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A Calibration Method for the Generalized Imaging Model with Uncertain Calibration Target Coordinates

Uhlig, David; Heizmann, Michael

Abstract (englisch):
The developments in optical metrology and computer vision require more and more advanced camera models. Their geometric calibration is of essential importance. Usually, low-dimensional models are used, which however often have insufficient accuracy for the respective applications. A more sophisticated approach uses the generalized camera model. Here, each pixel is described individually by its geometric ray properties. Our efforts in this article strive to improve this model. Hence, we propose a new approach for calibration. Moreover, we show how the immense number of parameters can be efficiently calculated and how the measurement uncertainties of reference features can be effectively utilized. We demonstrate the benefits of our method through an extensive evaluation of different cameras, namely a standard webcam and a microlens-based light field camera.

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Postprint §
DOI: 10.5445/IR/1000130834
Frei zugänglich ab 26.02.2022
DOI: 10.1007/978-3-030-69535-4_33
Zugehörige Institution(en) am KIT Institut für Industrielle Informationstechnik (IIIT)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISBN: 978-3-030-69534-7
ISSN: 0302-9743, 1611-3349
KITopen-ID: 1000130834
Erschienen in Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, J, November 11 - Dezember 04, 2020. Pt. 3. Ed.: H. Ishikawa
Veranstaltung 15th Asian Conference on Computer Vision (ACCV 2020), Kyōto, Japan, 30.11.2020 – 04.12.2020
Verlag Springer Nature Switzerland AG
Seiten 541–559
Serie Lecture Notes in Computer Science ; 12624
Vorab online veröffentlicht am 25.02.2021
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