Interaction with virtual crowd in Immersive and semi‐Immersive Virtual Reality systems

This study examines attributes of virtual human behavior that may increase the plausibility of a simulated crowd and affect the user's experience in Virtual Reality. Purpose-developed experiments in both Immersive and semi-Immersive Virtual Reality systems queried the impact of collision and basic interaction between real-users and the virtual crowd and their effect on the apparent realism and ease of navigation within Virtual Reality (VR). Participants' behavior and subjective measurements indicated that facilitating collision avoidance between the user and the virtual crowd makes the virtual characters, the environment, and the whole Virtual Reality system appear more realistic and lifelike. Adding basic social interaction, such as verbal salutations, gaze, and other gestures by the virtual characters towards the user, further contributes to this effect, with the participants reporting a stronger sense of presence. On the other hand, enabling collision avoidance on its own produces a reduced feeling of comfort and ease of navigation in VR. Objective measurements showed another interesting finding that collision avoidance may reduce the user's performance regarding their primary goal (navigating in VR following someone) and that this performance is further reduced when both collision avoidance and social interaction are facilitated

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Perceptual effects of scene context and viewpoint for virtual pedestrian crowds

In this article, we evaluate the effects of position, orientation, and camera viewpoint on the plausibility of pedestrian formations. In a set of three perceptual studies, we investigated how humans perceive characteristics of virtual crowds in static scenes reconstructed from annotated still images, where the orientations and positions of the individuals have been modified. We found that by applying rules based on the contextual information of the scene, we improved the perceived realism of the crowd formations when compared to random formations. We also examined the effect of camera viewpoint on the plausibility of virtual pedestrian scenes, and we found that an eye-level viewpoint is more effective for disguising random behaviors, while a canonical viewpoint results in these behaviors being perceived as less realistic than an isometric or top-down viewpoint. Results from these studies can help in the creation of virtual crowds, such as computer graphics pedestrian models or architectural scenes, and identify situations when users' perception is less accurate

Geometric Collision Avoidance for Heterogeneous Crowd Simulation

Simulation of human crowds can create plausible human trajectories, predict likely flows of pedestrians, and has application in areas such as games, movies, safety planning, and virtual environments. This dissertation presents new crowd simulation methods based on geometric techniques. I will show how geometric optimization techniques can be used to efficiently compute collision-avoidance constraints, and use these constraints to generate human-like trajectories in simulated environments. This process of reacting to the nearby environment is known as local navigation and it forms the basis for many crowd simulation techniques, including those described in this dissertation. Given the importance of local navigation computations, I devote much of this dissertation to the derivation, analysis, and implementation of new local navigation techniques. I discuss how to efficiently exploit parallelization features available on modern processors, and show how an efficient parallel implementation allows simulations of hundreds of thousands of agents in real time on many-core processors and tens of thousands of agents on multi-core CPUs. I analyze the macroscopic flows which arise from these geometric collision avoidance techniques and compare them to flows seen in real human crowds, both qualitatively (in terms of flow patterns) and quantitatively (in terms of flow rates). Building on the basis of these strong local navigation models, I further develop many important extensions to the simulation framework. Firstly, I develop a model for global navigation which allows for more complex scenarios by accounting for long-term planning around large obstacles or emergent congestion. Secondly, I demonstrate methods for using data-driven approaches to improve crowd simulations. These include using real-world data to automatically tune parameters, and using perceptual user study data to introduce behavioral variation. Finally, looking beyond geometric avoidance based crowd simulation methods, I discuss methods for objectively evaluating different crowd simulation strategies using statistical measures. Specifically, I focus on the problem of quantifying how closely a simulation approach matches real-world data. I propose a similarity metric that can be applied to a wide variety of simulation approaches and datasets. Taken together, the methods presented in this dissertation enable simulations of large, complex humans crowds with a level of realism and efficiency not previously possible.Doctor of Philosoph