Extrinsic Camera Calibration By Using A Nonuniform Subdivision Accumulator And Orthogonal Vanishing Points

In this study, we propose an accurate and efficient algorithm for extrinsic camera calibration that utilizes an accumulator on the sphere and the orthogonal constraint of vanishing points. We develop a nonuniform subdivision method to create an accurate accumulator for validating rotation matrix hypotheses. In contrast with the multiline method for generating rotation matrix hypotheses, we utilize the parallelism and orthogonality of two lines to develop hypotheses in the spherical coordinate. Moreover, we expand our method to the scene that lacks orthogonal information. Our method achieves 99.36% precision and 99.92% recall on the York Urban Database, and it is successfully applied to real-world scenes.