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Stratified camera calibration algorithm based on the calibrating conic
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AI
DOI：10.1364/OE.480086.png)
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Abstract
En 中文
In computer vision, camera calibration is essential for photogrammetric measurement. We propose a new stratified camera calibration method based on geometric constraints. This paper proposes several new theorems in 2D projective transformation: (1) There exists a family of lines whose parallelity remains invariable in a 2D projective transformation. These lines are parallel with the image of the infinity line. (2) There is only one line whose verticality is invariable with the family of parallel lines in a 2D projective transformation, and the principal point lies on this line. With the image of the infinite line and the dual conic of the circular points, the closed-form solution of the line passing through principal point is deduced. The angle among the target board and image plane, which influences camera calibration, is computed. We propose a new geometric interpretation of the target board's pose and solution method. To obtain appropriate poses of the target board for camera calibration, we propose a visual pose guide (VPG) of the target board system that can guide a user to move the target board to obtain appropriate images for calibration. The expected homography is defined, and its solution method is deduced. Experimental results with synthetic and real data verify correctness and validity of the proposed method. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
Keywords:
STRUCTURE-FROM-MOTION
3D RECONSTRUCTION
ACCURACY
VISION
POINTS
STEREO
SCALE
SLAM