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        "type_id": "masterthesis",
        "tu_id": null,
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        "title": "Realistic Local Lighting in Dynamic Height Fields",
        "date": "2013-05",
        "abstract": "This thesis presents a method to compute soft shadows from environment maps and local light sources on dynamic height fields, extending the work of Snyder et al. [29]. While direct illumination in static scenes is very common in video games and 3D applications, real-time global illumination methods supporting dynamic scenes and lights are still an active field of research.\r\n\r\nIn this work, a short general introduction to global illumination and spherical harmonics is presented as well as an overview of the state of the art methods in interactive global illumination for height fields.\r\n\r\nIn our method, visibility at each receiver point of a height field is determined by the visible horizon, which can be approximated efficiently using a multi-resolution sampling approach. Local light sources are represented by spherical lights and the incident radiance at receiver points is projected into the spherical harmonic basis. Hence, this method produces convincing shadows on dynamic height fields more efficiently than global illumination methods for general geometry.",
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                "firstname": "Aaron",
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                "short_abstract": "Laser scanning is an important tool in cultural heritage for documenting the state of archaeological monuments. The data produced by laser scanning is ever increasing, with the latest generation of laser scanners generating a billion of points in one measurement pass. To colorize the laser scans, additional photographs are taken. Managing these huge amounts of data in terms of size is a challenge on its own, but also to ensure the quality of the resulting point-based models is of utmost importance for the further development of laser scanning as a standard technique in cultural heritage. We identified three topics that can drive forward the integration of laser scanning in the everyday work of archaeologists.",
                "abstract": "<b>Project partners:</b>\n<ul>\n<li><a href=\"http://www.oeaw.ac.at/antike/index.php?id=50\">Austrian Academy of Sciences (ÖAW):</a> Norbert Zimmermann</li>\n<li><a href=\"http://www.imagination.at\">Imagination Computer Services GmbH</a></li>\n</ul>\n\n<p>\nLaser scanning is an important tool in cultural heritage for documenting the state of archaeological monuments. The data produced by laser scanning is ever increasing, with the latest generation of laser scanners generating a billion of points in one measurement pass. To colorize the laser scans, additional photographs are taken. Managing these huge amounts of data in terms of size is a challenge on its own, but also to ensure the quality of the resulting point-based models is of utmost importance for the further development of laser scanning as a standard technique in cultural heritage. We identified three topics that can drive forward the integration of laser scanning in the everyday work of archaeologists.\n\n<p>\nThe first topic is the recoloring of point clouds that are combined from several different scan positions. The photographs taken at the different scan positions all exhibit different colorizations of the objects in the scene, as the lighting conditions usually vary from scan position to scan position. We want to develop methods that can provide an artifact free colorized model, independent of the lighting conditions that prevailed during laser scanning. The second topic deals with the management of large point clouds. It incorporates compression of the point cloud data, where the data shall nevertheless remain editable, and the display of large data. Several compression techniques for different point attributes, lossless as well as lossy compression, and fitting points to higher order primitives will be used for compression depending on the further use of the data. To display the data, an eye-tracker can be used to increase the visual experience of the user. The third topic deals with the distribution of data over a network, and navigating through the data, so that users can get access to large point-based models of cultural heritage sites with intuitive navigation capabilities.\n<p>\nCultural Heritage is a growing market that needs intensive support from enabling technologies like real-time computer graphics and 3D object reconstruction. Especially the preservation and presentation of archaeological or historical items (architecture, artifacts) are of high importance there. Austria is well known in the tourism industry because of its cultural values. Preserving and presenting such cultural values not only physically but also in digital form, will help to distribute these values also using new media channels to the broad public.\nAny improvement of the technology that helps to preserve cultural items and allows presenting such items and scientific findings to a large audience will improve the value of these cultural items and in the same way boost the tourism industry.\n<p>\nEspecially in Austria there is a huge \"creative industries\" community, small and medium companies working on innovative presentations of cultural goods. Especially these companies will profit from the technology that will be developed in this project. One of these \"creative industries\" companies is Imagination, partner in this project and pioneer in cultural heritage presentations and preservation software.",
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        "abstract": "Diffusion curves are a powerful vector graphic representation that stores an image as a set of 2D Bezier curves with colors defined on either side. These colors are diffused over the image plane, resulting in smooth color regions\nas well as sharp boundaries. In this paper, we introduce a new automatic diffusion curve coloring algorithm. We\nstart by defining a geometric heuristic for the maximum density of color control points along the image curves.\nFollowing this, we present a new algorithm to set the colors of these points so that the resulting diffused image is as close as possible to a source image in a least squares sense. We compare our coloring solution to the existing one which fails for textured regions, small features, and inaccurately placed curves. The second contribution of the paper is to extend the diffusion curve representation to include texture details based on Gabor noise. Like the curves themselves, the defined texture is resolution independent, and represented compactly. We define methods to automatically make an initial guess for the noise texure, and we provide intuitive manual controls to edit the parameters of the Gabor noise. Finally, we show that the diffusion curve representation itself extends to storing any number of attributes in an image, and we demonstrate this functionality with image stippling an hatching\napplications.",
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