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.