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An Approach to Marker Detection in IR- and RGB-images for an Augmented Reality Marker

Topics: Engineering Applications; Engineering Applications on Robotics and Automation; Guidance, Navigation and Control; Image Processing; Industrial Automation and Robotics; Mobile Robots and Autonomous Systems; Perception and Awareness; Sensors Fusion; Vehicle Control Applications; Virtual Environment, Virtual and Augmented Reality; Vision, Recognition and Reconstruction

Authors: Aaronkumar Ehambram ; Patrick Hemme and Bernardo Wagner

Affiliation: Institute of Systems Engineering - Real Time Systems Group, Leibniz Universität Hannover, Appelstr. 9A, 30167 Hannover and Germany

Keyword(s): Computer Vision, Augmented Reality, Kinect, Intel RealSense, Pose Estimation, Retroreflective Markers, Sensor Fusion.

Related Ontology Subjects/Areas/Topics: Engineering Applications ; Image Processing ; Industrial Automation and Robotics ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Mobile Robots and Autonomous Systems ; Perception and Awareness ; Robotics and Automation ; Sensors Fusion ; Signal Processing, Sensors, Systems Modeling and Control ; Vehicle Control Applications ; Virtual Environment, Virtual and Augmented Reality ; Vision, Recognition and Reconstruction

Abstract: We introduce an augmented reality marker based on ArUco markers (Garrido-Jurado et al., 2014) that can be detected in RGB- and IR-images by using retroreflective material. Due to active perception by IR-capable camera systems the negative impact of external disturbances like change of light conditions on the marker detection is minimized. By the parallel processing architecture of RGB- and IR-images redundancy stabilizes the detection. As different retroreflective materials influence the image quality depending on the camera system, we also examined different retroreflective materials and compared the performance of the Kinect V2 and the Intel RealSense D435 regarding the detection probability depending on the geometrical distance of the augmented reality marker to the camera.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ehambram, A.; Hemme, P. and Wagner, B. (2019). An Approach to Marker Detection in IR- and RGB-images for an Augmented Reality Marker. In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-380-3; ISSN 2184-2809, SciTePress, pages 190-197. DOI: 10.5220/0007810301900197

@conference{icinco19,
author={Aaronkumar Ehambram. and Patrick Hemme. and Bernardo Wagner.},
title={An Approach to Marker Detection in IR- and RGB-images for an Augmented Reality Marker},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2019},
pages={190-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007810301900197},
isbn={978-989-758-380-3},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - An Approach to Marker Detection in IR- and RGB-images for an Augmented Reality Marker
SN - 978-989-758-380-3
IS - 2184-2809
AU - Ehambram, A.
AU - Hemme, P.
AU - Wagner, B.
PY - 2019
SP - 190
EP - 197
DO - 10.5220/0007810301900197
PB - SciTePress