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Abstract

The preservation of archaeological sites is an important task in cultural heritage. Classical methods conserve archaeological objects in museums and provide restoration of archaeological sites threatened by decay. The improved digitalization provides the possibility to generate an accurate representation of archaeological sites by using laser scanners. The resulting point clouds can preserve the archaeological site and provide the possibility to view it in its digital form even if it no longer exists. Usually, the archaeological site comes with a lot of different material, which has been created over the years. This material provides information about the digitalized object, which helps to gain a deeper understanding about the presented archaeological site. This thesis presents an annotation system for a point-cloud renderer. The system allows adding annotations in the 3D space next to the part of the point cloud it belongs to. This helps to provide the additional information of the point cloud in the context it belongs to. Moreover, each annotation should present interesting information about specific annotated parts of the archaeological site to the viewer. Besides simple textual annotations, a variable amount of documents, such as images and PDFs, can be attached to each annotation to provide all kind of information. Several filtering techniques, including viewpoint-dependent priority filtering, are presented to control the visibility of the annotations. Moreover, a guidance system based on graphs is introduced to lead viewers to different points of interest, which are represented as annotations. To provide a clear connection between annotations and the annotated part of the point cloud, a point-selection method and a point-marking method are presented. To allow the connection of a large set of annotations to a single point cloud, these methods are developed in CUDA. This is done by extending existing methods, which create octrees in CUDA. The developed methods allow fast execution on the GPU while a CPU-based method is not able to handle such a large amount of point selections in real-time.

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image: Annotations in a point cloud image: Annotations in a point cloud

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BibTeX

@mastersthesis{Tragust-2014-master-thesis,
  title =      "Integrating Annotations into a Point-based Rendering System",
  author =     "Markus Tragust",
  year =       "2014",
  abstract =   "The preservation of archaeological sites is an important
               task in cultural heritage. Classical methods conserve
               archaeological objects in museums and provide restoration of
               archaeological sites threatened by decay. The improved
               digitalization provides the possibility to generate an
               accurate representation of archaeological sites by using
               laser scanners. The resulting point clouds can preserve the
               archaeological site and provide the possibility to view it
               in its digital form even if it no longer exists. Usually,
               the archaeological site comes with a lot of different
               material, which has been created over the years. This
               material provides information about the digitalized object,
               which helps to gain a deeper understanding about the
               presented archaeological site. This thesis presents an
               annotation system for a point-cloud renderer. The system
               allows adding annotations in the 3D space next to the part
               of the point cloud it belongs to. This helps to provide the
               additional information of the point cloud in the context it
               belongs to. Moreover, each annotation should present
               interesting information about specific annotated parts of
               the archaeological site to the viewer. Besides simple
               textual annotations, a variable amount of documents, such as
               images and PDFs, can be attached to each annotation to
               provide all kind of information. Several filtering
               techniques, including viewpoint-dependent priority
               filtering, are presented to control the visibility of the
               annotations. Moreover, a guidance system based on graphs is
               introduced to lead viewers to different points of interest,
               which are represented as annotations. To provide a clear
               connection between annotations and the annotated part of the
               point cloud, a point-selection method and a point-marking
               method are presented. To allow the connection of a large set
               of annotations to a single point cloud, these methods are
               developed in CUDA. This is done by extending existing
               methods, which create octrees in CUDA. The developed methods
               allow fast execution on the GPU while a CPU-based method is
               not able to handle such a large amount of point selections
               in real-time.",
  month =      jan,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  keywords =   "user guidance, annotating objects, information system",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2014/Tragust-2014-master-thesis/",
}