Camera auto-calibration as Rectangular Polynomial Eigenvalue Problem

Ákos, Pernek [Pernek, Ákos (alkalmazott infor...), szerző] Automatizálási és Alkalmazott Informatikai Tanszék (BME / VIK); Levente, Hajder [Hajder, Levente (Geometriai modell...), szerző] Automatizálási és Alkalmazott Informatikai Tanszék (BME / VIK)

Angol nyelvű Tudományos Konferenciaközlemény (Könyvrészlet)
    Azonosítók
    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.
    Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
    2021-03-05 05:16