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Cluster Computing

, Volume 22, Supplement 1, pp 781–793 | Cite as

Fitting a cluster of line images under central catadioptric camera

  • Huixian Duan
  • Yihong WuEmail author
  • Lei Song
  • Jun Wang
  • Na Liu
Article
  • 51 Downloads

Abstract

Generally, due to the partial occlusion, it is very difficult to correctly estimate the central catadioptric line image from its visible part. Except for the necessary and sufficient conditions that must be satisfied by a set of paracatadioptric line images, we find that if the antipodal points of image points on the visible arc are known, the fitting accuracy can be improved greatly. In this paper, we propose a new method for fitting line images, which can be applied to all central catadioptric projection. Firstly, a new relationship between a pair of antipodal image points and the camera principal point is derived. Next, using this relationship, a new method is proposed to estimate the line images. These estimated line images are used to calibrate camera intrinsic parameters to evaluate the performance of our fitting method. Experimental results on both simulated and real data have demonstrated the effectiveness of our method.

Keywords

Central catadioptric projection Line image Camera calibration 

Notes

Acknowledgements

This work is sponsored by the National Natural Science Foundation of China (61632003, 61403084, 61402116); by the Project of the Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University(ESSCKF 2015-03); and by the Shanghai Rising-Star Program (17QB1401000); and by the Application Innovation Plan of Ministry of Public Security (2017YYCXSXST030); and by the Special Funds for the Basic R&D Business Expenses of the Central Level Public Welfare Scientific Research Institutions(C17348)“The Construction of Standard Video Dataset and Intelligent Video Evaluation Platform”.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Huixian Duan
    • 1
    • 2
  • Yihong Wu
    • 3
    Email author
  • Lei Song
    • 1
  • Jun Wang
    • 1
  • Na Liu
    • 1
  1. 1.Cyber Physical System R & D Center, The Third Research Institute of Ministry of Public SecurityShanghaiChina
  2. 2.Shanghai International Technology & Trade United Co., LtdShanghaiChina
  3. 3.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of SciencesBeijingChina

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