Self-calibration of hybrid central catadioptric and perspective cameras

  • Authors:

  • Xiaoming Deng;Fuchao Wu;Yihong Wu;Fuqing Duan;Liang Chang;Hongan Wang

  • Affiliations:

  • Institute of Software, Chinese Academy of Sciences, P.O. Box 8718, Beijing 100190, China;National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, China;National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, China;College of Information Science and Technology, Beijing Normal University, No. 19, XinJieKouWai Street, Beijing 100875, China;College of Information Science and Technology, Beijing Normal University, No. 19, XinJieKouWai Street, Beijing 100875, China;State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, P.O. Box 8718, Beijing 100190, China

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

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Abstract

Hybrid central catadioptric and perspective cameras are desired in practice, because the hybrid camera system can capture large field of view as well as high-resolution images. However, the calibration of the system is challenging due to heavy distortions in catadioptric cameras. In addition, previous calibration methods are only suitable for the camera system consisting of perspective cameras and catadioptric cameras with only parabolic mirrors, in which priors about the intrinsic parameters of perspective cameras are required. In this work, we provide a new approach to handle the problems. We show that if the hybrid camera system consists of at least two central catadioptric and one perspective cameras, both the intrinsic and extrinsic parameters of the system can be calibrated linearly without priors about intrinsic parameters of the perspective cameras, and the supported central catadioptric cameras of our method can be more generic. In this work, an approximated polynomial model is derived and used for rectification of catadioptric image. Firstly, with the epipolar geometry between the perspective and rectified catadioptric images, the distortion parameters of the polynomial model can be estimated linearly. Then a new method is proposed to estimate the intrinsic parameters of a central catadioptric camera with the parameters in the polynomial model, and hence the catadioptric cameras can be calibrated. Finally, a linear self-calibration method for the hybrid system is given with the calibrated catadioptric cameras. The main advantage of our method is that it cannot only calibrate both the intrinsic and extrinsic parameters of the hybrid camera system, but also simplify a traditional nonlinear self-calibration of perspective cameras to a linear process. Experiments show that our proposed method is robust and reliable.