Monocular camera calibration method based on modified aquila optimizer
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College of Automation Engineering, Shanghai University of Electric Power,Shanghai 200090, China

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TP391.41

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    Abstract:

    To improve the camera calibration accuracy, this paper proposes a monocular camera calibration method based on the Modified Aquila Optimizer: The internal and external parameters of the monocular camera are calculated by Zhang Zheng You calibration method. Based on the obtained camera parameters, the average reprojection error of all corners in the calibration image is calculated and the objective function is established. The Aquila Optimizer which is improved by adaptive allocation mechanism, dynamic compensation strategy and nonlinear tide strategy is used for optimization to obtain the optimal internal parameters and distortion coefficient of camera calibration. Thus, the optimization accuracy of the camera nonlinear calibration process is improved. The experimental results show that the improved Aquila optimizer algorithm has superior optimization results on different benchmark test functions. The calibration results obtained by the camera optimization calibration method proposed in this paper are more accurate, and the reprojection error is 0006 pixels.

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  • Received:
  • Revised:
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  • Online: January 04,2024
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