Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes

  • Authors:

  • Ioannis Stamos;Lingyun Liu;Chao Chen;George Wolberg;Gene Yu;Siavash Zokai

  • Affiliations:

  • Department of Computer Science, Hunter College/CUNY, New York, USA;Department of Computer Science, Hunter College/CUNY, New York, USA;Department of Computer Science, Hunter College/CUNY, New York, USA;Department of Computer Science, City College of New York/CUNY, New York, USA;Department of Computer Science, City College of New York/CUNY, New York, USA;Brainstorm Technology LLC, New York, USA

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2008

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Abstract

The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes.