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Variation of Camera Parameters due to Common Physical Changes in Focal Length and Camera Pose

arXiv 2409.01171 ↗First posted 2 Sep 2024cs.CVcited by 0

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Abstract (arXiv)

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.

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References · 3

  1. 2017Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Artcited by 182
  2. 2020FedVision: An Online Visual Object Detection Platform Powered by Federated Learningcited by 121
  3. 2020Computer Vision based Animal Collision Avoidance Framework for Autonomous Vehiclescited by 1

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