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Subtleties of extrinsic calibration of cameras with non-overlapping fields of view

Li, Zaijuan ; Willert, Volker (2022)
Subtleties of extrinsic calibration of cameras with non-overlapping fields of view.
Forum Bildverarbeitung 2018. Karlsruhe, Germany (29.11.2018-30.11.2018)
doi: 10.26083/tuprints-00017613
Conference or Workshop Item, Secondary publication, Publisher's Version

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Subtleties of extrinsic calibration of cameras with non-overlapping fields of view
Language: English
Date: 9 September 2022
Place of Publication: Darmstadt
Year of primary publication: 2018
Publisher: KIT Scientific Publishing
Book Title: Forum Bildverarbeitung 2018
Event Title: Forum Bildverarbeitung 2018
Event Location: Karlsruhe, Germany
Event Dates: 29.11.2018-30.11.2018
DOI: 10.26083/tuprints-00017613
Corresponding Links:
Origin: Secondary publication service
Abstract:

The calibration of the relative pose between rigidly connected cameras with non-overlapping fields of view (FOV) is a prerequisite for many applications. In this paper, we focus on the subtleties of experimental realization of such a calibration optimization method presented in [1]. We evaluate two strategies to adapt a given optimization process to find better local minima. The first strategy is the introduction of a quality measure for the image data used for calibration, which is based on the projection size of known planar calibration patterns on the image. We show, that introducing an additional weighting to the optimization objective chosen as a function of that quality measure improves calibration accuracy and increases robustness against noise. The second strategy to further improve accuracy is a careful data acquisition of pose pairs used for the calibration. We integrate the above strategies into different setups and demonstrate the improvement both in simulation and real-world experiment.

Uncontrolled Keywords: Quality measure, extrinsic calibration
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-176131
Classification DDC: 500 Science and mathematics > 530 Physics
600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics (from 01.08.2022 renamed Control Methods and Intelligent Systems)
Date Deposited: 09 Sep 2022 13:16
Last Modified: 19 Sep 2023 18:02
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/17613
PPN: 500153140
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