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

Extending 3-DoF Metrics to Model User Behaviour Similarity in 6-DoF Immersive Applications

Immersive reality technologies, such as Virtual and Augmented Reality, have ushered a new era of user-centric systems, in which every aspect of the coding-delivery-rendering chain is tailored to the interaction of the users. Understanding the actual interactivity and behaviour of the users is still an open challenge and a key step to enabling such a user-centric system. Our main goal is to extend the applicability of existing behavioural methodologies for studying user navigation in the case of 6 Degree-of-Freedom (DoF). Specifically, we first compare the navigation in 6-DoF with its 3-DoF counterpart highlighting the main differences and novelties. Then, we define new metrics aimed at better modelling behavioural similarities between users in a 6-DoF system. We validate and test our solutions on real navigation paths of users interacting with dynamic volumetric media in 6-DoF Virtual Reality conditions. Our results show that metrics that consider both user position and viewing direction better perform in detecting user similarity while navigating in a 6-DoF system. Having easy-to-use but robust metrics that underpin multiple tools and answer the question "how do we detect if two users look at the same content?" open the gate to new solutions for a user-centric syste

Extending 3-DoF Metrics to Model User Behaviour Similarity in 6-DoF Immersive Applications

Immersive reality technologies, such as Virtual and Augmented Reality, have ushered a new era of user-centric systems, in which every aspect of the coding--delivery--rendering chain is tailored to the interaction of the users. Understanding the actual interactivity and behaviour of the users is still an open challenge and a key step to enabling such a user-centric system. Our main goal is to extend the applicability of existing behavioural methodologies for studying user navigation in the case of 6 Degree-of-Freedom (DoF). Specifically, we first compare the navigation in 6-DoF with its 3-DoF counterpart highlighting the main differences and novelties. Then, we define new metrics aimed at better modelling behavioural similarities between users in a 6-DoF system. We validate and test our solutions on real navigation paths of users interacting with dynamic volumetric media in 6-DoF Virtual Reality conditions. Our results show that metrics that consider both user position and viewing direction better perform in detecting user similarity while navigating in a 6-DoF system. Having easy-to-use but robust metrics that underpin multiple tools and answer the question ``how do we detect if two users look at the same content?" open the gate to new solutions for a user-centric system

Exploration-exploitation Trade-off in a Treasure Hunting Game

AbstractSearching experiments conducted in different virtual environments over a gender balanced group of people revealed a gender irrelevant scale-free spread of searching activity on large spatiotemporal scales. We have suggested and solved analytically a simple statistical model of the coherent-noise type describing the exploration-exploitation trade-off in humans (“should I stay or should I go”). The model exhibits a variety of saltatory behaviours, ranging from Levy flights occurring under uncertainty to Brownian walks performed by a treasure hunter confident of the eventual success

Space and camera path reconstruction for omni-directional vision

In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the reconstruction is unique. For example, if there are three points in general position and three omni-directional cameras in general position, a unique reconstruction is possible up to a similarity. We then look at the reconstruction problem with m cameras and n points, where n and m can be large and the over-determined system is solved by least square methods. The reconstruction is robust and generalizes to the case of a dynamic environment where landmarks can move during the movie capture. Possible applications of the result are computer assisted scene reconstruction, 3D scanning, autonomous robot navigation, medical tomography and city reconstructions

Towards Autonomous Unmanned Vehicle Systems

As an emerging technology, autonomous Unmanned Vehicle Systems (UVS) have found not only many military applications, but also various civil applications. For example, Google, Amazon and Facebook are developing their UVS plans to explore new markets. However, there are still a lot of challenging problems which deter the UVS’s development. We study two important and challenging problems in this dissertation, i.e. localization and 3D reconstruction. Specifically, most GPS based localization systems are not very accurate and can have problems in areas where no GPS signals are available. Based on the Received Signal Strength Indication (RSSI) and Inertial Navigation System (INS), we propose a new hybrid localization system, which is very efficient and can account for dynamic communication environments. Extensive simulation results demonstrate the efficiency of the proposed localization system. Besides, 3D reconstruction is a key problem in autonomous navigation and hence very important for UVS.With the help of high-speed Internet and powerful cloud servers, the light-weight computers on the UVS can now execute computationally expensive computer vision based algorithms. We develop a 3D reconstruction scheme which employs cloud computing to perform realtime 3D reconstruction. Simulations and experiments show the efficacy and efficiency of our scheme

Space Invaders: Pedestrian Proxemic Utility Functions and Trust Zones for Autonomous Vehicle Interactions

Understanding pedestrian proxemic utility and trust will help autonomous vehicles to plan and control interactions with pedestrians more safely and efficiently. When pedestrians cross the road in front of human-driven vehicles, the two agents use knowledge of each other’s preferences to negotiate and to determine who will yield to the other. Autonomous vehicles will require similar understandings, but previous work has shown a need for them to be provided in the form of continuous proxemic utility functions, which are not available from previous proxemics studies based on Hall’s discrete zones. To fill this gap, a new Bayesian method to infer continuous pedestrian proxemic utility functions is proposed, and related to a new definition of ‘physical trust requirement’ (PTR) for road-crossing scenarios. The method is validated on simulation data then its parameters are inferred empirically from two public datasets. Results show that pedestrian proxemic utility is best described by a hyperbolic function, and that trust by the pedestrian is required in a discrete ‘trust zone’ which emerges naturally from simple physics. The PTR concept is then shown to be capable of generating and explaining the empirically observed zone sizes of Hall’s discrete theory of proxemics