Full Camera Calibration from a Single View of Planar Scene

  • Yisong Chen
  • Horace Ip
  • Zhangjin Huang
  • Guoping Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5358)


We present a novel algorithm that applies conics to realize reliable camera calibration. In particular, we show that a single view of two coplanar circles is sufficiently powerful to give a fully automatic calibration framework that estimates both intrinsic and extrinsic parameters. This method stems from the previous work of conic based calibration and calibration-free scene analysis. It eliminates many a priori constraints such as known principal point, restrictive calibration patterns, or multiple views. Calibration is achieved statistically through identifying multiple orthogonal directions and optimizing a probability function by maximum likelihood estimate. Orthogonal vanishing points, which build the basic geometric primitives used in calibration, are identified based on the fact that they represent conjugate directions with respect to an arbitrary circle under perspective transformation. Experimental results from synthetic and real scenes demonstrate the effectiveness, accuracy, and popularity of the approach.


Augmented Reality Camera Calibration Intrinsic Parameter Principal Point Single View 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yisong Chen
    • 1
  • Horace Ip
    • 2
  • Zhangjin Huang
    • 1
  • Guoping Wang
    • 1
  1. 1.Key Laboratory of Machine Perception (Ministry of Education)Peking UniversityChina
  2. 2.Department of Computer ScienceCity University of Hong KongChina

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