A quantitative measure for the evaluation of drone-based video quality on a target

Daniela Doroftei; Geert De Cubber; Hans De Smet

doi:https://www.thinkmind.org/index.php?view=article&articleid=icas_2022_1_40_20018

A quantitative measure for the evaluation of drone-based video quality on a target

Daniela Doroftei, Geert De Cubber, Hans De Smet

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

Abstract

This paper presents a methodology to assess video quality and based on that automatically calculate drone trajectories that optimize the video quality.

Originalsprache	Englisch
Titel	Eighteenth International Conference on Autonomic and Autonomous Systems (ICAS)
Erscheinungsort	Venice, Italy
Herausgeber (Verlag)	ThinkMind
ISBN (Print)	978-1-61208-966-9
DOIs	https://doi.org/https://www.thinkmind.org/index.php?view=article&articleid=icas_2022_1_40_20018
Publikationsstatus	Veröffentlicht - 1 Juni 2022

Zugriff auf Dokument

https://www.thinkmind.org/index.php?view=article&articleid=icas_2022_1_40_20018

https://www.thinkmind.org/articles/icas_2022_1_40_20018.pdf

HFM/19-05: Simulation engine for military RPAS operations with integrated Human factors and standardised test methodologies - ALPHONSE
De Smet, H. (Leitende(r) Forscher/-in), Doroftei, L. (Forschende) & Haelterman, R. (Forschende)
1/01/19 → 31/12/23
Projekt: Forschung › Research

Dieses zitieren

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title = "A quantitative measure for the evaluation of drone-based video quality on a target",

abstract = "This paper presents a methodology to assess video quality and based on that automatically calculate drone trajectories that optimize the video quality.",

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AB - This paper presents a methodology to assess video quality and based on that automatically calculate drone trajectories that optimize the video quality.

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M3 - Conference contribution

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BT - Eighteenth International Conference on Autonomic and Autonomous Systems (ICAS)

PB - ThinkMind

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ER -

A quantitative measure for the evaluation of drone-based video quality on a target

Abstract

Zugriff auf Dokument

Projekte

HFM/19-05: Simulation engine for military RPAS operations with integrated Human factors and standardised test methodologies - ALPHONSE

Dieses zitieren