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camera_calibration_and_stereo_vision

Summary

  • Marker tracking using a pair of cameras is a common task, however setting up and calibrating the cameras can be challenging
  • In the SoRo Adhesives project, we designed a stereo-vision setup; this setup can be adapted to different projects
  • The scripts used are based on the work of Temuge Batpurev which is hosted on GitHub

Key Points

  • Camera calibration relies on acquiring images of a checkerboard using two cameras (see image below)
  • This file can be used to generate checkerboards for calibration
  • In the camera calibration function, you must set three parameters: rows, columns and world_scaling
    • Rows and columns refer the number of “crosses” in each axis of the checkerboard
    • In the image below:
      rows = 5
      columns = 7
    • Note that OpenCV will throw an error if the number of rows and columns is incorrect
    • world_scaling is the physical dimension of a square on the checkerboard, it is up to you to choose the unit
  • Checkerboard images are used to obtain the intrinsic matrices and distortion coefficients of each camera individually
  • The camera calibration process also outputs a value related to the quality of the calibration (RMSE) which should be less than 0.30
  • Note that both camera frames must have the same dimensions for stereo calibration

  • It is often important to define a world frame
camera_calibration_and_stereo_vision.txt · Last modified: 2024/04/24 21:31 by wilfred

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