A Subjective Study of Viewing Experience for Drone Videos

Stephen Boyle; Aaron Zhang; David Bull

doi:10.1109/ICIP.2019.8803747

A Subjective Study of Viewing Experience for Drone Videos

Stephen Boyle, Aaron Zhang, David Bull

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Abstract

This paper presents subjective evaluation results on the viewing experience of aerial videos shot at different drone heights. A total of fifty video sequences were generated using a simulation engine, Unreal Engine 4, for two scenarios and five different shot types. Twenty human viewers were then employed to participate a subjective experiment, providing their preference opinions on viewing experience of these videos. Through the subjective test, optimal parameters of UAV height have been identified for the evaluated shot types and scenarios. These will provide recommendation of default shot parameters for drone operation in autonomous shooting and flight planning.

Original language	English
Title of host publication	2019 26th IEEE International Conference on Image Processing (ICIP 2019)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	5
ISBN (Electronic)	978-1-5386-6249-6
ISBN (Print)	9781538662502
DOIs	https://doi.org/10.1109/ICIP.2019.8803747
Publication status	E-pub ahead of print - 26 Aug 2019

Publication series

Name
ISSN (Print)	1522-4880

Keywords

Drone cinematography
Multidrone
optimal drone parameter

Access to Document

10.1109/ICIP.2019.8803747

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at https://ieeexplore.ieee.org/document/8803747. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 4.36 MB

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Boyle, S., Zhang, A., & Bull, D. (2019). A Subjective Study of Viewing Experience for Drone Videos. In 2019 26th IEEE International Conference on Image Processing (ICIP 2019) Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIP.2019.8803747

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