Improved rotation-based self-calibration with a strategy of rotational angles

Abstract

Purely rotation-based self-calibration receives the most attention among various self-calibration methods, owing to its algorithmic simplicity. However, it is actually impossible to ensure that the camera motion for this kind of self-calibration is a pure rotation, since the rotation center should-but unfortunately may never-completely coincide with the optical center with an unknown position. Almost all conventional pure rotation methods tend to ignore any translation, so the significant errors of calibration results could be inevitably introduced. We propose a practical and effective approach to improve the purely rotation-based selfcalibration approach. The proposed approach accounts for translational offsets. According to the fact that the rotational angles between camera orientations have a very strong impact on the calibration errors from the translations, we compute the relative camera orientations prior to calibrating, then use different and very appropriate strategies for selfcalibration in different angle circumstances, to achieve better calibration results. Both synthetic data and real data are used to test the proposed approach and very good results are obtained. Comparing the experimental results with those of conventional methods, the proposed approach significantly yields higher accuracy, and therefore reduces the calibration errors by the translations.

Three-dimensional reconstruction of the cone-like aggregate pile based on binocular vision

“…(2) Calibration method based on active vision By precisely controlling the movement of the camera workbench, including pure translation, pure rotationetc., the camera can capture images from multiple angles and then use the constraint relationship between the camera motion parameters and the captured images to obtain the camera parameters. For example, Zhu [45] proposed a calibration method based on planar motion. This method considers the camera's radial, tangential, and thin lens distortion..…”

Coal Mine Rescue Robots Based on Binocular Vision: A Review of the State of the Art

“…This method provides an effective solution for camera calibration after distortion. Furthermore, camera calibration methods based on pure rotational motion and projective reconstruction also have a certain range of applications [36], [37].…”