LoCoMoTe – a framework for classification of natural locomotion in VR by task, technique and modality

Virtual reality (VR) research has provided overviews of locomotion techniques, how they work, their strengths and overall user experience. Considerable research has investigated new methodologies, particularly machine learning to develop redirection algorithms. To best support the development of redirection algorithms through machine learning, we must understand how best to replicate human navigation and behaviour in VR, which can be supported by the accumulation of results produced through live-user experiments. However, it can be difficult to identify, select and compare relevant research without a pre-existing framework in an ever-growing research field. Therefore, this work aimed to facilitate the ongoing structuring and comparison of the VR-based natural walking literature by providing a standardised framework for researchers to utilise. We applied thematic analysis to study methodology descriptions from 140 VR-based papers that contained live-user experiments. From this analysis, we developed the LoCoMoTe framework with three themes: navigational decisions, technique implementation, and modalities. The LoCoMoTe framework provides a standardised approach to structuring and comparing experimental conditions. The framework should be continually updated to categorise and systematise knowledge and aid in identifying research gaps and discussions

Sensitivity to Rate of Change in Gains Applied by Redirected Walking

Redirected walking allows for natural locomotion in virtual environments that are larger than a user’s physical environment. The mapping between real and virtual motion is modified by scaling some aspect of motion. As a user traverses the virtual environment these modifications (or gains) must be dynamically adjusted to prevent collision with physical obstacles. A significant body of work has established perceptual thresholds on rates of absolute gain, but the effect of changing gain is little understood. We present the results of a user study on the effects of rate of gain change. A psychophysical experiment was conducted with 21 participants. Each participant completed a series of two-alternative forced choice tasks in which they determined whether their virtual motion differed from their physical motion while experiencing one of three different methods of gain change: sudden gain change, slow gain change and constant gain. Gain thresholds were determined by 3 interleaved 2-up 1-down staircases, one per condition. Our results indicate that slow gain change is significantly harder to detect than sudden gain change

Advancing proxy-based haptic feedback in virtual reality

This thesis advances haptic feedback for Virtual Reality (VR). Our work is guided by Sutherland's 1965 vision of the ultimate display, which calls for VR systems to control the existence of matter. To push towards this vision, we build upon proxy-based haptic feedback, a technique characterized by the use of passive tangible props. The goal of this thesis is to tackle the central drawback of this approach, namely, its inflexibility, which yet hinders it to fulfill the vision of the ultimate display. Guided by four research questions, we first showcase the applicability of proxy-based VR haptics by employing the technique for data exploration. We then extend the VR system's control over users' haptic impressions in three steps. First, we contribute the class of Dynamic Passive Haptic Feedback (DPHF) alongside two novel concepts for conveying kinesthetic properties, like virtual weight and shape, through weight-shifting and drag-changing proxies. Conceptually orthogonal to this, we study how visual-haptic illusions can be leveraged to unnoticeably redirect the user's hand when reaching towards props. Here, we contribute a novel perception-inspired algorithm for Body Warping-based Hand Redirection (HR), an open-source framework for HR, and psychophysical insights. The thesis concludes by proving that the combination of DPHF and HR can outperform the individual techniques in terms of the achievable flexibility of the proxy-based haptic feedback.Diese Arbeit widmet sich haptischem Feedback für Virtual Reality (VR) und ist inspiriert von Sutherlands Vision des ultimativen Displays, welche VR-Systemen die Fähigkeit zuschreibt, Materie kontrollieren zu können. Um dieser Vision näher zu kommen, baut die Arbeit auf dem Konzept proxy-basierter Haptik auf, bei der haptische Eindrücke durch anfassbare Requisiten vermittelt werden. Ziel ist es, diesem Ansatz die für die Realisierung eines ultimativen Displays nötige Flexibilität zu verleihen. Dazu bearbeiten wir vier Forschungsfragen und zeigen zunächst die Anwendbarkeit proxy-basierter Haptik durch den Einsatz der Technik zur Datenexploration. Anschließend untersuchen wir in drei Schritten, wie VR-Systeme mehr Kontrolle über haptische Eindrücke von Nutzern erhalten können. Hierzu stellen wir Dynamic Passive Haptic Feedback (DPHF) vor, sowie zwei Verfahren, die kinästhetische Eindrücke wie virtuelles Gewicht und Form durch Gewichtsverlagerung und Veränderung des Luftwiderstandes von Requisiten vermitteln. Zusätzlich untersuchen wir, wie visuell-haptische Illusionen die Hand des Nutzers beim Greifen nach Requisiten unbemerkt umlenken können. Dabei stellen wir einen neuen Algorithmus zur Body Warping-based Hand Redirection (HR), ein Open-Source-Framework, sowie psychophysische Erkenntnisse vor. Abschließend zeigen wir, dass die Kombination von DPHF und HR proxy-basierte Haptik noch flexibler machen kann, als es die einzelnen Techniken alleine können

