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A Survey of 6D Object Detection Based on 3D Models for Industrial Applications

Gorschlüter, Felix ; Rojtberg, Pavel ; Pöllabauer, Thomas (2022)
A Survey of 6D Object Detection Based on 3D Models for Industrial Applications.
In: Journal of Imaging, 8 (3)
doi: 10.3390/jimaging8030053
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

Six-dimensional object detection of rigid objects is a problem especially relevant for quality control and robotic manipulation in industrial contexts. This work is a survey of the state of the art of 6D object detection with these use cases in mind, specifically focusing on algorithms trained only with 3D models or renderings thereof. Our first contribution is a listing of requirements typically encountered in industrial applications. The second contribution is a collection of quantitative evaluation results for several different 6D object detection methods trained with synthetic data and the comparison and analysis thereof. We identify the top methods for individual requirements that industrial applications have for object detectors, but find that a lack of comparable data prevents large-scale comparison over multiple aspects.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Gorschlüter, Felix ; Rojtberg, Pavel ; Pöllabauer, Thomas
Art des Eintrags: Bibliographie
Titel: A Survey of 6D Object Detection Based on 3D Models for Industrial Applications
Sprache: Englisch
Publikationsjahr: 24 Februar 2022
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Journal of Imaging
Jahrgang/Volume einer Zeitschrift: 8
(Heft-)Nummer: 3
DOI: 10.3390/jimaging8030053
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Kurzbeschreibung (Abstract):

Six-dimensional object detection of rigid objects is a problem especially relevant for quality control and robotic manipulation in industrial contexts. This work is a survey of the state of the art of 6D object detection with these use cases in mind, specifically focusing on algorithms trained only with 3D models or renderings thereof. Our first contribution is a listing of requirements typically encountered in industrial applications. The second contribution is a collection of quantitative evaluation results for several different 6D object detection methods trained with synthetic data and the comparison and analysis thereof. We identify the top methods for individual requirements that industrial applications have for object detectors, but find that a lack of comparable data prevents large-scale comparison over multiple aspects.

Freie Schlagworte: Object detection, Machine learning, 3D Computer vision, 3D Object localisation, Camera based systems
Zusätzliche Informationen:

Art.No.: 53

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 03 Mär 2022 09:01
Letzte Änderung: 03 Jul 2024 02:56
PPN: 492978506
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