LRDDv2: Enhanced Long-Range Drone Detection Dataset with Range Information and Comprehensive Real-World Challenges
Amirreza Rouhi, Sneh Patel, Noah McCarthy, Siddiqa Khan, Hadi Khorsand, Kaleb Lefkowitz, David K.Han
TL;DR
LRDDv2 is a comprehensive drone detection dataset with over 39,000 images, including range data, designed to improve long-range UAV detection under diverse real-world conditions.
Contribution
The paper introduces LRDDv2, a significantly expanded drone detection dataset with range annotations, addressing the need for more diverse and challenging data for long-range UAV detection research.
Findings
Includes 39,516 annotated images for drone detection.
Provides range information for over 8,000 images.
Focuses on small drones at long distances in varied conditions.
Abstract
The exponential growth in Unmanned Aerial Vehicles (UAVs) usage underscores the critical need of detecting them at extended distances to ensure safe operations, especially in densely populated areas. Despite the tremendous advances made in computer vision through deep learning, the detection of these small airborne objects remains a formidable challenge. While several datasets have been developed specifically for drone detection, the need for a more extensive and diverse collection of drone image data persists, particularly for long-range detection under varying environmental conditions. We introduce here the Long Range Drone Detection (LRDD) Version 2 dataset, comprising 39,516 meticulously annotated images, as a second release of the LRDD dataset released previously. The LRDDv2 dataset enhances the LRDDv1 by incorporating a greater variety of images, providing a more diverse and…
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