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Through a systematic review of relevant literature, this paper comprehensively elucidates the evolution of camera calibration techniques and analyzes key milestones in its development. It introduces traditional camera calibration, self-calibration, and neural network-based camera calibration methods along with their research status, summarizing the characteristics and applicable scenarios of each method in practical applications. Based on the latest research progress, it delineates the latest technologies and methods in the field of camera calibration, highlighting their respective advantages and limitations. Prospects for the future development of camera calibration techniques are provided, exploring potential breakthroughs in high-precision, high-robustness mapping models, and automatic, accurate marking of image feature points, thereby offering valuable insights for addressing complex scenarios in 3D measurement applications.
Zhang et al. (Tue,) studied this question.
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