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International Journal of Computer Vision

, Volume 117, Issue 2, pp 111–130 | Cite as

Vanishing Point Estimation and Line Classification in a Manhattan World with a Unifying Camera Model

  • Lilian Zhang
  • Huimin Lu
  • Xiaoping Hu
  • Reinhard Koch
Article

Abstract

The problem of estimating vanishing points for visual scenes under the Manhattan world assumption has been addressed for more than a decade. Surprisingly, the special characteristic of the Manhattan world that lines should be orthogonal or parallel to each other is seldom well utilized. In this paper, we present an algorithm that accurately and efficiently estimates vanishing points and classifies lines by thoroughly taking advantage of this simple fact in the Manhattan world for images grabbed by a camera with a single effective viewpoint (e.g. perspective camera or central catadioptric camera). The algorithm is also extended to estimate the focal length of the camera when it is uncalibrated. The key novelty is to estimate three orthogonal line directions in the camera frame simultaneously instead of estimating vanishing points in the image plane directly. The performance of the proposed algorithm is demonstrated on four publicly available databases. Compared to the state-of-the-art methods, the experiments show its superiority in terms of both accuracy and efficiency.

Keywords

Vanishing points Line classification Manhattan world Unifying camera model 

Notes

Acknowledgments

This work was supported by China Scholarship Council (No. 2009611008) and National Natural Science Foundation of China (No. 61503403). The authors thank the anonymous reviewers for their valuable comments.

Supplementary material

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Supplementary material 1 (pdf 28979 KB)
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Supplementary material 2 (pdf 13905 KB)
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Supplementary material 3 (mpg 61446 KB)
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Supplementary material 4 (mpg 177574 KB)

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Lilian Zhang
    • 1
  • Huimin Lu
    • 1
  • Xiaoping Hu
    • 1
  • Reinhard Koch
    • 2
  1. 1.Department of Automatic Control, College of Mechatronics and AutomationNational University of Defense TechnologyChangshaChina
  2. 2.Institute of Computer ScienceUniversity of KielKielGermany

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