Rotating-star Pattern for Camera Calibration
This work addresses camera calibration accuracy for 3D vision applications, but it is incremental as it builds on existing pattern-based methods.
The paper tackled the problem of aliasing artifacts in star-shaped camera calibration patterns by using a series of checkerboard patterns rotated around a central point, resulting in improved accuracy and high stability across varying exposure levels.
Camera calibration is fundamental to 3D vision, and the choice of calibration pattern greatly affects the accuracy. To address aberration issue, star-shaped pattern has been proposed as alternatives to traditional checkerboard. However, such pattern suffers from aliasing artifacts. In this paper, we present a novel solution by employing a series of checkerboard patterns rotated around a central point instead of a single star-shaped pattern. We further propose a complete feature extraction algorithm tailored for this design. Experimental results demonstrate that our approach offers improved accuracy over the conventional star-shaped pattern and achieves high stability across varying exposure levels.