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Calibration Method for Fisheye Camera Based on Multi-checkerboard Detection

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DOI: 10.23977/autml.2023.040104 | Downloads: 22 | Views: 425

Author(s)

Zhou Su 1,2, Zhu Xiaofeng 1, Lu Yanda 1

Affiliation(s)

1 School of Automotive Studies, Tongji University, Shanghai, China
2 Sino-German College, Tongji University, Shanghai, China

Corresponding Author

Zhu Xiaofeng

ABSTRACT

This paper proposes a fisheye camera calibration method based on multiple chessboard detection. To address the complexity and multiple-frame requirement of traditional calibration methods, this method detects multiple chessboard corner points using libcbdetect algorithm and obtains pixel coordinates. Then, it uses a depth-first search algorithm to obtain the world coordinates of the chessboard corners and calculates the homography matrix based on the world-pixel coordinates pair through RANSAC algorithm. Finally, the undistorted image is transformed into a bird's eye view (BEV) using the obtained homography matrix. This method is simple and effective, and can improve the accuracy of lane keeping functions, which is of practical significance in autonomous driving applications.

KEYWORDS

Fisheye camera, Calibration, Inverse perspective transformation, Corner detection

CITE THIS PAPER

Zhou Su, Zhu Xiaofeng, Lu Yanda, Calibration Method for Fisheye Camera Based on Multi-checkerboard Detection. Automation and Machine Learning (2023) Vol. 4: 24-31. DOI: http://dx.doi.org/10.23977/autml.2023.040104.

REFERENCES

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