Rojtberg, Pavel ; Kuijper, Arjan (2018)
Efficient Pose Selection for Interactive Camera Calibration.
IEEE International Symposium on Mixed and Augmented Reality (ISMAR). Munich, Germany (16.10.2018-20.10.2018)
doi: 10.1109/ISMAR.2018.00026
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The choice of poses for camera calibration with planar patterns is only rarely considered — yet the calibration precision heavily depends on it. This work presents a pose selection method that finds a compact and robust set of calibration poses and is suitable for interactive calibration. Consequently, singular poses that would lead to an unreliable solution are avoided explicitly, while poses reducing the uncertainty of the calibration are favoured. For this, we use uncertainty propagation. Our method takes advantage of a self-identifying calibration pattern to track the camera pose in real-time. This allows to iteratively guide the user to the target poses, until the desired quality level is reached. Therefore, only a sparse set of key-frames is needed for calibration. The method is evaluated on separate training and testing sets, as well as on synthetic data. Our approach performs better than comparable solutions while requiring 30% less calibration frames.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Rojtberg, Pavel ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Efficient Pose Selection for Interactive Camera Calibration |
| Sprache: | Englisch |
| Publikationsjahr: | 2018 |
| Ort: | Los Alamitos |
| Verlag: | IEEE |
| Buchtitel: | 2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) |
| Veranstaltungstitel: | IEEE International Symposium on Mixed and Augmented Reality (ISMAR) |
| Veranstaltungsort: | Munich, Germany |
| Veranstaltungsdatum: | 16.10.2018-20.10.2018 |
| DOI: | 10.1109/ISMAR.2018.00026 |
| URL / URN: | https://doi.org/10.1109/ISMAR.2018.00026 |
| Kurzbeschreibung (Abstract): | The choice of poses for camera calibration with planar patterns is only rarely considered — yet the calibration precision heavily depends on it. This work presents a pose selection method that finds a compact and robust set of calibration poses and is suitable for interactive calibration. Consequently, singular poses that would lead to an unreliable solution are avoided explicitly, while poses reducing the uncertainty of the calibration are favoured. For this, we use uncertainty propagation. Our method takes advantage of a self-identifying calibration pattern to track the camera pose in real-time. This allows to iteratively guide the user to the target poses, until the desired quality level is reached. Therefore, only a sparse set of key-frames is needed for calibration. The method is evaluated on separate training and testing sets, as well as on synthetic data. Our approach performs better than comparable solutions while requiring 30% less calibration frames. |
| Freie Schlagworte: | Artificial intelligence (AI), Vision understanding, Scene understanding, Modeling of physical attributes, Recovery of physical attributes, Pattern recognition, Implementations, Interactive systems |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 26 Jun 2019 11:44 |
| Letzte Änderung: | 03 Jul 2024 10:37 |
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