Dynamic Masking and Unmasking for Drone Surveillance: A Privacy-Preserving Solution for Real-Time Video Processing

The proliferation of drone technology in surveillance, media, and commercial applications has intensified the need for robust privacy protection measures, especially in regions with strict data protection laws like the Republic of Korea. This paper introduces a versatile video masking and unmasking system designed for real-time processing of drone footage, capable of detecting and masking sensitive objects such as faces and vehicles during flight or live video streams. Leveraging state-of-the-art object detection algorithms, including YOLOv8, the system automatically identifies these objects and applies various masking techniques to obscure them, ensuring compliance with privacy regulations. Additionally, the system includes secure unmasking functionality for authorized users, enabling controlled access to unaltered footage when necessary. The effectiveness and efficiency of the system are demonstrated through various real-world scenarios, highlighting its adaptability to different environments and its potential applications in public safety, media, and commercial surveillance. The paper also discusses future directions for enhancing the system's capabilities and expanding its use cases to further advance privacy-preserving solutions and optimize performance.