Enabling scalability by partitioning virtual environments using frontier sets

We present a class of partitioning scheme that we have called frontier sets. Frontier sets build on the notion of a potentially visible set (PVS). In a PVS, a world is subdivided into cells and for each cell all the other cells that can be seen are computed. In contrast, a frontier set considers pairs of cells, A and B. For each pair, it lists two sets of cells (two frontiers), FAB and FBA. By definition, from no cell in FAB is any cell in FBA visible and vice versa. Our initial use of frontier sets has been to enable scalability in distributed networking. This is possible because, for example, if at time t0 Player1 is in cell A and Player2 is in cell B, as long as they stay in their respective frontiers, they do not need to send update information to each other. In this paper we describe two strategies for building frontier sets. Both strategies are dynamic and compute frontiers only as necessary at runtime. The first is distance-based frontiers. This strategy requires precomputation of an enhanced potentially visible set. The second is greedy frontiers. This strategy is more expensive to compute at runtime, however it leads to larger and thus more efficient frontiers. Network simulations using code based on the Quake II engine show that frontiers have significant promise and may allow a new class of scalable peer-to-peer game infrastructures to emerge

Using tracked mobile sensors to make maps of environmental effects

We present a study the results of a study of environmental carbon monoxide pollution that has uses a set of tracked, mobile pollution sensors. The motivating concept is that we will be able to map pollution and other properties of the real world a fine scale if we can deploy a large set of sensors with members of the general public who would carry them as they go about their normal everyday activities. To prove the viability of this concept we have to demonstrate that data gathered in an ad-hoc manner is reliable enough in order to allow us to build interesting geo-temporal maps. We present a trial using a small number of global positioning system-tracked CO sensors. From analysis of raw GPS logs we find some well-known spatial and temporal properties of CO. Further, by processing the GPS logs we can find fine-grained variations in pollution readings such as when crossing roads. We then discuss the space of possibilities that may be enabled by tracking sensors around the urban environment – both in getting at personal experience of properties of the environment and in making summative maps to predict future conditions. Although we present a study of CO, the techniques will be applicable to other environmental properties such as radio signal strength, noise, weather and so on

A simple method for estimating the latency of interactive, real-time graphics simulations

One of the critical determinants of the effectiveness and usability of interactive graphics simulations is the latency with which visual updates can be made based on input from interaction devices. High latency can diminish performance and can lead to simulator sickness. We demonstrate a new method for measuring latency using a standard video camera. The method is simple to configure, sensitive and rapid to use. This is in contrast to previous methods which required specialized equipment, were laborious or could only determine gross changes in latency. We attach a tracker to a pendulum and move a simulated image on the screen using the tracker positions. We video both the pendulum and simulated image together, and fit two sine curves, one to centre of motion of pendulum and one to the centre of motion of the simulated image. From the phase difference between these two sine curves we can determine latency changes significantly less than the frame rate of the camera. We demonstrate the method by comparing the latency of a two different systems for a CAVE™-like display

Construction and Evaluation of an Ultra Low Latency Frameless Renderer for VR.

© 2016 IEEE.Latency-the delay between a users action and the response to this action-is known to be detrimental to virtual reality. Latency is typically considered to be a discrete value characterising a delay, constant in time and space-but this characterisation is incomplete. Latency changes across the display during scan-out, and how it does so is dependent on the rendering approach used. In this study, we present an ultra-low latency real-time ray-casting renderer for virtual reality, implemented on an FPGA. Our renderer has a latency of 1 ms from tracker to pixel. Its frameless nature means that the region of the display with the lowest latency immediately follows the scan-beam. This is in contrast to frame-based systems such as those using typical GPUs, for which the latency increases as scan-out proceeds. Using a series of high and low speed videos of our system in use, we confirm its latency of 1 ms. We examine how the renderer performs when driving a traditional sequential scan-out display on a readily available HMO, the Oculus Rift OK2. We contrast this with an equivalent apparatus built using a GPU. Using captured human head motion and a set of image quality measures, we assess the ability of these systems to faithfully recreate the stimuli of an ideal virtual reality system-one with a zero latency tracker, renderer and display running at 1 kHz. Finally, we examine the results of these quality measures, and how each rendering approach is affected by velocity of movement and display persistence. We find that our system, with a lower average latency, can more faithfully draw what the ideal virtual reality system would. Further, we find that with low display persistence, the sensitivity to velocity of both systems is lowered, but that it is much lower for ours

Data visualization within urban models

Models of urban environments have many uses for town planning, pre-visualization of new building work and utility service planning. Many of these models are three-dimensional, and increasingly there is a move towards real-time presentation of such large models. In this paper we present an algorithm for generating consistent 3D models from a combination of data sources, including Ordnance Survey ground plans, aerial photography and laser height data. Although there have been several demonstrations of automatic generation of building models from 2D vector map data, in this paper we present a very robust solution that generates models that are suitable for real-time presentation. We then demonstrate a novel pollution visualization that uses these models

A Platform Independent Architecture for Virtual Characters and Avatars

We have developed a Platform Independent Architecture for Virtual Characters and Avatars (PIAVCA), a character animation system that aims to be independent of any underlying graphics framework and so be easily portable. PIAVCA supports body animation based on a skeletal representation and facial animation based on morph targets

The Vehicle Pattern for Simplifying Cross-Platform Virtual Reality Development

Maintaining an application across different virtual reality systems can be difficult and time-consuming. Different systems require different strategies for implementing simple interactions such as locomotion and object manipulation. In this chapter, we describe a pattern that we have used to minimize the interactions between the interaction style (behaviour) with the scene elements, and the specific interaction devices. The vehicle pattern allows the programmer to ignore most of the implementation details of hardware and interaction, and focus on the scene description. They can then easily generate versions of the scene for different systems. We demonstrate the principles of the vehicle pattern with an outline implementation in Unit

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets