Skip to main content

Advertisement

SpringerLink
Log in

Modeling of binocular vision system for 3D reconstruction with improved genetic algorithms

  • Original Article
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper models the binocular vision system focused on 3D reconstruction and describes an improved genetic algorithm (GA) for estimating camera system parameters. The two-camera system model that takes into account camera radial distortion includes a total of 24 parameters. The proposed improved GA is used to solve this nonlinear optimization problem with high dimension. In our improved GA, the adaptive control of camera parameter search interval and the catastrophe strategy with elitist preservation are employed. The experimental results indicate that our improved GA is effective to solve the multi-peak function optimization problem and the 3D reconstruction accuracy of the binocular vision system is promising.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Tsai RY (1987) A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lens. IEEE J Robot Automat RA-3(4):323–344

    Google Scholar 

  2. Weng J, Cohen P, Herniou M (1992) Camera calibration with distortion models and accuracy evaluation. IEEE Trans Pattern Anal MachIntell 14(10):965–980

    Article  Google Scholar 

  3. Ji Q, Zhang Y (2001) Camera calibration with genetic algorithms. IEEE Trans Syst, Man, Cybern. Part A: Syst Humans 31(2):120–130

    Google Scholar 

  4. Bouchouicha M, Khelifa MB, Puech W (2003) A non-linear camera calibration with genetic algorithms. Signal Processing and Its Applications. Proceedings Seventh International Symposium, 1–4 July 2003, 2:189–192

  5. Roberts M, Naftel AJ (1994) A genetic algorithm approach to camera calibration in 3D machine vision. Genetic algorithms in image processing and vision. IEE Colloquium 1–5 December 1994

  6. Hati S, Sengupta S (1999) Robust camera parameter estimation using genetic algorithm. Syst, Man, Cybern, Proc IEEE International Conference, 12–15 Oct. 1999, 4:943–947

  7. Huang HY, Qi FH (2000) A genetic algorithm approach to accurate calibration of camera. J Infrared Millim Waves 19(1):1–6

    MATH  Google Scholar 

  8. Beasley D, Bull DR, Martin RR (1993) An overview of genetic algorithms: part 1, fundamentals. Univ Comput 15(2):58–69

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National NC System Engineering Research Center, Huazhong University of Science and Technology, Wuhan, 430074, P.R. China

    Ke Zhang, Bin Xu & Hanmin Shi

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, P.R. China

    Lixin Tang

Authors
  1. Ke Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bin Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lixin Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hanmin Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ke Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, K., Xu, B., Tang, L. et al. Modeling of binocular vision system for 3D reconstruction with improved genetic algorithms. Int J Adv Manuf Technol 29, 722–728 (2006). https://doi.org/10.1007/s00170-005-2566-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-005-2566-4

Keywords

Search

Navigation