Near Real-time Privacy Protection: Automated Location-dependent Video Blurring in UAV live-streams

In today’s world, privacy is becoming a major concern, especially with the use of drones for surveillance and recreational purposes. This paper presents a novel approach to privacy protection in UAV live-streaming by introducing an automated video blurring system that operates in near real-time, replacing time-consuming operations in the post-processing stage. Our method leverages the Scale Invariant Feature Transform algorithm to match live footage with a pre-constructed aerial template image, enabling the blurring of private properties in near real-time, allowing our UAV greater freedom of mobility whilst preserving the privacy of residents at ground level. This solution aligns with the EU’s General Data Protection Regulation (GDPR), balancing utility and privacy rights. This proposed framework has the potential to significantly aid the UAV industry by providing a practical tool for privacy preservation during aerial surveys and recreation drone flights.

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Institutions

Publication Details

Journal
Transportation research procedia
Published
2025-01-01
DOI
https://doi.org/10.1016/j.trpro.2025.03.064
Citations
4
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
19.97

Funders

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article

Near Real-time Privacy Protection: Automated Location-dependent Video Blurring in UAV live-streams

Muhammad Adnan, Davy Janssens, Wim Ectors, Geert Wets et al.
4 citations
Transportation research procedia
UAV Applications and Optimization
19.97
article

Near Real-time Privacy Protection: Automated Location-dependent Video Blurring in UAV live-streams

Muhammad Adnan, Davy Janssens, Wim Ectors, Geert Wets, Muhammad Waqas Ahmed, Afzal Ahmed
article en
4 citations

Abstract

In today’s world, privacy is becoming a major concern, especially with the use of drones for surveillance and recreational purposes. This paper presents a novel approach to privacy protection in UAV live-streaming by introducing an automated video blurring system that operates in near real-time, replacing time-consuming operations in the post-processing stage. Our method leverages the Scale Invariant Feature Transform algorithm to match live footage with a pre-constructed aerial template image, enabling the blurring of private properties in near real-time, allowing our UAV greater freedom of mobility whilst preserving the privacy of residents at ground level. This solution aligns with the EU’s General Data Protection Regulation (GDPR), balancing utility and privacy rights. This proposed framework has the potential to significantly aid the UAV industry by providing a practical tool for privacy preservation during aerial surveys and recreation drone flights.

Transportation research procediaVol. 84
Aga Khan University (PK), University of Leeds (GB), NED University of Engineering and Technology (PK), Hasselt University (BE)
Universiteit Hasselt
Openalex Percentile: Top 1%
UAV Applications and Optimization
19.97
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Near Real-time Privacy Protection: Automated Location-dependent Video Blurring in UAV live-streams — Muhammad Adnan, Davy Janssens, et al. · Transportation research procedia (2025) | TGRS Research Map | TGRS