Abstract

Urban modeling has attracted many attentions since Google and Microsoft have launched their 3D geo softwares. However, in order to achieve photo-realistic results at the same level as for the latest interactive video games for high-end applications, less effort has been made to automate urban objects recognition and reconstruction. This paper consists of the automation of image-based Haussmannian facade recognition and reconstruction. The input image is firstly rectified and segmented in order to obtain a rectangular and less distorted facade image extracted from urban scenes. Then based upon various visual features and architectural knowledge, different facade elements which include windows, doors and balconies are detected including positions and also measured sizes. Combined with the depth information computed from 3D range data, the facade geometries and textures can be produced. Finally, an analysis-synthesis approach is used to reconstruct the full 3D facade representation. The processing pipeline developed for this research has also been verified and tested on various Parisian facades and confirmed the desired recognition and reconstruction results.

Keywords

Window Detection Terrestrial Laser Scan Lens Distortion Building Facade Building Volume 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Chun Liu
    • 1
  • André Gagalowicz
    • 1
  1. 1.INRIA RocquencourtFrance

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