An Improved Fast Camera Calibration Method for Mobile Terminals

  • Guan, Fang-li (School of Information Engineering. Zhejiang Agriculture and Forestry University) ;
  • Xu, Ai-jun (School of Information Engineering. Zhejiang Agriculture and Forestry University) ;
  • Jiang, Guang-yu (School of Information Engineering. Zhejiang Agriculture and Forestry University)
  • Received : 2017.07.21
  • Accepted : 2017.11.01
  • Published : 2019.10.31


Camera calibration is an important part of machine vision and close-range photogrammetry. Since current calibration methods fail to obtain ideal internal and external camera parameters with limited computing resources on mobile terminals efficiently, this paper proposes an improved fast camera calibration method for mobile terminals. Based on traditional camera calibration method, the new method introduces two-order radial distortion and tangential distortion models to establish the camera model with nonlinear distortion items. Meanwhile, the nonlinear least square L-M algorithm is used to optimize parameters iteration, the new method can quickly obtain high-precise internal and external camera parameters. The experimental results show that the new method improves the efficiency and precision of camera calibration. Terminals simulation experiment on PC indicates that the time consuming of parameter iteration reduced from 0.220 seconds to 0.063 seconds (0.234 seconds on mobile terminals) and the average reprojection error reduced from 0.25 pixel to 0.15 pixel. Therefore, the new method is an ideal mobile terminals camera calibration method which can expand the application range of 3D reconstruction and close-range photogrammetry technology on mobile terminals.


Camera Calibration Technique;Camera Distortion Correction;Close-Range Photogrammetry;Machine Vision;Mobile Terminals;Pinhole Model


Grant : The research of tree's height and DBH measurement method based on the intelligent mobile terminals, Research and extension of intelligent tree measurement system based on Android platform

Supported by : National Natural Science Foundation of China, Zhejiang Provincial Education Department


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