Self-calibration of wireless cameras with restricted degrees of freedom

  • Authors:

  • Junbin Liu;Tim Wark;Ruan Lakemond;Sridha Sridharan

  • Affiliations:

  • Image and Video Research Lab, Queensland University of Technology, 2 George Street, Brisbane, Queensland 4000, Australia and CSIRO ICT Centre, PO Box 883, Kenmore, Queensland 4069, Australia;CSIRO ICT Centre, PO Box 883, Kenmore, Queensland 4069, Australia;Image and Video Research Lab, Queensland University of Technology, 2 George Street, Brisbane, Queensland 4000, Australia;Image and Video Research Lab, Queensland University of Technology, 2 George Street, Brisbane, Queensland 4000, Australia

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2012

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Abstract

This paper presents an approach for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical center and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. Previous methods for auto-calibration of cameras based on pure rotations fail to work in these two degenerate cases. In addition, our approach includes a modified RANdom SAmple Consensus (RANSAC) algorithm, as well as improved integration of the radial distortion coefficient in the computation of inter-image homographies. We show that these modifications are able to increase the overall efficiency, reliability and accuracy of the homography computation and calibration procedure using both synthetic and real image sequences.