Variation of Camera Parameters due to Common Physical Changes in Focal Length and Camera Pose
This addresses calibration challenges for computer vision applications like autonomous vehicles, but it is incremental as it builds on an existing method to analyze trends.
The paper tackled the problem of understanding how camera parameters vary with physical changes like focal length and pose, finding that principal point deviations differ by camera type for focal length changes but are similar for pose changes likely due to gravity.
Accurate calibration of camera intrinsic parameters is crucial to various computer vision-based applications in the fields of intelligent systems, autonomous vehicles, etc. However, existing calibration schemes are incompetent for finding general trend of the variation of camera parameters due to common physical changes. In this paper, it is demonstrated that major and minor variations due to changes in focal length and camera pose, respectively, can be identified with a recently proposed calibration method. It is readily observable from the experimental results that the former variations have different trends (directions) of principal point deviation for different types of camera, possibly due to different internal lens configurations, while the latter have very similar trends in the deviation which is most likely due to direction of gravity. Finally, to confirm the validity of such unprecedented findings, 3D to 2D reprojection errors are compared for different methods of camera calibration.