Artificial Life and Robotics

, Volume 7, Issue 3, pp 91–94 | Cite as

Camera calibration for a mobile robot prototype

Original Article
Received:
Accepted:

Abstract

Stereovision is an effective technique to use a CCD video camera to determine the 3D position of a target object from two or more simultaneous views of the scene. Camera calibration is a central issue in finding the position of objects in a stereovision system. This is usually carried out by calibrating each camera independently, and then applying a geometric transformation of the external parameters to find the geometry of the stereo setting. After calibration, the distance of various target objects in the scene can be calculated with CCD video cameras, and recovering the 3D structure from 2D images becomes simpler. However, the process of camera calibration is complicated. Based on the ideal pinhole model of a camera, we describe formulas to calculate intrinsic parameters that specify the correct camera characteristics, and extrinsic parameters that describe the spatial relationship between the camera and the world coordinate system. A simple camera calibration method for our CCD video cameras and corresponding experiment results are also given.

Key words

Camera calibration Intrinsic parameters Extrinsic parameters Pinhole model 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Zhang Z (2000) A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22:1330–1334CrossRefGoogle Scholar
  2. 2.
    Luong QT, Faugeras OD (1997) Self-calibration of a moving camera from point correspondences and fundamental matrices. Int J Comput Vision 22:261–289CrossRefGoogle Scholar
  3. 3.
    Heikkila J, Silken O (1996) Calibration procedure for short-focal-length off-the-shelf CCD cameras. Proceedings of the 13th International Conference on Pattern Recognition, Vienna, Austria, pp 166–170Google Scholar
  4. 4.
    Intel. Open source computer vision library (2000) http://developer. Intel.comGoogle Scholar
  5. 5.
    Faugeras OD, Toscani G (1987) Camera calibration for 3D computer vision. Proceedings of the International Workshop on Industrial Applications of Machine Vision and Machine Intelligence. Silken, Japan, pp 240–247Google Scholar
  6. 6.
    Tsai RY (1987) A versatile camera calibration technique for high-accuracy 3D machine metrology using off-the-shelf TV cameras and lenses. IEEE J Robotics Autom RA-3:323–344CrossRefGoogle Scholar

Copyright information

© ISAROB 2003

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringOita UniversityOitaJapan

Personalised recommendations