Fully automatic and robust UAV camera calibration using chessboard patterns

Abstract

Due to weight constraints, UAVs often carry cameras with lenses that create distortions in the image. For practical applications this distortion should be removed with a proper calibration procedure, without spending too much extra time. Existing methods require costly manual interaction when the grid is not fully visible, or when not all points can be extracted. In this paper we present an algorithm to perform the calibration without any user interaction whatsoever, which works under almost all possible conditions. The only inputs are a number of pictures of a checkerboard, taken with the camera. We extract the corners from the chessboard pictures, and set up a world coordinate grid that is robust to missing corner points, occlusion and deformations. We automatically omit the pictures that are too close to another picture, to avoid giving too much weight to often viewed areas. Finally we optimize the result by iteratively removing outlier pictures from the set.