13,271 research outputs found

    The Douglas-Peucker algorithm for line simplification: Re-evaluation through visualization

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    The primary aim of this paper is to illustrate the value of visualization in cartography and to indicate that tools for the generation and manipulation of realistic images are of limited value within this application. This paper demonstrates the value of visualization within one problem in cartography, namely the generalisation of lines. It reports on the evaluation of the Douglas-Peucker algorithm for line simplification. Visualization of the simplification process and of the results suggest that the mathematical measures of performance proposed by some other researchers are inappropriate, misleading and questionable

    Doctor of Philosophy

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    dissertationDataflow pipeline models are widely used in visualization systems. Despite recent advancements in parallel architecture, most systems still support only a single CPU or a small collection of CPUs such as a SMP workstation. Even for systems that are specifically tuned towards parallel visualization, their execution models only provide support for data-parallelism while ignoring taskparallelism and pipeline-parallelism. With the recent popularization of machines equipped with multicore CPUs and multi-GPU units, these visualization systems are undoubtedly falling further behind in reaching maximum efficiency. On the other hand, there exist several libraries that can schedule program executions on multiple CPUs and/or multiple GPUs. However, due to differences in executing a task graph and a pipeline along with their APIs being considerably low-level, it still remains a challenge to integrate these run-time libraries into current visualization systems. Thus, there is a need for a redesigned dataflow architecture to fully support and exploit the power of highly parallel machines in large-scale visualization. The new design must be able to schedule executions on heterogeneous platforms while at the same time supporting arbitrarily large datasets through the use of streaming data structures. The primary goal of this dissertation work is to develop a parallel dataflow architecture for streaming large-scale visualizations. The framework includes supports for platforms ranging from multicore processors to clusters consisting of thousands CPUs and GPUs. We achieve this in our system by introducing the notion of Virtual Processing Elements and Task-Oriented Modules along with a highly customizable scheduler that controls the assignment of tasks to elements dynamically. This creates an intuitive way to maintain multiple CPU/GPU kernels yet still provide coherency and synchronization across module executions. We have implemented these techniques into HyperFlow which is made of an API with all basic dataflow constructs described in the dissertation, and a distributed run-time library that can be used to deploy those pipelines on multicore, multi-GPU and cluster-based platforms

    Visualisation, VISC and scientific insight

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    CISRG discussion paper ;

    Real Time, Accurate, Multi-Featured Rendering of Bump Mapped Surfaces

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    We present a new technique to render in real time objects which have part of their high frequency geometric detail encoded in bump maps. It is based on the quantization of normal-maps, and achieves excellent result both in rendering time and rendering quality, with respect to other alternative methods. The method proposed also allows to add many interesting visual effects, even for object with large bumb maps, including non-photorealistic rendering, chrome effects, shading under multiple lights, rendering of different materials within a single object, specular reflections and others. Moreover, the implementation of the method is not complex and can be eased by software reuse

    Algorithms for sketching surfaces

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    CISRG discussion paper ; 1

    Viewfinder: final activity report

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    The VIEW-FINDER project (2006-2009) is an 'Advanced Robotics' project that seeks to apply a semi-autonomous robotic system to inspect ground safety in the event of a fire. Its primary aim is to gather data (visual and chemical) in order to assist rescue personnel. A base station combines the gathered information with information retrieved from off-site sources. The project addresses key issues related to map building and reconstruction, interfacing local command information with external sources, human-robot interfaces and semi-autonomous robot navigation. The VIEW-FINDER system is a semi-autonomous; the individual robot-sensors operate autonomously within the limits of the task assigned to them, that is, they will autonomously navigate through and inspect an area. Human operators monitor their operations and send high level task requests as well as low level commands through the interface to any nodes in the entire system. The human interface has to ensure the human supervisor and human interveners are provided a reduced but good and relevant overview of the ground and the robots and human rescue workers therein

    Testing goGPS low-cost RTK positioning with a web-based track log management system

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    Location-based online collaborative platforms are proving to be an effective and widely adopted solution for geospatial data collection, update and sharing. Popular collaborative projects like OpenStreetMap, Wikimapia and other services that collect and publish user-generated geographic contents have been fostered by the increasing availability of location-aware palmtop devices. These instruments include GPS-enabled mobile phones and low-cost GPS receivers, which are employed for quick field surveys at both professional and non-professional levels. Nevertheless, data collected with such devices are often not accurate enough to avoid heavy user intervention before using or sharing them. Providing tools for collecting and sharing accuracy-enhanced positioning data to a wide and diverse user base requires to integrate modern web technologies and online services with advanced satellite positioning techniques. A web-based prototype system for enhancing GPS tracks quality and managing track logs and points of interest (POI), originally developed using standard GPS devices, was tested by using goGPS software to apply kinematic relative positioning (RTK) with low-cost single-frequency receivers. The workflow consists of acquiring raw GPS measurements from the user receiver and from a network of permanent GPS stations, processing them by RTK positioning within goGPS Kalman filter algorithm, sending the accurate positioning data to the web-based system, performing further quality enhancements if needed, logging the data and displaying them. The whole system can work either in real-time or post-processing, the latter providing a solution to collect and publish enhanced location data without necessarily requiring mobile Internet connection on the field. Tests were performed in open areas and variously dense urban environments, comparing different indices for quality-based filtering. Results are promising and suggest that the integration of web technologies with advanced geodetic techniques applied to low-cost instruments can be an effective solution to collect, update and share accurate location data on collaborative platforms

    Mobile graphics: SIGGRAPH Asia 2017 course

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