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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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

Original language	English
Title of host publication	Eighteenth International Conference on Autonomic and Autonomous Systems (ICAS)
Place of Publication	Venice, Italy
Publisher	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
Publication status	Published - 1 Jun 2022

Keywords

Robotics

Access to Document

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. (Promotor) & Doroftei, L. (Researcher)
1/01/19 → 31/12/23
Project: Research

Cite this

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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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N2 - This paper presents a methodology to assess video quality and based on that automatically calculate drone trajectories that optimize the video quality.

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

KW - Robotics

U2 - https://www.thinkmind.org/index.php?view=article&articleid=icas_2022_1_40_20018

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

M3 - Conference contribution

SN - 978-1-61208-966-9

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

PB - ThinkMind

CY - Venice, Italy

ER -

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

Abstract

Keywords

Access to Document

Projects

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

Cite this