Motion-based 3D reconstruction (SfM) with missing data has been a challenging computer
vision task since the late 90s. Under perspective camera model, one of the most di#?#cult
tasks is camera auto-calibration which determines intrinsic camera parameters without
using any known calibration object or assuming special properties of the scene. This
paper presents a novel algorithm to perform camera auto-calibration bene#?#ting from
multiple images and dealing with the missing data problem. The method supposes semi-calibrated
cameras (every intrinsic camera parameter except for the focal length is considered
to be known) and constant focal length over all the images. The solution requires
at least one image pair having at least eight common measured points. Tests veri#?#ed
that the algorithm is numerically stable and produces accurate results. Based on the
obtained camera calibration data, most reconstruction methods using perspective camera
model are able to reconstruct the 3D structure of the object, thus the technique is
of great importance for the SfM problem.
