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Calibration of Omnidirectional Camera by Considering Inlier Distribution

  • Yongho Hwang
  • Hyunki Hong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4259)

Abstract

This paper presents a new self-calibration algorithm of omnidirectional camera from uncalibrated images by considering the inlier distribution. First, one parametric non-linear projection model of omnidirectional camera is estimated with the known rotation and translation parameters. After deriving projection model, we can compute an essential matrix of the camera with unknown motions, and then determine the camera positions. The standard deviations are used as a quantitative measure to select a proper inlier set. The experimental results showed that we can achieve a precise estimation of the omnidirectional camera model and extrinsic parameters including rotation and translation.

Keywords

Projection Model Camera Model Fisheye Lens Omnidirectional Image Essential Matrix 
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 2006

Authors and Affiliations

  • Yongho Hwang
    • 1
  • Hyunki Hong
    • 1
  1. 1.Dept. of Image Eng., Graduate School of Advanced Imaging Science, Multimedia and FilmChung-Ang Univ. 

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