Automatic Recognition of Repeating Patterns in Rectified Facade Images

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s):
  • Rendering and Modeling
• Date: December 2009
• Date (Start): 2009
• Date (End): 2009
• Diploma Examination: 16. December 2009
• First Supervisor:
  • Werner Purgathofer
  • Przemyslaw Musialski

Abstract

Building facades typically consist of multiple similar tiles which are arranged quite strictly in grid-like structures. The proposed method takes advantage of translational symmetries and is able to analyze and segment facades into tiles assuming that there are horizontal and vertical repetitions of similar tiles. In order to solve this quite complex computer vision task efficiently a Monte Carlo approach is presented which samples only selected image features. This method, which is meant to be a preprocessing step for more sophisticated tile segmentation and window identification in urban reconstruction tasks, is able to robustly identify orthogonal repetitive patterns on rectified facade images even if they are partially occluded, shadowed, blurry or otherwise damaged. Additionally, the algorithm is very running time efficient because neither quality of results nor the computational complexity are significantly depending on the image size.

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BibTeX

@mastersthesis{recheis-2009-arr,
  title =      "Automatic Recognition of Repeating Patterns in Rectified
               Facade Images",
  author =     "Meinrad Recheis",
  year =       "2009",
  abstract =   "Building facades typically consist of multiple similar tiles
               which are arranged quite strictly in grid-like structures.
               The proposed method takes advantage of translational
               symmetries and is able to analyze and segment facades into
               tiles assuming that there are horizontal and vertical
               repetitions of similar tiles. In order to solve this quite
               complex computer vision task efficiently a Monte Carlo
               approach is presented which samples only selected image
               features. This method, which is meant to be a preprocessing
               step for more sophisticated tile segmentation and window
               identification in urban reconstruction tasks, is able to
               robustly identify orthogonal repetitive patterns on
               rectified facade images even if they are partially occluded,
               shadowed, blurry or otherwise damaged. Additionally, the
               algorithm is very running time efficient because neither
               quality of results nor the computational complexity are
               significantly depending on the image size.",
  month =      dec,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2009/recheis-2009-arr/",
}