Upgrading Bridge Rails on Low-Volume Roads in Iowa: Final Report

Building on previous research, the goal of this project was to identify significant influencing factors for the Iowa Department of Transportation (DOT) to consider in future updates of its Instructional Memorandum (I.M.) 3.213, which provides guidelines for determining the need for traffic barriers (guardrail and bridge rail) at secondary roadway bridges—specifically, factors that might be significant for the bridge rail rating system component of I.M. 3.213. A literature review was conducted of policies and guidelines in other states and, specifically, of studies related to traffic barrier safety countermeasures at bridges in several states. In addition, a safety impact study was conducted to evaluate possible non-driver-related behavior characteristics of crashes on secondary road structures in Iowa using road data, structure data, and crash data from 2004 to 2013. Statistical models (negative binomial regression) were used to determine which factors were significant in terms of crash volume and crash severity. The study found that crashes are somewhat more frequent on or at bridges possessing certain characteristics—traffic volume greater than 400 vehicles per day (VPD) (paved) or greater than 50 vpd (unpaved), bridge length greater than 150 ft (paved) or greater than 35 ft (unpaved), bridge width narrower than its approach (paved) or narrower than 20 ft (unpaved), and bridges older than 25 years (both paved and unpaved). No specific roadway or bridge characteristic was found to contribute to more serious crashes. The study also confirmed previous research findings that crashes with bridges on secondary roads are rare, low-severity events. Although the findings of the study support the need for appropriate use of bridge rails, it concludes that prescriptive guidelines for bridge rail use on secondary roads may not be necessary, given the limited crash expectancy and lack of differences in crash expectancy among the various combinations of explanatory characteristics

Characterising population variability in brain structure through models of whole-brain structural connectivity

Models of whole-brain connectivity are valuable for understanding neurological function. This thesis seeks to develop an optimal framework for extracting models of whole-brain connectivity from clinically acquired diffusion data. We propose new approaches for studying these models. The aim is to develop techniques which can take models of brain connectivity and use them to identify biomarkers or phenotypes of disease. The models of connectivity are extracted using a standard probabilistic tractography algorithm, modified to assess the structural integrity of tracts, through estimates of white matter anisotropy. Connections are traced between 77 regions of interest, automatically extracted by label propagation from multiple brain atlases followed by classifier fusion. The estimates of tissue integrity for each tract are input as indices in 77x77 ”connectivity” matrices, extracted for large populations of clinical data. These are compared in subsequent studies. To date, most whole-brain connectivity studies have characterised population differences using graph theory techniques. However these can be limited in their ability to pinpoint the locations of differences in the underlying neural anatomy. Therefore, this thesis proposes new techniques. These include a spectral clustering approach for comparing population differences in the clustering properties of weighted brain networks. In addition, machine learning approaches are suggested for the first time. These are particularly advantageous as they allow classification of subjects and extraction of features which best represent the differences between groups. One limitation of the proposed approach is that errors propagate from segmentation and registration steps prior to tractography. This can cumulate in the assignment of false positive connections, where the contribution of these factors may vary across populations, causing the appearance of population differences where there are none. The final contribution of this thesis is therefore to develop a common co-ordinate space approach. This combines probabilistic models of voxel-wise diffusion for each subject into a single probabilistic model of diffusion for the population. This allows tractography to be performed only once, ensuring that there is one model of connectivity. Cross-subject differences can then be identified by mapping individual subjects’ anisotropy data to this model. The approach is used to compare populations separated by age and gender

You’re Making Me Sick: A Systematic Review of How Virtual Reality Research Considers Gender & Cybersickness

© {Owner/Author | ACM} 2021. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, http://dx.doi.org/10.1145/3411764.3445701.While multiple studies suggest that female-identified participants are more likely to experience cybersickness in virtual reality (VR), our systematic review of 71 eligible VR publications (59 studies and 12 surveys) pertaining to gender and cybersickness reveals a number of confounding factors in study design (e.g., a variety of technical specifications, tasks, content), a lack of demographic data, and a bias in participant recruitment. Our review shows an ongoing need within VR research to more consistently include and report on women’s experiences in VR to better understand the gendered possibility of cybersickness. Based on the gaps identified in our systematic review, we contribute study design recommendations for future work, arguing that gender considerations are necessary at every stage of VR study design, even when the study is not ‘about’ gender.Funder 1, NSERC Discovery Grant 2016-04422 || Funder 2, NSERC Discovery Accelerator Grant 492970-2016 || Funder 3, NSERC CREATE Saskatchewan-Waterloo Games User Research (SWaGUR) Grant 479724-2016 || Funder 4, Ontario Early Researcher Award ER15-11-18

