International Journal of Computer Vision

, Volume 61, Issue 2, pp 159–184

Data Processing Algorithms for Generating Textured 3D Building Facade Meshes from Laser Scans and Camera Images

Authors

  • Christian Frueh
    • Video and Image Processing Laboratory, Department of Electrical Engineering and Computer SciencesUniversity of California
  • Siddharth Jain
    • Video and Image Processing Laboratory, Department of Electrical Engineering and Computer SciencesUniversity of California
  • Avideh Zakhor
    • Video and Image Processing Laboratory, Department of Electrical Engineering and Computer SciencesUniversity of California
Article

DOI: 10.1023/B:VISI.0000043756.03810.dd

Cite this article as:
Frueh, C., Jain, S. & Zakhor, A. Int J Comput Vision (2005) 61: 159. doi:10.1023/B:VISI.0000043756.03810.dd

Abstract

In this paper, we develop a set of data processing algorithms for generating textured facade meshes of cities from a series of vertical 2D surface scans and camera images, obtained by a laser scanner and digital camera while driving on public roads under normal traffic conditions. These processing steps are needed to cope with imperfections and non-idealities inherent in laser scanning systems such as occlusions and reflections from glass surfaces. The data is divided into easy-to-handle quasi-linear segments corresponding to approximately straight driving direction and sequential topological order of vertical laser scans; each segment is then transformed into a depth image. Dominant building structures are detected in the depth images, and points are classified into foreground and background layers. Large holes in the background layer, caused by occlusion from foreground layer objects, are filled in by planar or horizontal interpolation. The depth image is further processed by removing isolated points and filling remaining small holes. The foreground objects also leave holes in the texture of building facades, which are filled by horizontal and vertical interpolation in low frequency regions, or by a copy-paste method otherwise. We apply the above steps to a large set of data of downtown Berkeley with several million 3D points, in order to obtain texture-mapped 3D models.

3D city modelocclusionhole fillingimage restorationtexture synthesisurban simulation
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Copyright information

© Kluwer Academic Publishers 2005