Panoramic Scenes for Texture Mapping of 3d City Models

نویسندگان

  • Norbert Haala
  • Martin Kada
چکیده

Urban models can be collected area covering and efficiently based on aerial data like stereo images or LIDAR. While a large number of applications like simulations are already feasible based on the available three-dimensional building representations, a further quality improvement is required for some other tasks. Especially, if very realistic visualisations from pedestrian viewpoints have to be generated, the quality and amount of detail, which is available for urban models generated from aerial data has to be improved. As an example, due to the viewpoint restrictions of airborne platforms, image texture for the facades of the buildings frequently is not available from airborne sensors. Since this information is crucial to improve the visual appearance of urban models for pedestrian perspectives, alternative data sources have to be applied. Thus, image texture for the faces of existing building models is frequently generated based on manual mapping of terrestrial images. As it will be discussed within the paper, the efficiency of the manual mapping process can be increased considerably by the application of panoramic scenes. If these panoramic scenes are collected from a high-level system based on a rotating CCD line scanner, large areas are covered at high resolution and superb image quality. Thus, the processing of a single scene is sufficient to extract texture for a considerable number of buildings. After the mapping of terrestrial image against the available building model is defined, the process of texture extraction and placement can be realized very efficiently if the functionality of 3D graphics hardware is used. In contrast to the application of standard viewers, this technique allows to model even complex geometric effects like self-occlusion or lens distortion. By these means a very fast and flexible on-the-fly generation of façade texture using real world imagery is feasible.

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تاریخ انتشار 2005