Publication:
Detection of Binary Square Fiducial Markers Using an Event Camera

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Date

2021-02-10

Authors

Sarmadi, Hamid
Muñoz-Salinas, Rafael
Olivares-Mendez, Miguel A.
Medina-Carnicer, Rafael

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Institute of Electrical and Electronics Engineers
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Abstract

Event cameras are a new type of image sensors that output changes in light intensity (events) instead of absolute intensity values. They have a very high temporal resolution and a high dynamic range. In this paper, we propose a method to detect and decode binary square markers using an event camera. We detect the edges of the markers by detecting line segments in an image created from events in the current packet. The line segments are combined to form marker candidates. The bit value of marker cells is decoded using the events on their borders. To the best of our knowledge, no other approach exists for detecting square binary markers directly from an event camera. Experimental results show that the performance of our proposal is much superior to the one from the RGB ArUco marker detector. Additionally, the proposed method can run on a single CPU thread in real-time.

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Medical Subject Headings::Information Science::Information Science::Computing Methodologies::Image Processing, Computer-Assisted
Medical Subject Headings::Information Science::Information Science::Computing Methodologies::Algorithms
Medical Subject Headings::Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans
Medical Subject Headings::Health Care::Environment and Public Health::Environment::Environment, Controlled::Lighting
Medical Subject Headings::Anatomy::Sense Organs::Eye::Retina
Medical Subject Headings::Information Science::Information Science::Computing Methodologies::Computer Systems::Computers

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Keywords

Event camera, ArUco markers, Square binary markers, Silicon retina, Computer vision, Algorithms, Cameras, Image reconstruction, Image edge detection, Image segmentation, Brightness, Real-time systems, Image sensors, Marcadores fiduciales, Inteligencia artificial, Algoritmos, Procesamiento de imagen asistido por computador, Contaminación lumínica, Sistemas de computación

Citation

Sarmadi H, Muñoz-Salinas R, Olivares-Mendez MA, Medina-Carnicer R. Detection of Binary Square Fiducial Markers Using an Event Camera. IEEE Access. 2021; 9:27813-27826