Processing of Façade Imagery
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Date
2010
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Publisher
Musialski
Text.PhDThesis
Abstract
Modeling and reconstruction of urban environments is currently the subject of intensive research. There is a wide range of possible applications, including virtual environments like cyber-tourism, computer games, and the entertainment industries in general, as well as urban planning and architecture, security planning and training, traffic simulation, driving guidance and telecommunications, to name but a few. The research directions are spread across the disciplines of computer vision, computer graphics, image processing, photogrammetry and remote sensing, as well as architecture and the geosciences. Reconstruction is a complex problem and requires an entire pipeline of different tasks. In this thesis we focus on processing of images of fa{\c c}ades which is one specific subarea of urban reconstruction. The goal of our research is to provide novel algorithmic solutions for problems in fa{\c c}ade imagery processing. In particular, the contribution of this thesis is the following: First, we introduce a system for generation of approximate orthogonal fa{\c c}ade images. The method is a combination of automatic and interactive tools in order to provide a convenient way to generate high-quality results. The second problem addressed in this thesis is fa{\c c}ade image segmentation. In particular, usually by segmentation we mean the subdivision of the fa{\c c}ade into windows and other architectural elements. We address this topic with two different algorithms for detection of grids over the fa{\c c}ade image. Finally, we introduce one more fa{\c c}ade processing algorithm, this time with the goal to improve the quality of the fa{\c c}ade appearance. The algorithm propagates visual information across the image in order to remove potential obstacles and occluding objects. The output is intended as source for textures in urban reconstruction projects. The construction of large three-dimensional urban environments itself is beyond the scope of this thesis. However, we propose a suite of tools together with mathematical foundations that contribute to the state-of-the-art and provide helpful building blocks important for large scale urban reconstruction projects.
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