Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45792
Title: Near Real-time Privacy Protection: Automated Location-dependent Video Blurring in UAV live-streams
Authors: AHMED, Muhammad Waqas 
ADNAN, Muhammad 
Ahmed, Muhammad
JANSSENS, Davy 
WETS, Geert 
Ahmed, Afzal
ECTORS, Wim 
Issue Date: 2025
Publisher: Elsevier
Source: Elsevier, p. 201 -208
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.
Keywords: UAV;drone;privacy;GDPR;SIFT;real-time
Document URI: http://hdl.handle.net/1942/45792
ISSN: 2352-1457
DOI: 10.1016/j.trpro.2025.03.064
Rights: 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Smart Mobility and Logistics Ecosystems
Category: C1
Type: Proceedings Paper
Appears in Collections:Research publications

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