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Creating Multi-Viewpoint Panoramas of Streets with Sparsely Located Buildings

  • Takayuki Okatani
  • Jun Yanagisawa
  • Daiki Tetsuka
  • Ken Sakurada
  • Koichiro Deguchi
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 92)

Abstract

This paper presents a method for creating multi-viewpoint panoramas that is particularly targeted at streets with sparsely located buildings. As is known in the literature, it is impossible to create panoramas of such scenes having a wide range of depths in a distortion-free manner. To overcome this difficulty, our method renders sharp images only for the facades of buildings and the ground surface (e.g., vacant lands and sidewalks) along the target streets; it renders blurry images for other objects in the scene to make their geometric distortion less noticeable while maintaining their presence. To perform these, our method first estimates the three-dimensional structures of the target scenes using the results obtained by SfM (structure from motion), identifies to which category (i.e., the facade surface, the ground surface, or other objects) each scene point belongs based on MRF (Markov Random Field) optimization, and creates panoramic images of the scene by mosaicing the images of the three categories. The blurry images of objects are generated by a similar technique to digital refocus of the light field photography. We present several panoramic images created by our method for streets in the tsunami-devastated areas in the north-eastern Japan coastline because of the Great East Japan Earthquake of March 11, 2011.

Keywords

Ground Surface Point Cloud Panoramic Image Street View Vacant Land 
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 2014

Authors and Affiliations

  • Takayuki Okatani
    • 1
  • Jun Yanagisawa
    • 1
  • Daiki Tetsuka
    • 1
  • Ken Sakurada
    • 1
  • Koichiro Deguchi
    • 1
  1. 1.Tohoku UniversitySendaiJapan

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