the rotated distal scenes, piloting selectively resets the position or heading representations produced by path integration.

Automatic Procedural 3d Modelling of Buildings

The problem of modelling, especially of large-scale virtual urban environments such as city areas is today very challenging for cartographers. Cities are difficult to model in detail because of their often complex geometries. This paper describes the applied and tested new procedures for the development of a test three-dimensional urban area model using the Esri CityEngine software, which is based on procedural modelling. This process involves three steps. The first step is to collect the available data, as well as the Digital Model Relief data. The second step is to create a Computer Generated Architecture (CGA) file that contains a set of rules used by the software for an automatic generation of the model. The third step is to create and visualize 3D models in the CityEngine software because it can be programmed, for example, according to the rules of cartographic visualization. The Level of Detail (LOD) 2 was reconstructed. Several potential uses of such 3D visualization are also described.

THE VIRTUAL TOURIST: COGNITIVE STRATEGIES AND DIFFERENCES IN NAVIGATION AND MAP USE WHILE EXPLORING AN MAGINARY CITY

Abstract. This paper, submitted for the Workshop/Theme session on Virtual & Augmented Reality: Technology, Design & Human Factors, organized by ISPRS Working Group IV/9, explores the research field opened by experiments in virtual environments from multidisciplinary approach. At the recently established Cognitive Cartography Lab, Eötvös University, Budapest we designed an experiment to study and better understand the role of visuospatial displays in spatial cognition, in particular the cognitive conditions of navigation in an imaginary city with a map. Below we present some preliminary results based on our experiments recording the spatial behaviour of 62 subjects, including their verbal reactions and eye tracking data collected during the sessions. We measured the wayfinding behaviour of participants after an active or passive learning phase. The analysis of the accumulated data suggested no significant differences in the efficiency of spatial problem solving between the groups of subjects. For further investigation we found that – although salient visual cues grasped the attention of the participants – they could not benefit from this knowledge of landmarks in the actual navigational tasks. Despite the lack of group differences, the low number of getting lost in such complex, large-scale virtual environment suggests that participants could solve the navigational tasks rather efficiently, most probably due to using different cognitive strategies. The project was part of an educational development plan and was supported by the Student Talent Grant of Eötvös University. It was designed by a multidisciplinary research group including university students and offered them the opportunity to collaborate, cross disciplinary borders and develop their profile when contributing to front-line scientific research.

Repetitive transcranial magnetic stimulation reveals a causal role of the human precuneus in spatial updating

As we move through an environment, the positions of surrounding objects relative to our body constantly change, with some objects even leaving our field of view. As a consequence, maintaining orientation requires spatial updating, the continuous monitoring of self-motion cues to update external locations within an egocentric frame of reference. While previous research using functional magnetic resonance imaging has implicated the precuneus in spatial updating, direct evidence for this claim is missing. To address this important question, we applied theta burst repetitive transcranial magnetic stimulation (rTMS) over the precuneus to induce a “virtual lesion”. Following stimulation, participants were tested in a large-scale virtual environment in which they had to use visual self-motion information to keep track of the position of virtual objects. Compared to sham stimulation, rTMS affected working memory traces for object locations. Critically, rTMS further impaired the ability to update these locations whenever participants experienced simulated movement. As this effect could not be explained by working memory deficits alone, we conclude that visual spatial updating relies on the construction of updated representations of egocentric object locations within the precuneus. Together, these findings establish the precuneus as performing key computations for the formation of cognitive maps.

FiVES: an aspect-oriented approach for shared virtual environments in the web

Virtual Environments have become a compelling tool for various applications beyond gaming and Virtual Worlds, for example, for education, collaborative engineering, or simulation and visualization. In the emerging field of smart environments, like Smart Cities and Smart Factories for industry or agriculture, a digital counterpart of a real-world site, driven by hundreds of Internet of Things sensors that emit their data in real-time, is a central part of the application. Maintaining such a large-scale virtual environment and keeping it up-to-date with changing requirements set by connected sensors and services is a challenge. For this, we present FiVES, a server framework that is based on an aspect-oriented architecture to create highly maintainable large-scale virtual environments by avoiding cross-cutting concerns like tangling or scattering of code between modules in resulting applications. We present a fully functional implementation of our system that builds on an extendable and versatile data model, a flexible plugin mechanism, and a transparent yet efficient synchronization layer that is independent of the modules from which applications are assembled.

On the (a)symmetry between the perception of time and space in large-scale environments.

Cross-dimensional interference between spatial and temporal processing is well documented in humans, but the direction of these interactions remains unclear. The theory of metaphoric structuring states that space is the dominant concept influencing time perception, whereas time has little effect upon the perception of space. In contrast, theories proposing a common neuronal mechanism representing magnitudes argue for a symmetric interaction between space and time perception. Here, we investigated space-time interactions in realistic, large-scale virtual environments. Our results demonstrate a symmetric relationship between the perception of temporal intervals in the supra-second range and room size (experiment 1), but an asymmetric relationship between the perception of travel time and traveled distance (experiment 2). While the perception of time was influenced by the size of virtual rooms and by the distance traveled within these rooms, time itself affected only the perception of room size, but had no influence on the perception of traveled distance. These results are discussed in the context of recent evidence from rodent studies suggesting that subsets of hippocampal place and entorhinal grid cells can simultaneously code for space and time, providing a potential neuronal basis for the interactions between these domains.