Periodic Patterns Recovery for Multicamera Calibration

Lorenzo Sorgi, Andrey Bushnevskiy

Abstract

Camera calibration is an essential step for most computer vision applications. This task usually requires the consistent detection of a 2D periodic pattern across multiple views and in practice one of the main difficulties is a correct localization of the pattern origin and its orientation in case of partial occlusion. To overcome this problem many calibration tools require a full visibility of the calibration pattern, which is not always possible, especially when a multicamera systems are used. This paper addresses the specific problem of consistent recovery of the calibration pattern, captured by a multicamera systems under the condition of partial occlusion of the calibration object in several (even all) calibration images. The proposed algorithm is structured in two sequential steps aimed at the removal of the rotational and the translational components of the pattern offset transformation, which is essential for a correct calibration. The paper focuses on two common calibration patterns, the checkerboard grid and the bundle of parallel lines; however, the technique can be easily rearranged in order to cope with other classes of periodic patterns. The algorithm effectiveness has been successfully proven on the simulated data and two real calibration datasets, captured using a fisheye stereo rig.

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Paper Citation


in Harvard Style

Sorgi L. and Bushnevskiy A. (2015). Periodic Patterns Recovery for Multicamera Calibration . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 62-67. DOI: 10.5220/0005281300620067


in Bibtex Style

@conference{visapp15,
author={Lorenzo Sorgi and Andrey Bushnevskiy},
title={Periodic Patterns Recovery for Multicamera Calibration},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={62-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005281300620067},
isbn={978-989-758-089-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Periodic Patterns Recovery for Multicamera Calibration
SN - 978-989-758-089-5
AU - Sorgi L.
AU - Bushnevskiy A.
PY - 2015
SP - 62
EP - 67
DO - 10.5220/0005281300620067