VR Lab: User Interaction in Virtual Environments using Space and Time Morphing

Virtual Reality (VR) allows exploring changes in space and time that would otherwise be difficult to simulate in the real world. It becomes possible to transform the virtual world by increasing or diminishing distances or playing with time delays. Analysing the adaptability of users to different space-time conditions allows studying human perception and finding the right combination of interaction paradigms. Different methods have been proposed in the literature to offer users intuitive techniques for navigating wide virtual spaces, even if restricted to small physical play areas. Other studies investigate latency tolerance, suggesting humans’ inability to detect slight discrepancies between visual and proprioceptive sensory information. These studies contribute valuable insights for designing immersive virtual experiences and interaction techniques suitable for each task. This dissertation presents the design, implementation, and evaluation of a tangible VR Lab where spatiotemporal morphing scenarios can be studied. As a case study, we restricted the scope of the research to three spatial morphing scenarios and one temporal morphing scenario. The spatial morphing scenarios compared Euclidean and hyperbolic geometries, studied size discordance between physical and virtual objects, and the representation of hands in VR. The temporal morphing scenario investigated from what visual delay the task performance is affected. The users’ adaptability to the different spatiotemporal conditions was assessed based on task completion time, questionnaires, and observed behaviours. The results revealed significant differences between Euclidean and hyperbolic spaces. They also showed a preference for handling virtual and physical objects with concordant sizes, without any virtual representation of the hands. Although task performance was affected from 200 ms onwards, participants considered the ease of the task to be affected only from 500 ms visual delay onwards.A Realidade Virtual (RV) permite explorar mudanças no espaço e no tempo que de outra forma seriam difíceis de simular no mundo real. Torna-se possível transformar o mundo virtual aumentando ou diminuindo as distâncias ou manipulando os atrasos no tempo. A análise da adaptabilidade dos utilizadores a diferentes condições espaço-temporais permite estudar a perceção humana e encontrar a combinação certa de paradigmas de interação. Diferentes métodos têm sido propostos na literatura para oferecer aos utilizadores técnicas intuitivas de navegação em espaços virtuais amplos, mesmo que restritos a pequenas áreas físicas de jogo. Outros estudos investigam a tolerância à latência, sugerindo a incapacidade do ser humano de detetar ligeiras discrepâncias entre a informação sensorial visual e propriocetiva. Estes estudos contribuem com valiosas informações para conceber experiências virtuais imersivas e técnicas de interação adequadas a cada tarefa. Esta dissertação apresenta o desenho, implementação e avaliação de um Laboratório de RV tangível onde podem ser estudados cenários de distorção espaço-temporal. Como estudo de caso, restringimos o âmbito da investigação a três cenários de distorção espacial e um cenário de distorção temporal. Os cenários de distorção espacial compararam geometrias Euclidianas e hiperbólicas, estudaram a discordância de tamanho entre objetos físicos e virtuais, e a representação das mãos em RV. O cenário de distorção temporal investigou a partir de que atraso visual o desempenho da tarefa é afetado. A adaptabilidade dos utilizadores às diferentes condições espaço-temporais foi avaliada com base no tempo de conclusão da tarefa, questionários, e comportamentos observados. Os resultados revelaram diferenças significativas entre os espaços Euclidiano e hiperbólico. Também mostraram a preferência pelo manuseamento de objetos virtuais e físicos com tamanhos concordantes, sem qualquer representação virtual das mãos. Embora o desempenho da tarefa tenha sido afetado a partir dos 200 ms, os participantes consideraram que a facilidade da tarefa só foi afetada a partir dos 500 ms de atraso visual

CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS

The book collects the short papers presented at the 13th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS). The meeting has been organized by the Department of Statistics, Computer Science and Applications of the University of Florence, under the auspices of the Italian Statistical Society and the International Federation of Classification Societies (IFCS). CLADAG is a member of the IFCS, a federation of national, regional, and linguistically-based classification societies. It is a non-profit, non-political scientific organization, whose aims are to further classification research