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Efficient Pose Selection for Interactive Camera Calibration

Rojtberg, Pavel and Kuijper, Arjan (2018):
Efficient Pose Selection for Interactive Camera Calibration.
In: 2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Los Alamitos, IEEE, In: IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Munich, Germany, 2018, DOI: 10.1109/ISMAR.2018.00026,
[Online-Edition: https://doi.org/10.1109/ISMAR.2018.00026],
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Rojtberg, Pavel and Kuijper, Arjan
Title: Efficient Pose Selection for Interactive Camera Calibration
Language: English
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.

Title of Book: 2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Place of Publication: Los Alamitos
Publisher: IEEE
Uncontrolled Keywords: Artificial intelligence (AI), Vision understanding, Scene understanding, Modeling of physical attributes, Recovery of physical attributes, Pattern recognition, Implementations, Interactive systems
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Event Location: Munich, Germany
Event Dates: 2018
Date Deposited: 26 Jun 2019 11:44
DOI: 10.1109/ISMAR.2018.00026
Official URL: https://doi.org/10.1109/ISMAR.2018.00026
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