15 research outputs found

    Intelligent Computational Transportation

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    Transportation is commonplace around our world. Numerous researchers dedicate great efforts to vast transportation research topics. The purpose of this dissertation is to investigate and address a couple of transportation problems with respect to geographic discretization, pavement surface automatic examination, and traffic ow simulation, using advanced computational technologies. Many applications require a discretized 2D geographic map such that local information can be accessed efficiently. For example, map matching, which aligns a sequence of observed positions to a real-world road network, needs to find all the nearby road segments to the individual positions. To this end, the map is discretized by cells and each cell retains a list of road segments coincident with this cell. An efficient method is proposed to form such lists for the cells without costly overlapping tests. Furthermore, the method can be easily extended to 3D scenarios for fast triangle mesh voxelization. Pavement surface distress conditions are critical inputs for quantifying roadway infrastructure serviceability. Existing computer-aided automatic examination techniques are mainly based on 2D image analysis or 3D georeferenced data set. The disadvantage of information losses or extremely high costs impedes their effectiveness iv and applicability. In this study, a cost-effective Kinect-based approach is proposed for 3D pavement surface reconstruction and cracking recognition. Various cracking measurements such as alligator cracking, traverse cracking, longitudinal cracking, etc., are identified and recognized for their severity examinations based on associated geometrical features. Smart transportation is one of the core components in modern urbanization processes. Under this context, the Connected Autonomous Vehicle (CAV) system presents a promising solution towards the enhanced traffic safety and mobility through state-of-the-art wireless communications and autonomous driving techniques. Due to the different nature between the CAVs and the conventional Human- Driven-Vehicles (HDVs), it is believed that CAV-enabled transportation systems will revolutionize the existing understanding of network-wide traffic operations and re-establish traffic ow theory. This study presents a new continuum dynamics model for the future CAV-enabled traffic system, realized by encapsulating mutually-coupled vehicle interactions using virtual internal and external forces. A Smoothed Particle Hydrodynamics (SPH)-based numerical simulation and an interactive traffic visualization framework are also developed

    Understanding Hardware-Accelerated 2D Vector Graphics

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    With the rising support of compute kernels and low-level GPU architecture access over the past few years, friction with general-purpose GPU computing is fading. With new accessibility, new analytics methods for hardware-accelerated vector rasterization are being tried with new leverage. There are compelling reasons to optimize performance given the resolution-independent imaging model and inherent benefits. However, there is a noticeable lack of comparison between algorithms, techniques, and libraries which gauge the modern rendering capability. Analyzing the performance of vector graphics on the GPU is challenging, primarily when various technologies may compete for differing scarce computer resources. This thesis examines the contention found with modern vector graphic rendering and expands on analysis techniques used to de-obfuscate efficacy by providing an analytic benchmarking framework for hardware-accelerated renderers

    EFFICIENT AND ACCURATE FUSION OF MASSIVE VECTOR DATA ON 3D TERRAIN

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    This paper presents a viewpoint-related fusion method of massive vector data and 3D terrain, in order to superpose the massive 2D vector data onto the undulating multi-resolution 3D terrain precisely and efficiently. First, the method establishes an adaptive hierarchical grid spatial index for vector data. It will determine the geographic spatial relationship between vector data and the tiles of 3D terrain in the visible area; secondly, this method will use the improved sub-pixel graphics engine AggExt to generate textures for vector data that has been bound to terrain tiles in real time; Finally, considering that a large amount of vector data will generate a lot of 2D textures in the computer memory, the method should release the “expired” vector textures. In this paper, in order to take into account the real-time convergence and the smooth interactivity of 3D scenes, this method will adopt a multi-threading strategy. The experimental results show that this method can realize the real-time and seamless fusion of massive vector objects on the 3D terrain, and has a high rendering frame rate. It can also reduce the aliasing produced by traditional texture-based methods and improve the quality of vector data fusion

    Acta Polytechnica Hungarica 2015

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    Efficient Algorithms for Large-Scale Image Analysis

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    This work develops highly efficient algorithms for analyzing large images. Applications include object-based change detection and screening. The algorithms are 10-100 times as fast as existing software, sometimes even outperforming FGPA/GPU hardware, because they are designed to suit the computer architecture. This thesis describes the implementation details and the underlying algorithm engineering methodology, so that both may also be applied to other applications

    Game engine for location-based services

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    Tese de mestrado integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201

    Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

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    It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

    Parallel scanline algorithm for rapid rasterization of vector geographic data

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